{ "@context": "https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld", "@type": "dcat:Catalog", "conformsTo": "https://project-open-data.cio.gov/v1.1/schema", "describedBy": "https://project-open-data.cio.gov/v1.1/schema/catalog.json", "dataset": [ { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=872bd8dfe0c64728a806294a51b45cb2", "landingPage": "https://afrigeo.africageoportal.com/content/esri::global-fishing-intensity-year-2020", "title": "Global Fishing Intensity (Year 2020)", "description": "
This layer shows the amount of fishing activity recorded by Automatic Identification System (AIS) for the year 2020.
 
This layer has two variables:
  1. Hours - Identification of fishing vessels in the AIS data.
  2. Fishing Hours (displayed by default) - Detection of fishing activity.

Using cloud computing, machine learning and public vessel registry information, Global Fishing Watch (GFW) analyze tens of millions of AIS positions each day to map global apparent fishing effort. Producing such a map involves two key steps: Identification of fishing vessels in the AIS data (Hours) and Detection of fishing activity (Fishing Hours). This annual summary is produced from the daily GFW AIS-based apparent fishing effort data. The daily fishing activity made available by GFW was rasterized at 100th degree resolution then aggregated to produce an annual summary for the given year. The maps show areas where likely fishing activity occurred in the year 2020 and the estimated level of fishing intensity. This information can help understand areas where fishing activity might be considered in a marine spatial planning application.

 
More information: https://globalfishingwatch.org/dataset-and-code-fishing-effort/
 

Dataset Summary

Variable Mapped: Occupancy (hours) and effort (fishing hours) in hours per sq/km

Data Projection: GCS WGS84

Service Projection: Web Mercator

Extent: Global

Cell Size: (~1km)

Source Type: Scientific/Double

Data Source: Global Fishing Watch

Data Accessed Date: September 23, 2023

Version: 2.0, released 18 March 2021

 

What can you do with this layer?

The layer can be used in analysis and visualization. This layer can be used to summarize the values withing a polygon (using zonal statistics).  Fishing effort can be used to understand the areas impacted by fishing and designate marine protection if needed.


 

See companion layers in this ArcGIS Online Group: Global Fishing Watch

", "keyword": [ "AIS", "vessel traffic", "fishing", "conservation", "ocean", "marine", "marine spatial planning", "resource protection" ], "issued": "2024-11-20T21:32:48.000Z", "modified": "2026-10-27T17:20:06.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_oceans", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-77.8400,180.0000,81.7200", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/content/esri::global-fishing-intensity-year-2020" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiledimageservices.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/global_fish_watch_annual_fleet_sum_2020_v03/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=372f24874ce841fbbc3f3798277bb387", "landingPage": "https://afrigeo.africageoportal.com/content/esri::global-fishing-intensity-monthly-time-series-year-2020", "title": "Global Fishing Intensity - Monthly Time Series (Year 2020)", "description": "
This is time-series layer of monthly fishing activity for the year 2020. This layer shows the amount of fishing activity recorded by Automatic Identification System (AIS) broken out by month. Each pixel value represents the number of hours per square kilometer of fishing activity.
 
Fishing activity can be described using the two available variables:
  1. Hours - Identification of fishing vessels in the AIS data.
  2. Fishing Hours (displayed by default) - Detection of fishing activity.

Using cloud computing, machine learning and public vessel registry information, Global Fishing Watch (GFW) analyze tens of millions of AIS positions each day to map global apparent fishing effort. Producing such a map involves two key steps: Identification of fishing vessels in the AIS data (Hours) and Detection of fishing activity (Fishing Hours).

 
This annual summary is produced from the daily GFW AIS-based apparent fishing effort data. The daily fishing activity made available by GFW was rasterized at 100th degree resolution then aggregated to produce an annual summary for the given year. The maps show areas where likely fishing activity occurred in the year 2020 and the estimated level of fishing intensity. This information can help understand areas where fishing activity might be considered in a marine spatial planning application.
 
More information: https://globalfishingwatch.org/dataset-and-code-fishing-effort/
 

Dataset summary

Variable Mapped: Occupancy (hours) and effort (fishing hours) in hours per sq/km

Dimension: Time – 12Months (Year 2020)

Data Projection: GCS WGS84

Service Projection: Web Mercator

Extent: Global

Cell Size: (~1km)

Source Type: Scientific/Double

Data Source: Global Fishing Watch

Data Accessed Date: September 23, 2023

Version: 2.0, released 18 March 2021

 

What can you do with this layer?

The layer can be used in analysis and visualization. This layer can be used to summarize the values within a polygon (using zonal statistics).  Fishing effort can be used to understand the areas impacted by fishing and designate marine protection if needed. This layer allows use of the time dimension to help understand locations and months/seasons when fishing intensity is higher or lower.

 

See companion layers in this ArcGIS Online Group: Global Fishing Watch

", "keyword": [ "AIS", "vessel traffic", "fishing", "conservation", "ocean", "marine", "marine spatial planning", "resource protection" ], "issued": "2024-11-20T20:00:05.000Z", "modified": "2026-10-27T17:17:17.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_oceans", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-77.8400,180.0000,81.7200", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/content/esri::global-fishing-intensity-monthly-time-series-year-2020" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiledimageservices.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/gfw_2020_monthly_v2/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=afd124844ba84da69c2c533d4af10a58", "landingPage": "https://afrigeo.africageoportal.com/content/esri::land-cover-classification-sentinel-2", "title": "Land Cover Classification (Sentinel-2)", "description": "

Land cover describes the surface of the earth. Land cover maps are useful in urban planning, resource management, change detection, agriculture, and a variety of other applications in which information related to earth surface is required. Land cover classification is a complex exercise and is hard to capture using traditional means. Deep learning models are highly capable of learning these complex semantics, giving superior results.
 

Using the model

Follow the guide to use the model. Before using this model, ensure that the supported deep learning libraries are installed. For more details, check Deep Learning Libraries Installer for ArcGIS.

Fine-tuning the model

This model can be fine-tuned using the Train Deep Learning Model tool. Follow the guide to fine-tune this model.
 

Input

Raster, mosaic dataset, or image service. (Preferred cell size is 10 meters.)
Note: This model is trained to work on Sentinel-2 Imagery datasets which are in WGS 1984 Web Mercator (auxiliary sphere) coordinate system (WKID 3857).
 
Output

Classified raster with the same classes as in Corine Land Cover (CLC) 2018. 

Applicable geographies
This model is expected to work well in Europe and the United States.

Model architecture
This model uses the UNet model architecture implemented in ArcGIS API for Python.
 
Accuracy metrics

This model has an overall accuracy of 82.41% with Level-1C imagery and 84.0% with Level-2A imagery, for CLC class level 2 classification (15 classes). The table below summarizes the precision, recall and F1-score of the model on the validation dataset.

 

ClassLevel-2A ImageryLevel-1C Imagery
PrecisionRecallF1 ScorePrecisionRecallF1 Score
Urban fabric0.810.830.820.820.840.83
Industrial, commercial and transport units0.740.650.690.730.660.7
Mine, dump and construction sites0.630.520.570.690.550.61
Artificial, non-agricultural vegetated areas0.700.460.550.670.470.55
Arable land0.860.900.880.860.890.87
Permanent crops0.760.730.740.750.710.73
Pastures0.750.710.730.740.710.73
Heterogeneous agricultural areas0.610.560.580.620.510.56
Forests0.880.930.900.880.920.9
Scrub and/or herbaceous vegetation associations0.740.690.720.730.670.7
Open spaces with little or no vegetation0.870.840.850.850.820.84
Inland wetlands0.810.780.800.820.770.79
Maritime wetlands0.740.760.750.870.890.88
Inland waters0.940.920.930.940.910.92
Marine waters0.980.990.980.970.980.98

 

This model has an overall accuracy of 90.79% with Level-2A imagery for CLC class level 1 classification (5 classes). The table below summarizes the precision, recall and F1-score of the model on the validation dataset.
 
ClassPrecisionRecallF1 Score
Artificial surfaces0.850.810.83
Agricultural areas0.900.910.91
Forest and semi natural areas0.910.920.92
Wetlands0.770.700.73
Water bodies0.960.970.96
 
Training data
This model has been trained on the Corine Land Cover (CLC) 2018 with the same Sentinel 2 scenes that were used to produce the database. Scene IDs for the imagery were available in the metadata of the dataset.


Sample results
Here are a few results from the model. To view more, see this story.


 


 

", "keyword": [ "land cover", "deep learning", "dlpk", "living atlas", "sentinel", "corine" ], "issued": "2021-02-17T07:21:35.000Z", "modified": "2026-09-01T07:11:48.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_analytics", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-125.4371,25.0695,42.4688,65.1465", "license": "

 This work is licensed under the Esri Master License Agreement

View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/content/esri::land-cover-classification-sentinel-2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=d1598feb7ec64101b53b96d1879f8b22&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/d1598feb7ec64101b53b96d1879f8b22_0", "title": "OpenStreetMap Leisure Areas for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) leisure areas data for Africa, which is updated every 15 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM polygon (closed way) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes leisure features defined as a query against the hosted feature layer (i.e. leisure is not blank).

In OSM, a leisure area is a place where people go in their spare time.  These features are identified with a leisure tag.  There are thousands of different tag values for leisure used in the OSM database.  In this feature layer, unique symbols are used for several of the most popular leisure types, while lesser used types are grouped in an "other" category.

Zoom in to large scales (e.g. City level or 1:80k scale) to see the leisure area features display.  You can click on a feature to get the name of the leisure area (if available).  The name of the leisure area will display by default at large scales (e.g. Street level of 1:5k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this leisure areas layer displaying just one or two leisure types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. leisure is stadium), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.  Esri may publish a few such layers (e.g. parks) that are ready to use, but not for every type of leisure area.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "leisure", "Africa", "OpenStreetMap", "park", "pitch", "garden", "pool", "stadium" ], "issued": "2021-05-17T19:42:58.000Z", "modified": "2026-11-08T19:37:01.164Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-26.9338,-55.4431,74.1261,53.9887", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/d1598feb7ec64101b53b96d1879f8b22_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Leisure/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d1598feb7ec64101b53b96d1879f8b22/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d1598feb7ec64101b53b96d1879f8b22/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d1598feb7ec64101b53b96d1879f8b22/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d1598feb7ec64101b53b96d1879f8b22/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=d00cdd36743a4a2888d760f8dbd71ce5&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/d00cdd36743a4a2888d760f8dbd71ce5_0", "title": "OpenStreetMap Tourist Attractions for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) tourist attraction point data for Africa, which is updated every 5 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM point (node) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes tourism features defined as a query against the hosted feature layer (i.e. tourism is not blank).

In OSM, tourism features are places and things of specific interest to tourists including places to see, places to stay, things and places providing information and support to tourists.  These features are identified with a tourism tag.  There are hundreds of different tag values used in the OSM database.  In this feature layer, unique symbols are used for several of the most popular tourism types, while lesser used types are grouped in an "other" category.

Zoom in to large scales (e.g. Cities level or 1:160k scale) to see the tourism features display.  You can click on a feature to get the name of the tourism feature.  The name of the feature will display by default at very large scales (e.g. Building level of 1:2k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this tourism layer displaying just one or two tourism types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. tourism is ruin), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "tourism", "Africa", "OpenStreetMap", "tourist attraction" ], "issued": "2021-05-17T19:39:01.000Z", "modified": "2026-11-11T04:33:20.143Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-25.7372,-58.8227,73.9120,43.4042", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/d00cdd36743a4a2888d760f8dbd71ce5_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Tourism/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d00cdd36743a4a2888d760f8dbd71ce5/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d00cdd36743a4a2888d760f8dbd71ce5/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d00cdd36743a4a2888d760f8dbd71ce5/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d00cdd36743a4a2888d760f8dbd71ce5/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=d36d5425c81c420fad8857c12f89e458&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/d36d5425c81c420fad8857c12f89e458_0", "title": "OpenStreetMap POIs for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) point of interest (POI) data for Africa, which is updated every 1-2 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM point (node) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file. The layer includes POIs with a large number of tags, including amenity, shop, tourism, and several more.

Zoom in to large scales (e.g. City level or 1:80k scale) to see the POI features display.  You can click on the feature to get the name of the POI.  The name of the POI will display by default at very large scales (e.g. Building level of 1:2k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this POI layer displaying just one or two types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. amenity is bar or shop is alcohol), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.  Esri may publish a few such layers that are ready to use, but not for every type of amenity.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "POI", "Africa", "OpenStreetMap", "point of interest" ], "issued": "2021-05-17T19:36:43.000Z", "modified": "2026-11-11T04:33:20.143Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-25.7372,-58.8227,73.9120,43.4042", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/d36d5425c81c420fad8857c12f89e458_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_POIs/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d36d5425c81c420fad8857c12f89e458/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d36d5425c81c420fad8857c12f89e458/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d36d5425c81c420fad8857c12f89e458/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d36d5425c81c420fad8857c12f89e458/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=fdaca2611b5b4cb485caba97eab19e1d", "landingPage": "https://afrigeo.africageoportal.com/pages/africageoportal::geoshapers-the-afrigeo-youth-project-series", "title": "GeoShapers: The AfriGEO Youth Project Series", "description": "{{description}}", "keyword": [ "" ], "issued": "2026-06-12T07:54:00.000Z", "modified": "2026-08-10T07:54:01.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "okeyopauline", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/pages/africageoportal::geoshapers-the-afrigeo-youth-project-series" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=efd2d197cc6742598b463adfa7505ed2", "landingPage": "https://afrigeo.africageoportal.com/apps/esri::sentinel-2-land-cover-explorer", "title": "Sentinel-2 Land Cover Explorer", "description": "
About the data
Land use land cover (LULC) maps are an increasingly important tool for decision-makers in many industry sectors and developing nations around the world. The information provided by these maps helps inform policy and land management decisions by better understanding and quantifying the impacts of earth processes and human activity.
ArcGIS Living Atlas of the World provides a detailed, accurate, and timely LULC map of the world. The data is the result of a three-way collaboration among Esri, Impact Observatory, and Microsoft. For more information about the data, see Sentinel-2 10m Land Use/Land Cover Time Series.

About the app
One of the foremost capabilities of this app is the dynamic change analysis. The app provides dynamic visual and statistical change by comparing annual slices of the Sentinel-2 10m Land Use/Land Cover data as you explore the map.

Overview of capabilities:
", "keyword": [ "Land Cover", "Land Use", "Sentinel-2", "Change Detection", "Change Analysis", "Imagery", "esriimageryexplorer" ], "issued": "2023-02-07T06:19:53.000Z", "modified": "2026-07-10T03:15:37.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-88.3541,180.0000,85.0511", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/apps/esri::sentinel-2-land-cover-explorer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://livingatlas.arcgis.com/landcoverexplorer/" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=7a30da7ae1ee44248e12e99c928c4939", "landingPage": "https://afrigeo.africageoportal.com/apps/esri::landsat-explorer", "title": "Landsat Explorer", "description": "
About the data
Jointly managed by NASA and the USGS, Landsat is the longest running spaceborne earth imaging and observation program in history. The Landsat program began in 1972, with the launch of Landsat 1. Beginning with Landsat 4, the program began providing mission to mission data continuity.

Landsat Collection 2 Level-2 science products, imagery from 1982 to present, are made publicly available by the USGS. The continuity in this scientific record allows for critical and reliable observation and analysis of Earth processes and changes over time.

The Landsat Level-2 multispectral imagery is available in ArcGIS Living Atlas of the World as a dynamic time enabled image service, accessible across the ArcGIS system and used to power this app. For more about the service and the data, see Landsat Level-2.

About the app
Landsat multispectral imagery helps to track and document land use and land change associated with climate change, urbanization, drought, wildfire, deforestation, and other natural processes and human activity.

Through an intuitive user experience, this app leverages a variety of ArcGIS capabilities to explore and begin to unlock the wealth of information that Landsat provides. Some of the key capabilities include:

Visual exploration of a Dynamic global mosaic of the best available Landsat scenes.

", "keyword": [ "Landsat", "Level-2", "Science Products", "imagery", "esriimageryexplorer" ], "issued": "2023-09-01T04:53:59.000Z", "modified": "2026-07-10T03:15:21.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-87.2613,180.0000,85.0511", "license": "
 This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/apps/esri::landsat-explorer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://livingatlas.arcgis.com/landsatexplorer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=23cee85fe6b449819c4dbda064f29a2c", "landingPage": "https://afrigeo.africageoportal.com/apps/esri::sentinel-1-explorer", "title": "Sentinel-1 Explorer", "description": "
About the data
Sentinel-1 is a spaceborne Synthetic Aperture Radar (SAR) imaging system and mission from the European Space Agency and the European Commission. The mission launched and began collecting imagery in 2014.

The Sentinel-1 RTC data in this collection is an analysis ready product derived from the Ground Range Detected (GRD) Level-1 products produced by the European Space Agency. Radiometric Terrain Correction (RTC) accounts for terrain variations that affect both the position of a given point on the Earth's surface and the brightness of the radar return.

With the ability to see through cloud and smoke cover, and because it does not rely on solar illumination of the Earth's surface, Sentinel-1 is able to collect useful imagery in most weather conditions, during both day and night. This data is good for wide range of land and maritime applications, from mapping floods, to deforestation, to oil spills, and more.

About the app
Sentinel-1 imagery helps to track and document land use and land change associated with climate change, urbanization, drought, wildfire, deforestation, and other natural processes and human activity.

Through an intuitive user experience, this app leverages a variety of ArcGIS capabilities to explore and begin to unlock the wealth of information that Sentinel-1 provides. Some of the key capabilities include:
", "keyword": [ "Sentinel-1", "Explorer", "RTC", "SAR", "esriimageryexplorer" ], "issued": "2024-07-09T23:21:44.000Z", "modified": "2026-07-10T03:14:45.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-85.7150,180.0000,85.0055", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/apps/esri::sentinel-1-explorer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://livingatlas.arcgis.com/sentinel1explorer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ca91605a3261409aa984f01f7d065fbc", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-1-rtc", "title": "Sentinel-1 RTC", "description": "Sentinel-1 Radiometric Terrain Corrected (RTC) 10-meter C-band synthetic aperture radar (SAR) imagery with on-the-fly functions for visualization and unit conversions for analysis. The Sentinel-1 RTC data in this collection is an analysis ready product derived from the Ground Range Detected (GRD) Level-1 products produced by the European Space Agency. Radiometric Terrain Correction accounts for terrain variations that affect both the position of a given point on the Earth's surface and the brightness of the radar return. For more information in the source data, see Sentinel-1 Radiometric Terrain Corrected (RTC) in the Microsoft Planetary Computer data catalog.

With the ability to see through cloud and smoke cover, and because it does not rely on solar illumination of the Earth's surface, Sentinel-1 is able to collect useful imagery in most weather conditions, during both day and night. This data is good for wide range of land and maritime applications, from deforestation monitoring to oil spill mapping.



Key Properties

Geographic Coverage: Global - approximately 80° North to 80° South
Temporal Coverage: 10/10/2014 – Present
Revisit Time*: ~6-days from 10/10/2014 – 12/23/2021; ~12-days from 12/23/2021 – Present
Product Type: Ground Range Detected (GRD)
Product Level: Radiometrically terrain corrected (RTC) and analysis ready
Frequency Band: C-band
Instrument Mode: Interferometric Wide Swath Mode (IW)
Source Data Coordinate System: Universal Transverse Mercator (UTM) WGS84
Service Coordinate System: Web Mercator Auxiliary Sphere WGS84 (EPSG:3857)

*Prior to Dec 23, 2021, the mission included two satellites, Sentinel-1A and Sentinel-1B. On Dec 23, 2021, Sentinel-1B experienced a power anomaly resulting in permanent loss of data transmission. The mission is currently comprised of a single satellite, Sentinel-1A.

Applications

The RTC product can be used for a wide range of applications, including:
  • Land cover classification such as forests, wetlands, water bodies, urban areas, and agricultural land
  • Change detection such as deforestation and urban growth
  • Natural hazard monitoring such as floods
  • Oceanography such as oil spill monitoring and ship detection

Available Bands/Polarizations


Dynamic Renderings and Data Transformations
  • The default rendering is False Color (VV, VH, VV/VH) in dB scale with Dynamic Range Adjustment (DRA)
  • The DRA version of each layer enables visualization of the full dynamic range of the images.
  • Various pre-defined on-the-fly Raster Functions can be selected, or custom functions created.

Image Selection/Filtering
  • A number of fields are available for filtering, including Polarization Type, Sensor, Orbit Direction, Acquisition Date, and Numdate.
  • To isolate and work with specific images, either use the ‘Image Filter’ to create custom layers or add a ‘Query Filter’ to restrict the default layer display to a specified image or group of images. NOTE: Image Filter is currently only available in Map Viewer Classic.
Additional Usage Notes
  • Image exports and Raster Analysis are limited to 4000 columns x 4000 rows per request.
  • This dynamic imagery layer can be used in Web Maps and ArcGIS Pro as well as web and mobile applications using the ArcGIS REST APIs.
", "keyword": [ "Sentinel-1", "Microsoft", "ESA", "European Space Agency", "Temporal", "RTC", "Radiometrically Terrain Corrected", "Sentinel", "AnalysisOptimized", "Analysis", "Optimized" ], "issued": "2023-03-04T00:18:16.000Z", "modified": "2023-09-29T18:02:30.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "
 This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use


Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:
If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-1-rtc" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel1.imagery1.arcgis.com/arcgis/rest/services/Sentinel1RTC/ImageServer" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=bd6b545b95654d91a0b7faf7b5e010f5", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::landsat-level-2-1", "title": "Landsat Level-2", "description": "
Landsat 4, 5, 7, 8, and 9 multispectral and multitemporal analysis ready imagery with on-the-fly renderings and indices for visualization and analysis. This layer is time enabled and includes a number band combinations and indices rendered on demand. See available spectral bands in the table below. The imagery in this layer is sourced from the Microsoft Planetary Computer Landsat Collection 2 Level-2 data catalog on Azure.


Geographic Coverage

Temporal Coverage

Product Level

  • Landsat Collection 2 Level-2 Science Products
  • NOTE: The appropriate scale factors are dynamically applied to this imagery. The pixel values provided by the service are provided as scientific floating point values for Surface Reflectance and Surface Temperature.
  • More information on Level-2 Science Products

Image Selection/Filtering

  • A number of fields are available for filtering, including Acquisition Date, Estimated Cloud Cover, and Product ID
  • To isolate and work with specific images, either use the ‘Image Filter’ to create custom layers or add a ‘Query Filter’ to restrict the default layer display to a specified image or group of images

Visual Rendering

  • The default rendering is Natural Color (bands 4,3,2) with Dynamic Range Adjustment (DRA)
  • The DRA version of each layer enables visualization of the full dynamic range of the images
  • Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions
  • Various pre-defined Raster Functions can be selected or custom functions can be created
  • Pre-defined functions:  Natural Color with DRA, Agriculture with DRA, Geology with DRA, Color Infrared with DRA, Bathymetric with DRA, Short-wave Infrared with DRA, Normalized Difference Moisture Index Colorized, NDVI Raw, NDVI Colorized, NBR Raw

Multispectral Bands  

Band

Description

Wavelength* (µm)

Spatial Resolution (m)

1

Coastal aerosol**

0.43 - 0.45

30

2

Blue

0.45 - 0.52

30

3

Green

0.52 - 0.60

30

4

Red

0.63 - 0.69

30

5

NIR

0.76 - 0.90

30

6

SWIR 1

1.55 - 1.75

30

7

SWIR 2

2.08 - 2.35

30

8

Pixel QA

NA

30

9

Surface Temperature (Kelvin)

10.4-12.5

30***

10

Surface Temperature QA

NA

30

*This is the max range for each band based on the combined missions. For reference to the distinct ranges for each mission see this document.

**Coastal Aerosol is only available from Landsat 8 and 9. This band is simply a place holder and does not contain data for the other missions. 

***The thermal band is acquired at 100 or 120 meter resolution and resampled to 30 meters.

 Learn more about the Quality Assessment (QA) Bands


Data Source

Landsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). The imagery in this layer is hosted in Azure as part of the Microsoft Planetary Computer Data Catalog.

", "keyword": [ "Landsat", "multispectral", "multitemporal", "Azure", "Planetary Computer", "imagery", "Science Products", "Level-2", "AnalysisOptimized", "Analysis", "Optimized" ], "issued": "2021-07-12T14:55:02.000Z", "modified": "2024-03-14T21:51:08.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-179.9930,-84.4572,179.9930,84.4038", "license": "
 This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:
If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::landsat-level-2-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsat.imagery1.arcgis.com/arcgis/rest/services/LandsatC2L2/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=255af1ceee844d6da8ef8440c8f90d00", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-2-level-2a", "title": "Sentinel-2 Level-2A", "description": "Sentinel-2 multispectral and multitemporal atmospherically corrected imagery with on-the-fly visual renderings and indices for visualization and analysis. This includes thirteen multispectral bands at spatial resolutions of 10, 20, and 60-meters. This Imagery Layer is sourced from the Planetary Computer Sentinel-2 Level-2A data catalog on Azure, which is updated daily with the latest available imagery.

Geographic Coverage

Temporal Coverage

Product Level

Image Selection/Filtering

Visual Rendering

Multispectral Bands

Band

Description

Wavelength (µm)

Resolution (m)

1

Coastal aerosol

0.433 - 0.453

60

2

Blue

0.458 - 0.523

10

3

Green

0.543 - 0.578

10

4

Red

0.650 - 0.680

10

5

Vegetation Red Edge

0.698 - 0.713

20

6

Vegetation Red Edge

0.733 - 0.748

20

7

Vegetation Red Edge

0.773 - 0.793

20

8

NIR

0.785 - 0.900

10

8A

Narrow NIR

0.855 - 0.875

20

9

Water vapour

0.935 - 0.955

60

10

SWIR – Cirrus

1.365 - 1.385

60

11

SWIR-1

1.565 - 1.655

20

12

SWIR-2

2.100 - 2.280

20

Additional Usage Notes

Data Source

Sentinel-2 imagery is the result of close collaboration between the European Space Agency (ESA), the European Commission and the USGS. The source data for this service is processed by Esri and hosted in Azure as as part of the Planetary Computer Data Catalog.

For information on Sentinel-2 imagery, see Sentinel-2.

", "keyword": [ "Sentinel", "Sentinel-2", "Level-2A", "multispectral", "multitemporal", "temporal", "Planetary Computer", "Azure", "AnalysisOptimized", "Analysis", "Optimized" ], "issued": "2021-07-12T19:33:31.000Z", "modified": "2023-12-21T18:24:16.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-89.0000,180.0000,83.7480", "license": "

This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-2-level-2a" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel.imagery1.arcgis.com/arcgis/rest/services/Sentinel2L2A/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=3b6115a6483a489eb00671972f9d5d89", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-carbon-monoxide-co", "title": "Sentinel-5P Level 3 - Carbon Monoxide (CO)", "description": "Sentinel-5 Precursor (5P) is a low Earth orbit polar satellite mission dedicated to monitoring air pollution. The satellite carries the state-of-the-art TROPOspheric Monitoring Instrument (TROPOMI). With TROPOMI, Sentinel-5P images air pollutants more accurately and at a higher spatial resolution than any other spaceborne instrument.

This layer provides daily global composite images of total column carbon monoxide measurements. Carbon monoxide (CO) indirectly contributes to the buildup of some greenhouse gases in the troposphere. It reacts with certain chemicals that would otherwise destroy methane and ozone, thus helping to elevate the concentrations of methane and ozone. Sentinel-5P retrieves the CO global abundance exploiting clear-sky and cloudy-sky Earth radiance measurements in the 2.3 µm spectral range of the shortwave infrared (SWIR) part of the solar spectrum. More...

Key Properties

Geographic Coverage: Global
Temporal Coverage: 11-Jul-2018 to Present
Spatial Resolution: 5 x 5 Km
Temporal Resolution: Daily*
Product Level: Level 3
Units/Physical Quantity: mol/m², Total Column
Typical Value Range: 0 - 0.1 mol/m² (0 - 100,000 μmol/m²), Certain events (wildfires) may cause these limits to be exceeded.

* While imagery is collected globally each day, the time between data collection and product availability from ESA can vary. This layer is updated as imagery products are made publicly available. See Data Collection Notes below for additional details on data availability.

Layer Configuration

Level 3 Processing Overview
The original Sentinel-5P Level 2 data from the European Space Agency has been re-gridded and merged to create a single Level 3 Cloud Optimized GeoTiff for each day of collection for each product. The software package HARP-Convert has been used to merge and re-grid the data in order to keep a single grid per orbit (that is, no aggregation across products is performed). The complete conversion to Level 3 using HARP-Convert utilizes the "bin_spatial" operation that spatially averages pixel values between overlapping scenes for a given day of collection. In addition to the merging operation, HARP Convert is used to filter pixel values for quality as well as other variables depending on product. After the merging and regridding process, OptimizeRasters is invoked to create a Level 3 Cloud Optimized GeoTiff for a given day's worth of data for each product.

Data Collection Notes
Sentinel-5 Mission Status Reports are available from the Sentinel-5P team at the European Space Agency. These reports provide information on the status of the satellite and the instrument, the associated ground segment, and any mission milestones.  From time to time, temporal data gaps may be present due to ground station outages, satellite repositioning, or recalibration of satellite instrumentation.  In all cases, any disruption to the Sentinel-5 collection pattern are documented in the Mission Status Reports. Daily collections with any data gaps are omitted from this layer.
", "keyword": [ "Sentinel-5P", "Atmosphere", "Air Pollution", "Carbon Monoxide", "CO" ], "issued": "2023-12-11T22:12:38.000Z", "modified": "2024-05-17T14:59:38.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-85.0000,180.0000,85.0000", "license": "
 This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-carbon-monoxide-co" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel5.imagery1.arcgis.com/arcgis/rest/services/S5CO/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=dafa5b805b014714b12d16ccf85ab976", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-formaldehyde-hcho", "title": "Sentinel-5P Level 3 - Formaldehyde (HCHO)", "description": "Sentinel-5 Precursor (5P) is a low Earth orbit polar satellite mission dedicated to monitoring air pollution. The satellite carries the state-of-the-art TROPOspheric Monitoring Instrument (TROPOMI). With TROPOMI, Sentinel-5P images air pollutants more accurately and at a higher spatial resolution than any other spaceborne instrument.

This layer provides daily global composite images of total column measurements of formaldehyde. Formaldehyde (HCHO) is an intermediate gas in almost all oxidation chains of Non-Methane Volatile Organic Compounds (NMVOC), leading eventually to CO2. NMVOCs are, together with NOx, CO and CH4, among the most important precursors of tropospheric O3. The major HCHO source in the remote atmosphere is CH4 oxidation. Over the continents, the oxidation of higher NMVOCs emitted from vegetation, fires, traffic and industrial sources results in important and localized enhancements of the HCHO levels.   More...

Key Properties

Geographic Coverage: Global
Temporal Coverage: 01-Jan-2019 to Present
Spatial Resolution: 5 x 5 Km
Temporal Resolution: Daily*
Product Level: Level 3
Units/Physical Quantity: mol/m², Troposheric Column
Typical Value Range: 0 - 0.001 mol/m² (0 - 1,000 μmol/m²), Certain events (wildfires) may cause these limits to be exceeded.

Layer Configuration
Level 3 Processing Overview
The original Sentinel-5P Level 2 data from the European Space Agency has been re-gridded and merged to create a single Level 3 Cloud Optimized GeoTiff for each day of collection for each product. The software package HARP-Convert has been used to merge and re-grid the data in order to keep a single grid per orbit (that is, no aggregation across products is performed). The complete conversion to Level 3 using HARP-Convert utilizes the "bin_spatial" operation that spatially averages pixel values between overlapping scenes for a given day of collection. In addition to the merging operation, HARP Convert is used to filter pixel values for quality as well as other variables depending on product. After the merging and regridding process, OptimizeRasters is invoked to create a Level 3 Cloud Optimized GeoTiff for a given day's worth of data for each product.

Data Collection Notes
Sentinel-5 Mission Status Reports are available from the Sentinel-5P team at the European Space Agency. These reports provide information on the status of the satellite and the instrument, the associated ground segment, and any mission milestones.  From time to time, temporal data gaps may be present due to ground station outages, satellite repositioning, or recalibration of satellite instrumentation.  In all cases, any disruption to the Sentinel-5 collection pattern are documented in the Mission Status Reports. Daily collections with any data gaps are omitted from this layer.
", "keyword": [ "Sentinel-5P", "Atmosphere", "Air Pollution", "Formaldehyde", "HCHO" ], "issued": "2023-12-11T22:12:41.000Z", "modified": "2024-05-17T15:00:33.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-85.0000,180.0000,85.0000", "license": "
 This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-formaldehyde-hcho" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel5.imagery1.arcgis.com/arcgis/rest/services/S5HCHO/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9101680d67654fb1b62e4a9d329e649a", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-methane-ch4", "title": "Sentinel-5P Level 3 - Methane (CH4)", "description": "Sentinel-5 Precursor (5P) is a low Earth orbit polar satellite mission dedicated to monitoring air pollution. The satellite carries the state-of-the-art TROPOspheric Monitoring Instrument (TROPOMI). With TROPOMI, Sentinel-5P images air pollutants more accurately and at a higher spatial resolution than any other spaceborne instrument.

This layer provides daily global composite images of atmospheric methane measurements. Methane (CH4) is the second most important contributor to the anthropogenically enhanced greenhouse effect. Roughly three-quarters of methane emissions are anthropogenic and as such it is important to continue the record of satellite-based measurements. TROPOMI aims at providing CH4 column concentrations with high sensitivity to the Earth's surface, good spatio/temporal coverage, and sufficient accuracy to facilitate inverse modelling of sources and sinks. More...

Key Properties

Geographic Coverage: Global
Temporal Coverage: 01-Jan-2019 to Present
Spatial Resolution: 5 x 5 Km
Temporal Resolution: Daily*
Product Level: Level 3
Units/Physical Quantity: Parts per billion, Column averaged dry air mixing ratio
Typical Value Range: 1,600 - 2,000 ppb

* While imagery is collected globally each day, the time between data collection and product availability from ESA can vary. This layer is updated as imagery products are made publicly available. See Data Collection Notes below for additional details on data availability.

Layer Configuration
Level 3 Processing Overview
The original Sentinel-5P Level 2 data from the European Space Agency, hosted on the Microsoft Planetary Computer, has been re-gridded and merged to create a single Level 3 Cloud Optimized GeoTiff for each day of collection for each product. The software package HARP-Convert has been used to merge and re-grid the data in order to keep a single grid per orbit (that is, no aggregation across products is performed). The complete conversion to Level 3 using HARP-Convert utilizes the "bin_spatial" operation that spatially averages pixel values between overlapping scenes for a given day of collection. In addition to the merging operation, HARP Convert is used to filter pixel values for quality as well as other variables depending on product. After the merging and regridding process, OptimizeRasters is invoked to create a Level 3 Cloud Optimized GeoTiff for a given day's worth of data for each product.

Data Collection Notes
Sentinel-5 Mission Status Reports are available from the Sentinel-5P team at the European Space Agency. These reports provide information on the status of the satellite and the instrument, the associated ground segment, and any mission milestones.  From time to time, temporal data gaps may be present due to ground station outages, satellite repositioning, or recalibration of satellite instrumentation.  In all cases, any disruption to the Sentinel-5 collection pattern are documented in the Mission Status Reports. Daily collections with any data gaps are omitted from this layer.


", "keyword": [ "Sentinel-5P", "Methane", "Atmosphere", "Air Pollution" ], "issued": "2023-12-11T22:12:44.000Z", "modified": "2024-05-17T14:58:50.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-85.0000,180.0000,85.0000", "license": "
 This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-methane-ch4" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel5.imagery1.arcgis.com/arcgis/rest/services/S5CH4/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e765753aaeb14ef5af32fd91e580a8c5", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-nitrogen-dioxide-no2", "title": "Sentinel-5P Level 3 - Nitrogen Dioxide (NO2)", "description": "Sentinel-5 Precursor (5P) is a low Earth orbit polar satellite mission dedicated to monitoring air pollution. The satellite carries the state-of-the-art TROPOspheric Monitoring Instrument (TROPOMI). With TROPOMI, Sentinel-5P images air pollutants more accurately and at a higher spatial resolution than any other spaceborne instrument.

This service provides daily global composite images of tropospheric nitrogen dioxide measurements. The presence of Nitrogen Dioxide (NO2) has direct negative respiratory effects and contributes to the formation and modification of other air pollutants, such as ozone and particulate matter. The Sentinel-5P NO2 data products pose an improvement over previous data sets, particularly in their unprecedented spatial resolution, but also in the separation of the stratospheric and tropospheric contributions of the retrieved slant columns, and in the calculation of the air-mass factors used to convert slant to total columns. More...

Key Properties

Geographic Coverage: Global
Temporal Coverage: 01-Nov-2018 to Present
Spatial Resolution: 5 x 5 Km
Temporal Resolution: Daily*
Product Level: Level 3
Units/Physical Quantity: mol/m², Tropospheric Column
Typical Value Range: 0 - 0.0003 mol/m² (0 - 300 μmol/m²), Peak values for polluted cities may reach two or three times the upper value.


Layer Configuration

Level 3 Processing Overview
The original Sentinel-5P Level 2 data from the European Space Agency has been re-gridded and merged to create a single Level 3 Cloud Optimized GeoTiff for each day of collection for each product. The software package HARP-Convert has been used to merge and re-grid the data in order to keep a single grid per orbit (that is, no aggregation across products is performed). The complete conversion to Level 3 using HARP-Convert utilizes the "bin_spatial" operation that spatially averages pixel values between overlapping scenes for a given day of collection. In addition to the merging operation, HARP Convert is used to filter pixel values for quality as well as other variables depending on product. After the merging and regridding process, OptimizeRasters is invoked to create a Level 3 Cloud Optimized GeoTiff for a given day's worth of data for each product.

Data Collection Notes
Sentinel-5 Mission Status Reports are available from the Sentinel-5P team at the European Space Agency. These reports provide information on the status of the satellite and the instrument, the associated ground segment, and any mission milestones.  From time to time, temporal data gaps may be present due to ground station outages, satellite repositioning, or recalibration of satellite instrumentation.  In all cases, any disruption to the Sentinel-5 collection pattern are documented in the Mission Status Reports. Daily collections with any data gaps are omitted from this layer.
", "keyword": [ "Sentinel-5P", "Atmosphere", "Air Pollution", "Nitrogen Dioxide", "NO2", "Sentinel" ], "issued": "2023-12-11T22:12:47.000Z", "modified": "2024-05-17T14:58:25.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-85.0000,180.0000,85.0000", "license": "
 This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-nitrogen-dioxide-no2" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel5.imagery1.arcgis.com/arcgis/rest/services/S5NO2/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=7f995aacf2fa4ca0bb1e10032b061832", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-ozone-o3", "title": "Sentinel-5P Level 3 - Ozone (O3)", "description": "Sentinel-5 Precursor (5P) is a low Earth orbit polar satellite mission dedicated to monitoring air pollution. The satellite carries the state-of-the-art TROPOspheric Monitoring Instrument (TROPOMI). With TROPOMI, Sentinel-5P images air pollutants more accurately and at a higher spatial resolution than any other spaceborne instrument.

This service provides daily global composite images of total column ozone measurements. Ozone (O3) is of crucial importance for the equilibrium of the Earth's atmosphere. In the stratosphere, the ozone layer shields the biosphere from dangerous solar ultraviolet radiation. In the troposphere, it acts as an efficient cleansing agent, but at high concentration it also becomes harmful to the health of humans, animals, and vegetation. Ozone is also an important greenhouse-gas contributor to ongoing climate change.   More...

Key Properties

Geographic Coverage: Global
Temporal Coverage: 23-Apr-2019 to Present
Spatial Resolution: 5 x 5 Km
Temporal Resolution: Daily*
Product Level: Level 3
Units/Physical Quantity: mol/m², Total Column
Typical Value Range: 0 - 0.36 mol/m² (0 - 360,000 μmol/m²)

* While imagery is collected globally each day, the time between data collection and product availability from ESA can vary. This layer is updated as imagery products are made publicly available. See Data Collection Notes below for additional details on data availability.

Layer Configuration

Level 3 Processing Overview
The original Sentinel-5P Level 2 data from the European Space Agency has been re-gridded and merged to create a single Level 3 Cloud Optimized GeoTiff for each day of collection for each product. The software package HARP-Convert has been used to merge and re-grid the data in order to keep a single grid per orbit (that is, no aggregation across products is performed). The complete conversion to Level 3 using HARP-Convert utilizes the "bin_spatial" operation that spatially averages pixel values between overlapping scenes for a given day of collection. In addition to the merging operation, HARP Convert is used to filter pixel values for quality as well as other variables depending on product. After the merging and regridding process, OptimizeRasters is invoked to create a Level 3 Cloud Optimized GeoTiff for a given day's worth of data for each product.

Data Collection Notes
Sentinel-5 Mission Status Reports are available from the Sentinel-5P team at the European Space Agency. These reports provide information on the status of the satellite and the instrument, the associated ground segment, and any mission milestones.  From time to time, temporal data gaps may be present due to ground station outages, satellite repositioning, or recalibration of satellite instrumentation.  In all cases, any disruption to the Sentinel-5 collection pattern are documented in the Mission Status Reports. Daily collections with any data gaps are omitted from this layer.
", "keyword": [ "Sentinel-5P", "Atmosphere", "Air Pollution", "Ozone", "O3" ], "issued": "2023-12-11T22:12:50.000Z", "modified": "2024-05-17T15:00:04.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-90.0000,180.0000,90.0000", "license": "
 This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-ozone-o3" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel5.imagery1.arcgis.com/arcgis/rest/services/S5O3/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a55b4201015d426e845789b67ef1ab15", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-sulfur-dioxide-so2", "title": "Sentinel-5P Level 3 - Sulfur Dioxide (SO2)", "description": "Sentinel-5 Precursor (5P) is a low Earth orbit polar satellite mission dedicated to monitoring air pollution. The satellite carries the state-of-the-art TROPOspheric Monitoring Instrument (TROPOMI). With TROPOMI, Sentinel-5P images air pollutants more accurately and at a higher spatial resolution than any other spaceborne instrument.

This layer provides daily global composite images of total column measurements of sulfur dioxide. Sulfur dioxide (SO2) enters the Earth's atmosphere through both natural (~30%) and anthropogenic processes (~70%). It plays a role in chemistry on a local and global scale and its impact ranges from short term pollution to effects on climate. The recognition of enhanced SO2 values is essential in order to detect and monitor volcanic eruptions and anthropogenic pollution sources.   More...

Key Properties

Geographic Coverage: Global
Temporal Coverage: 11-Jul-2018 to Present
Spatial Resolution: 5 x 5 Km
Temporal Resolution: Daily*
Product Level: Level 3
Units/Physical Quantity: mol/m², Total Column
Typical Value Range: 0 - 0.01 mol/m² (0 - 10,000 μmol/m²), Certain events (wildfires) may cause these limits to be exceeded.

* While imagery is collected globally each day, the time between data collection and product availability from ESA can vary. This layer is updated as imagery products are made publicly available. See Data Collection Notes below for additional details on data availability.

Layer Configuration

Level 3 Processing Overview
The original Sentinel-5P Level 2 data from the European Space Agency has been re-gridded and merged to create a single Level 3 Cloud Optimized GeoTiff for each day of collection for each product. The software package HARP-Convert has been used to merge and re-grid the data in order to keep a single grid per orbit (that is, no aggregation across products is performed). The complete conversion to Level 3 using HARP-Convert utilizes the "bin_spatial" operation that spatially averages pixel values between overlapping scenes for a given day of collection. In addition to the merging operation, HARP Convert is used to filter pixel values for quality as well as other variables depending on product. After the merging and regridding process, OptimizeRasters is invoked to create a Level 3 Cloud Optimized GeoTiff for a given day's worth of data for each product.

Data Collection Notes
Sentinel-5 Mission Status Reports are available from the Sentinel-5P team at the European Space Agency. These reports provide information on the status of the satellite and the instrument, the associated ground segment, and any mission milestones.  From time to time, temporal data gaps may be present due to ground station outages, satellite repositioning, or recalibration of satellite instrumentation.  In all cases, any disruption to the Sentinel-5 collection pattern are documented in the Mission Status Reports. Daily collections with any data gaps are omitted from this layer.
", "keyword": [ "Sentinel-5P", "Atmosphere", "Air Pollution", "Sulfur Dioxide", "SO2" ], "issued": "2023-12-11T22:12:52.000Z", "modified": "2024-05-17T14:59:12.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-85.0000,180.0000,85.0000", "license": "
 This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-5p-level-3-sulfur-dioxide-so2" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel5.imagery1.arcgis.com/arcgis/rest/services/S5SO2/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=cfcb7609de5f478eb7666240902d4d3d", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-2-10m-land-use-land-cover-time-series-1", "title": "Sentinel-2 10m Land Use/Land Cover Time Series", "description": "

This layer displays a global map of land use/land cover (LULC) derived from ESA Sentinel-2 imagery at 10m resolution. Each year is generated with Impact Observatory’s deep learning AI land classification model, trained using billions of human-labeled image pixels from the National Geographic Society. The global maps are produced by applying this model to the Sentinel-2 Level-2A image collection on Microsoft’s Planetary Computer, processing over 400,000 Earth observations per year.

The algorithm generates LULC predictions for nine classes, described in detail below.  

The year 2017 has a land cover class assigned for every pixel, but its class is based upon fewer images than the other years. The years 2018-2025 are based upon a more complete set of imagery. For this reason, the year 2017 may have less accurate land cover class assignments than the years 2018-2025.
 

Key Properties 

 
Variable mapped: Land use/land cover in 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025
Source Data Coordinate System: Universal Transverse Mercator (UTM) WGS84
Service Coordinate System: Web Mercator Auxiliary Sphere WGS84 (EPSG:3857)
Extent: Global
Source imagery: Sentinel-2 L2A
Cell Size: 10-meters
Type: Thematic
Attribution: Esri, Impact Observatory
Analysis: Optimized for analysis
Class Definitions: 
 
ValueNameDescription
1WaterAreas where water was predominantly present throughout the year; may not cover areas with sporadic or ephemeral water; contains little to no sparse vegetation, no rock outcrop nor built up features like docks; examples: rivers, ponds, lakes, oceans, flooded salt plains.
2TreesAny significant clustering of tall (~15 feet or higher) dense vegetation, typically with a closed or dense canopy; examples: wooded vegetation,  clusters of dense tall vegetation within savannas, plantations, swamp or mangroves (dense/tall vegetation with ephemeral water or canopy too thick to detect water underneath).
4Flooded vegetationAreas of any type of vegetation with obvious intermixing of water throughout a majority of the year; seasonally flooded area that is a mix of grass/shrub/trees/bare ground; examples: flooded mangroves, emergent vegetation, rice paddies and other heavily irrigated and inundated agriculture.
5CropsHuman planted/plotted cereals, grasses, and crops not at tree height; examples: corn, wheat, soy, fallow plots of structured land.
7Built AreaHuman made structures; major road and rail networks; large homogenous impervious surfaces including parking structures, office buildings and residential housing; examples: houses, dense villages / towns / cities, paved roads, asphalt.
8Bare groundAreas of rock or soil with very sparse to no vegetation for the entire year; large areas of sand and deserts with no to little vegetation; examples: exposed rock or soil, desert and sand dunes, dry salt flats/pans, dried lake beds, mines.
9Snow/IceLarge homogenous areas of permanent snow or ice, typically only in mountain areas or highest latitudes; examples: glaciers, permanent snowpack, snow fields.
10CloudsNo land cover information due to persistent cloud cover.
11RangelandOpen areas covered in homogenous grasses with little to no taller vegetation; wild cereals and grasses with no obvious human plotting (i.e., not a plotted field); examples: natural meadows and fields with sparse to no tree cover, open savanna with few to no trees, parks/golf courses/lawns, pastures. Mix of small clusters of plants or single plants dispersed on a landscape that shows exposed soil or rock; scrub-filled clearings within dense forests that are clearly not taller than trees; examples: moderate to sparse cover of bushes, shrubs and tufts of grass, savannas with very sparse grasses, trees or other plants.

NOTE: Land use focus does not provide the spatial detail of a land cover map. As such, for the built area classification, yards, parks, and groves will appear as built area rather than trees or rangeland classes.


Usage Information and Best Practices

Processing Templates

 

Visualization

 

Analysis

 

General

 

Classification Process

These maps include Version 003 of the global Sentinel-2 land use/land cover data product. It is produced by a deep learning model trained using over five billion hand-labeled Sentinel-2 pixels, sampled from over 20,000 sites distributed across all major biomes of the world.

The underlying deep learning model uses 6-bands of Sentinel-2 L2A surface reflectance data: visible blue, green, red, near infrared, and two shortwave infrared bands. To create the final map, the model is run on multiple dates of imagery throughout the year, and the outputs are composited into a final representative map for each year.

The input Sentinel-2 L2A data was accessed via Microsoft’s Planetary Computer and scaled using Microsoft Azure Batch.

 

Citation
Karra, Kontgis, et al. “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021.

Acknowledgements

Training data for this project makes use of the National Geographic Society Dynamic World training dataset, produced for the Dynamic World Project by National Geographic Society in partnership with Google and the World Resources Institute.
", "keyword": [ "Sentinel-2", "Land Cover", "Land Use", "land", "use", "cover", "10m", "global", "world", "lulc", "Time Series", "AnalysisOptimized", "Analysis", "Optimized" ], "issued": "2022-10-18T18:44:50.000Z", "modified": "2026-04-23T05:03:20.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-80.0134,180.0000,84.0326", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-2-10m-land-use-land-cover-time-series-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://ic.imagery1.arcgis.com/arcgis/rest/services/Sentinel2_10m_LandCover/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=bc6a9440f3cb41d6904b2c8831745903", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::digital-earth-africas-cropland-extents-for-africa", "title": "Digital Earth Africa's Cropland extents for Africa", "description": "

A\ncentral focus for governing bodies in Africa is the need to secure the\nnecessary food sources to support their populations. It has been estimated that\nthe current production of crops will need to double by 2050 to meet future\nneeds for food production. Higher level crop-based products that can assist\nwith managing food insecurity, such as cropping watering intensities, crop\ntypes, or crop productivity, require as a starting point precise and accurate\ncropland extent maps indicating where cropland occurs. Current cropland extent\nmaps are either inaccurate, have coarse spatial resolutions, or are not updated\nregularly. An accurate, high-resolution, and regularly updated cropland area\nmap for the African continent is therefore recognised as a gap in the current\ncrop monitoring services. 

Key Properties

Geographic Coverage: Continental Africa - approximately 37° North to 35 South
Temporal Coverage: 2019
Spatial Resolution: 10 x 10 meter
Update Frequency: TBD
Number of Bands: 3 Bands
Parent Dataset: Digital Earth Africa's Sentinel-2 Semiannual GeoMAD
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

\n\n
Digital\nEarth Africa’s cropland extent maps for Eastern, Western, and Northern Africa\nshow the estimated location of croplands in these countries for the period of\nJanuary to December 2019: 
\n\n\n\n

Cropland is\ndefined as:

\n\n

"a\npiece of land of minimum 0.01 ha (a single 10m x 10m pixel) that is\nsowed/planted and harvestable at least once within the 12 months after the\nsowing/planting date."

\n\n


\n\n

This\ndefinition will exclude non-planted grazing lands and perennial crops which can\nbe difficult for satellite imagery to differentiate from natural vegetation.

\n\n

The\nprovisional cropland extent maps have a resolution of 10 metres and were built\nusing Copernicus Sentinel-2 satellite images from 2019. The cropland extent\nmaps were built separately using extensive training data from Eastern, Western,\nand Northern Africa, coupled with a Random Forest machine learning model. A\ndetailed exploration of the methods used to produce the cropland extent map can\nbe found in the Jupyter Notebooks in DE Africa’s crop-mask GitHub\nrepository.

\n\n

Independent\nvalidation datasets suggest the following accuracies:

\n\n\n\n

The algorithms\nfor all regions tend to report more omission errors (labelling actual crops as\nnon-crops) than commission errors (labelling non-crops as crops). Where\ncommission errors occur, they tend to be focussed around wetlands and seasonal\ngrasslands which spectrally resemble some kinds of cropping.


\n\n

Available Bands


Band ID

Description

Value range

Data type

NoData/Fill value

mask

crop extent (pixel)

0 - 1

uint8

0

prob

crop probability (pixel)

0 - 100

uint8

0

filtered

crop extent (object-based)

0 - 1

uint8

0

\n\n

mask: This band\ndisplays cropped regions as a binary map. Values of 1 indicate the\npresence of crops, while a value of 0 indicates the absence of\ncropping. This band is a pixel-based cropland extent map, meaning the\nmap displays the raw output of the pixel-based Random Forest classification.

\n\n

prob: This band\ndisplays the prediction probabilities for the ‘crop’ class. As this service\nuses a random forest classifier, the prediction probabilities refer to the\npercentage of trees that voted for the random forest classification. For\nexample, if the model had 200 decision trees in the random forest, and 150 of\nthe trees voted ‘crop’, the prediction probability is 150 / 200 x 100 = 75\n%. Thresholding this band at > 50 % will produce a map identical\nto mask.

\n\n

filtered: This band displays cropped regions as a\nbinary map. Values of 1 indicate the presence of crops, while a value\nof 0 indicates the absence of cropping. This band is an object-based cropland extent map where the mask band has\nbeen filtered using an image segmentation algorithm (see this paper for\ndetails on the algorithm used). During this process, segments smaller than 1 Ha\n(100 10m x 10m pixels) are merged with neighbouring segments, resulting in a\nmap where the smallest classified region is 1 Ha in size.\nThe filtered dataset is provided as a complement to\nthe mask band; small commission errors are removed by object-based\nfiltering, and the ‘salt and pepper’ effect typical of classifying pixels is\ndiminished.

\n\n


More details on this dataset can be found here.


", "keyword": [ "crop_mask_eastern", "crop_mask_western", "crop_mask_northern", "crop_mask_southern", "crop_mask_sahel", "analysis", "agriculture", "cropland extent", "Africa", "Digital Earth Africa", "DE Africa" ], "issued": "2022-01-13T04:01:44.000Z", "modified": "2026-04-09T20:52:18.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-17.9093,-35.2421,58.7026,38.0420", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::digital-earth-africas-cropland-extents-for-africa" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://di-deafrica.img.arcgis.com/arcgis/rest/services/deafrica/cropmask/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=58526e3af88b46a3a1d1eb1738230ee3", "landingPage": "https://afrigeo.africageoportal.com/apps/esri::ecological-marine-unit-emu-explorer", "title": "Ecological Marine Unit (EMU) Explorer", "description": "

The existence, sources, distribution, circulation, and physicochemical nature of macroscale oceanic water bodies have long been a focus of oceanographic inquiry. Building on that work, this paper describes an objectively derived and globally comprehensive set of 37 distinct volumetric region units, called ecological marine units (EMUs). They are constructed on a regularly spaced ocean point-mesh grid, from sea surface to seafloor, and attributed with data from the 2018 World Ocean Atlas. 

The point attribute data are the means of the decadal averages from a 57-year climatology of six physical and chemical environment parameters (temperature, salinity, dissolved oxygen, nitrate, phosphate, and silicate). The database includes over 52 million points that depict the global ocean in x, y, and z dimensions. The point data were statistically clustered to define the 37 EMUs, which represent physically and chemically distinct water volumes based on spatial variation in the six marine environmental characteristics used. The aspatial clustering to produce the 37 EMUs did not include point location or depth as a determinant, yet strong geographic and vertical separation was observed. Twenty-two of the 37 EMUs are globally or regionally extensive, and account for 99% of the ocean volume, while the remaining 15 are smaller and shallower, and occur around coastal features. We assessed the vertical distribution of EMUs in the water column and placed them into classical depth zones representing epipelagic (0 m to 200 m), mesopelagic (200 m to 1,000 m), bathypelagic (1,000 m to 4,000 m) and abyssopelagic (>4,000 m) layers. The mapping and characterization of the EMUs represent a new spatial framework for organizing and understanding the physical, chemical, and ultimately biological properties and processes of oceanic water bodies. 

The EMUs are an initial objective partitioning of the ocean using longterm historical average data, and could be extended in the future by adding new classification variables and by introducing functionality to develop time-specific EMU distribution maps. The EMUs are an open-access resource, and as both a standardized geographic framework and a baseline physicochemical characterization of the oceanic environment, they are intended to be useful for disturbance assessments, ecosystem accounting exercises, conservation priority setting, and marine protected area network design, along with other research and management applications.

", "keyword": [ "open science", "emu", "ecological marine units", "ocean", "marine", "ecosystem", "ExU" ], "issued": "2016-09-13T20:29:05.000Z", "modified": "2026-02-19T22:46:27.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_oceans", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-71.3458,180.0000,83.7386", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/apps/esri::ecological-marine-unit-emu-explorer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://livingatlas.arcgis.com/emu" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=658732a227624146ba8322a94bc6ad8c", "landingPage": "https://afrigeo.africageoportal.com/maps/esri::live-stream-gauges", "title": "Live Stream Gauges", "description": "
Information on the amount of water flowing in streams and rivers is critical to the management of water resources, emergency response to flooding, fisheries management, and many other uses. This layer provides access to real-time stream gauge readings compiled from a variety of agencies and organizations.

Dataset Summary
The Live Stream Gauges layer contains real-time measurements of water depth from multiple reporting agencies recording at sensors across the world. This layer uses GeoEvent Processor to ingest and consolidate the many live sensor feeds, and updates itself every hour. At some gauges, flow in cubic feet per second is estimated using a stage-discharge rating curve. Flow forecasts are also provided where available. These sensor feeds are owned and maintained by the GIS community. For details on the coverage in this map and the users who contributed data for this map via the Community Maps Program, view the list of Contributors for the Live Stream Gauges Service. If you want to contribute your organization's gauges, read more about the program here.
", "keyword": [ "NOAA", "AHPS", "Flood", "Gauge", "Gage", "USGS", "NWIS", "earth observations", "environment", "esri_environment" ], "issued": "2014-06-26T20:53:23.000Z", "modified": "2026-02-19T18:41:13.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_observations", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-98.5826,27.7191,-92.9741,30.7929", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/esri::live-stream-gauges" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=52484b28322542ce97cff79046978f9e", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::landsat-gls-multispectral", "title": "Landsat GLS Multispectral", "description": "

This layer includes Landsat GLS multispectral imagery for use in visualization and analysis. This layer is time enabled and includes a number band combinations and indices rendered on demand. The layer includes Landsat 7 ETM+, Landsat 5 TM, and Landsat 4 imagery at 30m, and includes Landsat MSS imagery at 60m.

Geographic Coverage

Temporal Coverage

Analysis Ready

Image Selection/Filtering

NOTE: Turning off all filters, and loading the entire archive, may affect performance.

Visual Rendering

Multispectral Bands

\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
\n

Band

\n 		\n

Wavelength (µm)

\n
\n

\n 		\n

Landsat 7 ETM+

\n 		\n

Landsat 4-5 TM

\n 		\n

Landsat MSS

\n
\n

1

\n 		\n

0.45 – 0.52

\n 		\n

0.45 – 0.52

\n 		\n

N/A

\n
\n

2

\n 		\n

0.52 – 0.60

\n 		\n

0.52 – 0.60

\n 		\n

0.5 – 0.6

\n
\n

3

\n 		\n

0.63 – 0.69

\n 		\n

0.63 – 0.69

\n 		\n

0.6 – 0.7

\n
\n

4

\n 		\n

0.77 – 0.90

\n 		\n

0.76 – 0.90

\n 		\n

0.7 – 0.8

\n
\n

5

\n 		\n

1.55 – 1.75

\n 		\n

1.55 – 1.75

\n 		\n

0.8 – 1.1

\n
\n

6

\n 		\n

2.09 – 2.35

\n 		\n

2.08 – 2.35

\n 		\n

N/A

\n
\n\n

Other Layer Usage Notes...


Data Source

Landsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted by the Amazon Web Services as part of their Public Data Sets program. Users can access full scenes from Landsat on AWS, or alternatively access LandsatLook to review and download full scenes from the complete USGS archive.

The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit GLS.

", "keyword": [ "MS", "GLS", "Landsat", "imagery", "temporal", "multispectral" ], "issued": "2015-10-20T16:49:32.000Z", "modified": "2026-02-06T21:53:16.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-60.7671,180.0000,81.8850", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::landsat-gls-multispectral" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsat2.arcgis.com/arcgis/rest/services/LandsatGLS/MS/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=cada00e67e77433d87f639803376a0e6", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::landsat-gls-pansharpened", "title": "Landsat GLS Pansharpened", "description": "

This layer includes Landsat GLS pansharpened imagery rendered on-the-fly as Natural Color with DRA for use in visualization and analysis. This layer is time enabled and includes a number of pansharpened renderings on demand. The layer includes 30m natural color Landsat 7 ETM+, Landsat 5 TM, and Landsat 4 imagery, enhanced with 15m panchromatic imagery.

Geographic Coverage

Temporal Coverage

Analysis Ready

Image Selection/Filtering

NOTE:  Turning off all filters, and loading the entire archive, may affect performance.

Visual Rendering

Other Layer Usage Notes...

Data Source

Landsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted by the Amazon Web Services as part of their Public Data Sets program. Users can access full scenes from Landsat on AWS, or alternatively access LandsatLook to review and download full scenes from the complete USGS archive.

The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit GLS.

", "keyword": [ "PS", "Pansharpened", "GLS", "Landsat", "imagery", "temporal" ], "issued": "2015-10-20T16:49:39.000Z", "modified": "2026-09-02T05:34:29.402Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-60.7671,180.0000,81.8850", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::landsat-gls-pansharpened" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsat2.arcgis.com/arcgis/rest/services/LandsatGLS/PS/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=d9b466d6a9e647ce8d1dd5fe12eb434b", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::multispectral-landsat", "title": "Multispectral Landsat", "description": "

This layer includes Landsat GLS, Landsat 8, and Landsat 9 imagery for use in visualization and analysis. This layer is time enabled and includes a number band combinations and indices rendered on demand. The Landsat 8 and 9 imagery includes nine multispectral bands from the Operational Land Imager (OLI) and two bands from the Thermal Infrared Sensor (TIRS). It is updated daily with new imagery directly sourced from the USGS Landsat collection on AWS.

Geographic Coverage

Temporal Coverage

Product Level

Image Selection/Filtering

Visual Rendering

Multispectral Bands  

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
\n

Band

\n 		\n

Description

\n 		\n

Wavelength\n (µm)

\n 		\n

Spatial\n Resolution (m)

\n
\n

1

\n 		\n

Coastal\n aerosol

\n 		\n

0.43 - 0.45

\n 		\n

30

\n
\n

2

\n 		\n

Blue

\n 		\n

0.45 - 0.51

\n 		\n

30

\n
\n

3

\n 		\n

Green

\n 		\n

0.53 - 0.59

\n 		\n

30

\n
\n

4

\n 		\n

Red

\n 		\n

0.64 - 0.67

\n 		\n

30

\n
\n

5

\n 		\n

Near Infrared\n (NIR)

\n 		\n

0.85 - 0.88

\n 		\n

30

\n
\n

6

\n 		\n

SWIR 1

\n 		\n

1.57 - 1.65

\n 		\n

30

\n
\n

7

\n 		\n

SWIR 2

\n 		\n

2.11 - 2.29

\n 		\n

30

\n
\n

8

\n 		\n

Cirrus (in\n OLI this is band 9)

\n 		\n

1.36 - 1.38

\n 		\n

30

\n
\n

9

\n 		\n

QA Band\n (available with Collection 1)*

\n 		\n

NA

\n 		\n

30

\n

 *More about the Quality Assessment Band

TIRS Bands

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
\n

Band

\n 		\n

Description

\n 		\n

Wavelength\n (µm)

\n 		\n

Spatial\n Resolution (m)

\n
\n

10

\n 		\n

TIRS1

\n 		\n

10.60 - 11.19

\n 		\n

100 * (30)

\n
\n

11

\n 		\n

TIRS2

\n 		\n

11.50 - 12.51

\n 		\n

100 * (30)

\n

*TIRS bands are acquired at 100 meter resolution, but are resampled to 30 meter in delivered data product.

Additional Usage Notes

Data Source

Landsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted in Amazon Web Services as part of their Public Data Sets program.

For information, see Landsat 8  and Landsat 9.

*The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit GLS.

", "keyword": [ "Landsat on AWS", "Landsat", "Multispectral", "Multitemporal", "imagery", "landsat 8", "temporal", "MS", "landsat 9" ], "issued": "2015-03-19T16:21:14.000Z", "modified": "2026-02-06T21:52:35.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-65.3235,180.0000,65.3126", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::multispectral-landsat" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsat2.arcgis.com/arcgis/rest/services/Landsat/MS/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6b003010cbe64d5d8fd3ce00332593bf", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::panchromatic-landsat", "title": "Panchromatic Landsat", "description": "

This layer includes Landsat 8 and 9 imagery for use in visualization and analysis. This layer is time enabled and includes the panchromatic band from the Operational Land Imager (OLI). It is updated daily with new imagery directly sourced from the USGS Landsat collection on AWS.

Geographic Coverage

Temporal Coverage

Product Level

Image Selection/Filtering

Visual Rendering

Additional Usage Notes

Data Source

Landsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted in Amazon Web Services as part of their Public Data Sets program.

For information, see Landsat 8  and Landsat 9.

", "keyword": [ "Landsat on AWS", "Landsat", "Multitemporal", "panchromatic", "imagery", "landsat 8", "AWS", "temporal", "landsat 9" ], "issued": "2015-03-19T17:12:29.000Z", "modified": "2026-02-06T21:50:56.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-68.6273,180.0000,82.6557", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::panchromatic-landsat" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsat2.arcgis.com/arcgis/rest/services/Landsat/Pan/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a7412d0c33be4de698ad981c8ba471e6", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::pansharpened-landsat", "title": "Pansharpened Landsat", "description": "

This layer includes Landsat 8 and 9 imagery for use in visualization and analysis. This layer is time enabled and includes a number of pansharpened renderings on demand. The layer includes 15m imagery rendered on-the-fly as Natural Color with DRA.  It is updated daily with new imagery directly sourced from the USGS Landsat collection on AWS.

Geographic Coverage

Temporal Coverage

Product Level

Image Selection/Filtering

Visual Rendering

Additional Usage Notes

Data Source

Landsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted in Amazon Web Services as part of their Public Data Sets program.

For information, see Landsat 8  and Landsat 9.

", "keyword": [ "Landsat", "Landsat on AWS", "Multitemporal", "Pansharpened", "imagery", "multispectral", "landsat 8", "temporal", "PS", "landsat 9" ], "issued": "2015-03-19T16:39:35.000Z", "modified": "2026-02-06T21:49:43.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-65.3235,180.0000,65.3126", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::pansharpened-landsat" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsat2.arcgis.com/arcgis/rest/services/Landsat/PS/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=739b8a9dcf4246d3af7197878b7ec052", "landingPage": "https://afrigeo.africageoportal.com/maps/esri::sentinel-2-10-meter-land-use-land-cover-time-series", "title": "Sentinel-2 10-Meter Land Use/Land Cover Time Series", "description": "
This web map displays the land use/land cover (LULC) timeseries layer derived from ESA Sentinel-2 imagery at 10m resolution. The visualization uses blend modes and is best used in the new Map Viewer. The time slider can be used to advance through the five years of data from 2017-2021. There are also a series of bookmarks for the locations below:

Urban growth examples
Ouagadougou
Cairo/Giza
Dubai, UAE
Katy, Texas, USA
Loudoun County, Virginia

Infrastructure
Istanbul International Airport, Turkey
Grand Ethiopian Renaissance Dam, Ethiopia

Deforestation
Border of Acre and Rondonia states, Brazil
Harz Mountains, Germany

Wetlands loss
Pantanal, Brazil
Parana river, Argentina

Vegetation changing after fire
Northern California: Paradise, Redding, Clear Lake, Santa Rosa, Mendocino National Forest
Kangaroo Island, Australia
Victoria and NSW, Australia
Yakutia, Russia

Hurricane Impact
Abaco Island, Bahamas

Recent Lava Flow
Hawaii Island

Surface Mining
Brown Coal, Cottbus, Germany

Land Reclamation
Markermeer, Netherlands

Economic Development
North vs South Korea
", "keyword": [ "Land Cover", "Microsoft", "Impact Observatory", "land use", "global", "world", "sentinel" ], "issued": "2022-02-22T19:25:43.000Z", "modified": "2026-01-16T19:42:44.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_environment", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "92.0151,26.3420,92.4198,26.5227", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/esri::sentinel-2-10-meter-land-use-land-cover-time-series" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=fd61b9e0c69c4e14bebd50a9a968348c", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-2-views", "title": "Sentinel-2 Views", "description": "

Sentinel-2 Level-1C imagery with on-the-fly renderings for visualization. This imagery layer pulls directly from the Sentinel-2 on AWS collection and is updated daily with new imagery.

Sentinel-2 imagery can be applied across a number of industries, scientific disciplines, and management practices. Some applications include, but are not limited to, land cover and environmental monitoring, climate change, deforestation, disaster and emergency management, national security, plant health and precision agriculture, forest monitoring, watershed analysis and runoff predictions, land-use planning, tracking urban expansion, highlighting burned areas and estimating fire severity.

Geographic Coverage

Temporal Coverage

Product Level

Image Selection/Filtering

Visual Rendering

Multispectral Bands

Band

Description

Wavelength (µm)

Resolution (m)

1

Coastal aerosol

0.433 - 0.453

60

2

Blue

0.458 - 0.523

10

3

Green

0.543 - 0.578

10

4

Red

0.650 - 0.680

10

5

Vegetation Red Edge

0.698 - 0.713

20

6

Vegetation Red Edge

0.733 - 0.748

20

7

Vegetation Red Edge

0.773 - 0.793

20

8

NIR

0.785 - 0.900

10

8A

Narrow NIR

0.855 - 0.875

20

9

Water vapour

0.935 - 0.955

60

10

SWIR – Cirrus

1.365 - 1.385

60

11

SWIR-1

1.565 - 1.655

20

12

SWIR-2

2.100 - 2.280

20

Additional Notes

Data Source

Sentinel-2 imagery is the result of close collaboration between the (European Space Agency) ESA, the European Commission and USGS. Data is hosted by the Amazon Web Services as part of their Registry of Open Data. Users can access the imagery from Sentinel-2 on AWS, or alternatively access EarthExplorer or the Copernicus Data Space Ecosystem to download the scenes.

For information on Sentinel-2 imagery, see Sentinel-2.

", "keyword": [ "sentinel", "imagery", "multispectral", "temporal", "amazon", "MS", "esa", "sentinel on aws", "sentinel2", "sentinel2 on aws", "sentinel2 views", "sentinel-2" ], "issued": "2018-05-02T15:47:29.000Z", "modified": "2025-09-02T18:15:06.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-179.9973,-66.8050,179.9973,72.9957", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
 
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::sentinel-2-views" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel.arcgis.com/arcgis/rest/services/Sentinel2/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e33faba246b642ffab5297920c7ead55", "landingPage": "https://afrigeo.africageoportal.com/maps/africageoportal::coastlines-hotspots-in-africa", "title": "Coastlines Hotspots in Africa", "description": "The coastlines hotspots of Africa layer is part of the Digital Earth Africa coastlines dataset, representing the changes of coastlines across the continent as a summary layer producing moving window hotspots of coastal change at three differing scales of 15 km, 5 km, and 1 km. This layer is useful for visualizing regional or continental-scale patterns of coastal change.

Key Properties:

Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2000 to Present
Spatial Resolution: 30 x 30 meter
Update Frequency: Annual from 2000 - Present; 6 months from end of previous year
Parent Dataset: Landsat Collection 2 Surface Reflectance
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

More details on this dataset can be found here.
", "keyword": [ "Digital Earth Africa", "Africa", "Coastlines", "Coastline extraction", "Satellite-derived shorelines", "Coastal change", "Coastal monitoring", "Coastal erosion", "Sub-pixel waterline extraction", "Tidal modelling", "Landsat", "Open data cube", "Time-series analysis" ], "issued": "2023-08-16T17:17:22.000Z", "modified": "2025-08-12T15:00:20.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-17.5292,-34.8333,55.9539,37.3579", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/africageoportal::coastlines-hotspots-in-africa" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services8.arcgis.com/oTalEaSXAuyNT7xf/arcgis/rest/services/Coastlines_Hotspots/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e33faba246b642ffab5297920c7ead55&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::coastlines-hotspots-zoom-3", "title": "coastlines hotspots zoom 3", "description": "The coastlines hotspots of Africa layer is part of the Digital Earth Africa coastlines dataset, representing the changes of coastlines across the continent as a summary layer producing moving window hotspots of coastal change at three differing scales of 15 km, 5 km, and 1 km. This layer is useful for visualizing regional or continental-scale patterns of coastal change.

Key Properties:

Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2000 to Present
Spatial Resolution: 30 x 30 meter
Update Frequency: Annual from 2000 - Present; 6 months from end of previous year
Parent Dataset: Landsat Collection 2 Surface Reflectance
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

More details on this dataset can be found here.
", "keyword": [ "Digital Earth Africa", "Africa", "Coastlines", "Coastline extraction", "Satellite-derived shorelines", "Coastal change", "Coastal monitoring", "Coastal erosion", "Sub-pixel waterline extraction", "Tidal modelling", "Landsat", "Open data cube", "Time-series analysis" ], "issued": "2023-08-16T17:17:22.000Z", "modified": "2025-08-12T13:11:33.761Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-17.5292,-34.8333,55.9539,37.3579", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::coastlines-hotspots-zoom-3" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services8.arcgis.com/oTalEaSXAuyNT7xf/arcgis/rest/services/Coastlines_Hotspots/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e33faba246b642ffab5297920c7ead55&sublayer=3", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::coastlines-hotspots-zoom-2", "title": "coastlines hotspots zoom 2", "description": "The coastlines hotspots of Africa layer is part of the Digital Earth Africa coastlines dataset, representing the changes of coastlines across the continent as a summary layer producing moving window hotspots of coastal change at three differing scales of 15 km, 5 km, and 1 km. This layer is useful for visualizing regional or continental-scale patterns of coastal change.

Key Properties:

Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2000 to Present
Spatial Resolution: 30 x 30 meter
Update Frequency: Annual from 2000 - Present; 6 months from end of previous year
Parent Dataset: Landsat Collection 2 Surface Reflectance
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

More details on this dataset can be found here.
", "keyword": [ "Digital Earth Africa", "Africa", "Coastlines", "Coastline extraction", "Satellite-derived shorelines", "Coastal change", "Coastal monitoring", "Coastal erosion", "Sub-pixel waterline extraction", "Tidal modelling", "Landsat", "Open data cube", "Time-series analysis" ], "issued": "2023-08-16T17:17:22.000Z", "modified": "2025-08-12T13:11:43.445Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-17.5263,-34.8315,55.9451,37.3464", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::coastlines-hotspots-zoom-2" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services8.arcgis.com/oTalEaSXAuyNT7xf/arcgis/rest/services/Coastlines_Hotspots/FeatureServer/3" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/csv?layers=3" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/shapefile?layers=3" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/geojson?layers=3" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/kml?layers=3" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e33faba246b642ffab5297920c7ead55&sublayer=4", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::coastlines-hotspots-zoom-1", "title": "coastlines hotspots zoom 1", "description": "The coastlines hotspots of Africa layer is part of the Digital Earth Africa coastlines dataset, representing the changes of coastlines across the continent as a summary layer producing moving window hotspots of coastal change at three differing scales of 15 km, 5 km, and 1 km. This layer is useful for visualizing regional or continental-scale patterns of coastal change.

Key Properties:

Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2000 to Present
Spatial Resolution: 30 x 30 meter
Update Frequency: Annual from 2000 - Present; 6 months from end of previous year
Parent Dataset: Landsat Collection 2 Surface Reflectance
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

More details on this dataset can be found here.
", "keyword": [ "Digital Earth Africa", "Africa", "Coastlines", "Coastline extraction", "Satellite-derived shorelines", "Coastal change", "Coastal monitoring", "Coastal erosion", "Sub-pixel waterline extraction", "Tidal modelling", "Landsat", "Open data cube", "Time-series analysis" ], "issued": "2023-08-16T17:17:22.000Z", "modified": "2025-08-12T13:11:47.622Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-17.5193,-34.8315,55.9451,37.3424", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::coastlines-hotspots-zoom-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services8.arcgis.com/oTalEaSXAuyNT7xf/arcgis/rest/services/Coastlines_Hotspots/FeatureServer/4" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/csv?layers=4" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/shapefile?layers=4" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/geojson?layers=4" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e33faba246b642ffab5297920c7ead55/kml?layers=4" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=eba11120e3824363ad04234c1a6850fe&sublayer=6", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::africa-annual-shorelines-2000-2024", "title": "Africa Annual Shorelines (2000-2024)", "description": "
The Digital Earth Africa shorelines layer is a continental dataset that includes annual shorelines along the entire African coastline that has been generated for 2000 to Present.
 
The product combines satellite data from the Digital Earth Africa program with tidal modelling to map the typical location of the coastline at mean sea level each year. The product enables trends of coastal erosion and growth to be examined annually at both a local and continental scale, and for patterns of coastal change to be mapped historically and updated regularly as data continues to be acquired. This allows current rates of coastal change to be compared with that observed in previous years or decades.
 
The ability to map shoreline positions for each year provides valuable insights into whether changes to the coastline are the result of particular events or actions, or a process of more gradual change over time. This information can enable scientists, managers, and policy makers to assess impact from the range of drivers impacting the coastlines and potentially assist planning and forecasting for future scenarios.
 
Annual shoreline vectors from 2000 that represent the median or ‘most representative’ position of the shoreline at approximately mean sea level tide (0 m Above Mean Sea Level) for each year. Light-coloured lines (e.g. yellow) in the plot represent recent shorelines (e.g. 2024), while dark-coloured lines represent older shorelines (e.g. 2000).
 
Key Properties

 
Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2000 to Present
Spatial Resolution: 30 x 30 meter
Update Frequency: Annual from 2000 - Present; 6 months from end of previous year
Parent Dataset: Landsat Collection 2 Surface Reflectance
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

More details on this dataset can be found here.
", "keyword": [ "Coastline extraction", "Satellite-derived shorelines", "Coastal change", "Coastal monitoring", "Coastal erosion", "Sub-pixel waterline extraction", "Tidal modelling", "Landsat", "Open data cube", "Time-series analysis", "Digital Earth Africa", "Africa" ], "issued": "2022-10-26T06:43:57.000Z", "modified": "2025-08-12T12:41:39.674Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-17.5300,-34.8335,55.9651,37.3582", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::africa-annual-shorelines-2000-2024" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services8.arcgis.com/oTalEaSXAuyNT7xf/arcgis/rest/services/Annual_Shorelines/FeatureServer/6" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/eba11120e3824363ad04234c1a6850fe/csv?layers=6" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/eba11120e3824363ad04234c1a6850fe/shapefile?layers=6" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/eba11120e3824363ad04234c1a6850fe/geojson?layers=6" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/eba11120e3824363ad04234c1a6850fe/kml?layers=6" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=d12f5f00fa5c41dea3391eef49ba5215&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::rate-of-change-of-coastlines-in-africa", "title": "Rate of change of coastlines in Africa", "description": "The Digital Earth Africa Rates of change of coastlines dataset is a point dataset providing robust rates of coastal change (in metres per year) for every 30 m along Africa’s non-rocky (e.g. sandy and muddy) coastlines. These rates are calculated by linearly regressing annual shoreline positions against time, using the most recent shoreline as a baseline.

Negative values (red points) indicate retreat (e.g. erosion), and positive values indicate growth (e.g. progradation) over time. By default, rates of change are shown for points with a statistically significant trend over time only.

Key Properties
Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2000 to Present
Spatial Resolution: 30 x 30 meter
Update Frequency: Annual from 200 - Present; 6 months from end of previous year
Parent Dataset: Landsat Collection 2 Surface Reflectance
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

Rates of change statistics attributes:

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
\n

Attribute

\n
\n

rate_time

\n 		\n

Annual rates of change (in metres per year)\n calculated by linearly regressing annual shoreline distances against time\n (excluding outliers). Negative values indicate retreat and positive values\n indicate growth.

\n
\n

sig_time

\n 		\n

Significance (p-value) of the linear relationship\n between annual shoreline distances and time. Small values (e.g. p-value <\n 0.01) may indicate a coastline is undergoing consistent coastal change\n through time.

\n
\n

se_time

\n 		\n

Standard error (in metres) of the linear\n relationship between annual shoreline distances and time. This can be used to\n generate confidence intervals around the rate of change given by rate_time\n (e.g. 95% confidence interval = se_time * 1.96).

\n
\n

outl_time

\n 		\n

Individual annual shoreline are noisy estimators\n of coastline position that can be influenced by environmental conditions\n (e.g. clouds, breaking waves, sea spray) or modelling issues (e.g. poor tidal\n modelling results or limited clear satellite observations). To obtain\n reliable rates of change, outlier shorelines are excluded using a robust\n Median Absolute Deviation outlier detection algorithm, and recorded in this\n column.

\n
\n

sce

\n 		\n

Shoreline Change Envelope (SCE). A measure of the\n maximum change or variability across all annual shorelines, calculated by\n computing the maximum distance between any two annual shoreline (excluding\n outliers). This statistic excludes sub-annual shoreline variability.

\n
\n

nsm

\n 		\n

Net Shoreline Movement (NSM). The distance\n between the oldest (2000) and most recent annual shoreline (excluding\n outliers). Negative values indicate the coastline retreated between the\n oldest and most recent shoreline; positive values indicate growth. This\n statistic does not reflect sub-annual shoreline variability, so will\n underestimate the full extent of variability at any given location.

\n
\n

max_year, min_year

\n 		\n

The year that annual shorelines were at their\n maximum (i.e. located furthest towards the ocean) and their minimum (i.e.\n located furthest inland) respectively (excluding outliers). This statistic\n excludes sub-annual shoreline variability.

\n
\n

outl_time

\n 		\n

Individual annual shoreline are noisy estimators\n of coastline position that can be influenced by environmental conditions\n (e.g. clouds, breaking waves, sea spray) or modelling issues (e.g. poor tidal\n modelling results or limited clear satellite observations). To obtain\n reliable rates of change, outlier shorelines are excluded using a robust\n Median Absolute Deviation outlier detection algorithm, and recorded in this\n column.

\n

More details on this dataset can be found here.
", "keyword": [ "Digital Earth Africa", "Africa", "Coastlines", "Coastline extraction", "Satellite-derived shorelines", "Coastal change", "Coastal monitoring", "Coastal erosion", "Sub-pixel waterline extraction", "Tidal modelling", "Landsat", "Open data cube", "Time-series analysis" ], "issued": "2022-10-26T05:05:24.000Z", "modified": "2025-08-12T12:04:24.648Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-17.5300,-34.8335,55.9551,37.3582", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::rate-of-change-of-coastlines-in-africa" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services8.arcgis.com/oTalEaSXAuyNT7xf/arcgis/rest/services/DE_Africa_coastlines_v0_4_0_rates_of_change/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d12f5f00fa5c41dea3391eef49ba5215/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d12f5f00fa5c41dea3391eef49ba5215/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d12f5f00fa5c41dea3391eef49ba5215/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/d12f5f00fa5c41dea3391eef49ba5215/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=2a3dfb00c2c6425f85bd70da420d58eb", "landingPage": "https://afrigeo.africageoportal.com/content/esri::global-canopy-height-2020", "title": "Global Canopy Height 2020", "description": "
Many maps provide details of land classification types such as grassland, scrub, or tree cover. However, the total amount of biomass in these areas can vary greatly. Better mapping of the canopy height is important for understanding potential biodiversity, ecosystem function, or loss of carbon biomass due to deforestation, development, or fires.  Scientists at ETH Zurich created a method to estimate canopy height using the best available LiDAR from space and airborne sensors, including the Global Ecosystem Dynamics Investigation (GEDI) on board the International Space Station.

These LiDAR observations were used as ground truth data to train a deep convolutional neural network to regress canopy height from Sentinel-​2 images at a 10-m spatial resolution. Units are in meters. The accuracy of the vegetation height is ± 5 m.

This map was financed in a partnership with Barry Callebaut AG, the world's largest chocolate maker, to better allow companies to track deforestation in their supply chains. The intent is objective, highly automated tool to guide sustainable agribusiness.

More about this project may be read at ETH Zurich website here.
", "keyword": [ "Sentinel", "Forestry", "Height", "Vegetation", "Forest", "Canopy", "Deforestation", "global", "world", "carbon", "trees", "tree", "tree cover", "esri_environment", "environment" ], "issued": "2022-06-09T20:32:42.000Z", "modified": "2025-06-19T14:39:50.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_environment", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-60.0000,180.0000,84.0000", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/content/esri::global-canopy-height-2020" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiledimageservices.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/10m_Tree_Canopy_Height/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=f19fa6a1d73f4da5b89b99955b73fb0d", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::alos-palsar-annual-mosaics-for-africa-1", "title": "ALOS/PALSAR Annual Mosaics for Africa", "description": "

Digital Earth Africa provides access to Normalized Radar Backscatter data, for which for which Radiometric Terrain Correction (RTC) has been applied so data acquired with different imaging geometries over the same region can be compared. The ALOS/ALOS2 PALSAR is a global 25 m resolution dataset that combines data from many images captured by JAXA’s PALSAR and PALSAR-2 sensors on ALOS-1 and ALOS-2 satellites respectively. 

This product contains radar measurement in L-band and in HH and HV polarizations. It has a spatial resolution of 25m and is available annually for 2007 to 2010 (ALOS/PALSAR) and 2015 to 2021 (ALOS-2/PALSAR-2). ALOS/ALOS2 PALSAR mosaic data is part of a global dataset provided by the Japan Aerospace Exploration Agency (JAXA) Earth Observation Research Center. The relevant coverage and metadata of ALOS/ALOS2 PALSAR dataset can be viewed on DE Africa Metadata Explorer.

Key Properties

Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2007-2010, 2015 - 2021*
Spatial Resolution: 25 x 25 meter
Update frequency: Annual from 2007 to 2010 & 2015 to 2021
Product Type: Radar backscatter
Product Level: Radiometric Terrain Corrected (RTC)
Number of Bands: 5 Bands
Source Data Coordinate System: WGS 84 (World Geodetic System 1984) (EPSG:4326)
Service Coordinate System: WGS 84 (World Geodetic System 1984) (EPSG:4326)

*Time is enabled on this service using UTC – Coordinated Universal Time. To assure you are seeing the correct year for each annual slice of data, the time zone must be set specifically to UTC in the Map Viewer settings each time this layer is opened in a new map. More information on this setting can be found here: Set the map time zone.

Available Bands


Band ID

Description

Data type

No data

HH

HH backscatter

uint16

0

HV

HV backscatter

uint16

0

date

Observation date (days since launch)

uint16

0

linci

Local incidence angle

uint8

0

mask

Processing mask information

uint8

0

Backscatter data is provided as digital number (DN), which can be converted to backscatter in decibel unit using 10*log10(DN2) - 83.0 dB.
A data mask is provided that can be used to exclude pixels with potentially problematic measurements.

More information about the dataset can be found on the JAXA dataset description page.
", "keyword": [ "ALOS PALSAR", "ALOS-2 PALSAR-2", "ALOS/ALOS-2 PALSAR/PALSAR-2", "JERS SAR", "SAR", "DE Africa", "Africa", "Digital Earth Africa", "Digital Earth", "L-band", "JAXA" ], "issued": "2022-01-13T02:49:35.000Z", "modified": "2025-05-07T12:55:18.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-20.0000,-35.0003,55.0007,40.0000", "license": "
This dataset is available to use with no charge under the Terms for Use.
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::alos-palsar-annual-mosaics-for-africa-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://di-deafrica.img.arcgis.com/arcgis/rest/services/deafrica/ALOS_PALSAR/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a1c5888827b34aaa809427e31bbc2673", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::digital-earth-africas-sentinel-2-annual-geomad", "title": "Digital Earth Africa's Sentinel-2 Annual GeoMAD", "description": "

GeoMAD is\nthe Digital Earth Africa (DE Africa) surface reflectance geomedian and triple\nMedian Absolute Deviation data service. It is a cloud-free composite of\nsatellite data compiled over specific timeframes. This service is ideal for longer-term\ntime series analysis, cloudless imagery and statistical accuracy.

\n\n

GeoMAD has\ntwo main components: Geomedian and Median Absolute Deviations  (MADs)

\n\n

The\ngeomedian component combines measurements collected over the specified\ntimeframe to produce one representative, multispectral measurement for every\npixel unit of the African continent. The end result is a comprehensive dataset\nthat can be used to generate true-colour images for visual inspection of\nanthropogenic or natural landmarks. The full spectral dataset can be used to\ndevelop more complex algorithms.

\n\n

For each\npixel, invalid data is discarded, and remaining observations are mathematically\nsummarised using the geomedian statistic. Flyover coverage provided by\ncollecting data over a period of time also helps scope intermittently cloudy\nareas.

\n\n

Variations\nbetween the geomedian and the individual measurements are captured by the three\nMedian Absolute Deviation (MAD) layers. These are higher-order statistical\nmeasurements calculating variation relative to the geomedian. The MAD layers\ncan be used on their own or together with geomedian to gain insights about the\nland surface and understand change over time.

Key Properties

Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2017 – 2022*
Spatial Resolution: 10 x 10 meter
Update Frequency: Annual from 2017 - 2022
Product Type: Surface Reflectance (SR)
Product Level: Analysis Ready (ARD)
Number of Bands: 14 Bands
Parent Dataset: Sentinel-2 Level-2A Surface Reflectance
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

*Time is enabled on this service using UTC – Coordinated Universal Time. To assure you are seeing the correct year for each annual slice of data, the time zone must be set specifically to UTC in the Map Viewer settings each time this layer is opened in a new map. More information on this setting can be found here: Set the map time zone.

Applications

GeoMAD is the Digital Earth Africa (DE Africa) surface reflectance geomedian and triple Median Absolute Deviation data service. It is a cloud-free composite of satellite data compiled over specific timeframes. This service is ideal for:
  • Longer-term time series analysis
  • Cloud-free imagery
  • Statistical accuracy

Available Bands

Band ID

Description

Value range

Data type

No data value

B02

Geomedian B02 (Blue)

1 - 10000

uint16

0

B03

Geomedian B03 (Green)

1 - 10000

uint16

0

B04

Geomedian B04 (Red)

1 - 10000

uint16

0

B05

Geomedian B05 (Red edge 1)

1 - 10000

uint16

0

B06

Geomedian B06 (Red edge 2)

1 - 10000

uint16

0

B07

Geomedian B07 (Red edge 3)

1 - 10000

uint16

0

B08

Geomedian B08 (Near infrared (NIR) 1)

1 - 10000

uint16

0

B8A

Geomedian B8A (NIR 2)

1 - 10000

uint16

0

B11

Geomedian B11 (Short-wave infrared (SWIR) 1)

1 - 10000

uint16

0

B12

Geomedian B12 (SWIR 2)

1 - 10000

uint16

0

SMAD

Spectral Median Absolute Deviation

0 - 1

float32

NaN

EMAD

Euclidean Median Absolute Deviation

0 - 31623

float32

NaN

BCMAD

Bray-Curtis Median Absolute Deviation

0 - 1

float32

NaN

COUNT

Number of clear observations

1 - 65535

uint16

0

Bands can be subdivided as follows:

\n\n
Processing

All clear observations for the given time period are collated from the parent dataset. Cloudy pixels are identified and excluded. The geomedian and MADs calculations are then performed by the hdstats package. Annual GeoMAD datasets for the period use hdstats version 0.2.

More details on this dataset can be found here.
", "keyword": [ "Digital Earth Africa", "Africa", "GeoMAD", "Median Absolute Deviations", "Sentinel-2", "DE Africa", "Annual GeoMAD", "Cloud-free" ], "issued": "2021-09-23T03:36:19.000Z", "modified": "2025-04-30T18:14:27.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-27.8589,-48.3105,65.6679,38.9989", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::digital-earth-africas-sentinel-2-annual-geomad" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://di-deafrica.img.arcgis.com/arcgis/rest/services/deafrica/Geomedian_Annual/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8ab4222b2a584043a765eca942001337", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::digital-earth-africas-landsat-8-annual-geomad", "title": "Digital Earth Africa's Landsat 8 Annual GeoMAD", "description": "

GeoMAD is the\nDigital Earth Africa (DE Africa) surface reflectance geomedian and triple\nMedian Absolute Deviation data service. It is a cloud-free composite of\nsatellite data compiled over specific timeframes. This service is ideal for\nlonger-term time series analysis, cloudless imagery and statistical accuracy.

\n\n

GeoMAD has two\nmain components: Geomedian and Median Absolute Deviations (MADs).

\n\n

The geomedian component combines measurements\ncollected over the specified timeframe to produce one representative,\nmultispectral measurement for every pixel unit of the African continent. The\nend result is a comprehensive dataset that can be used to generate true-colour\nimages for visual inspection of anthropogenic or natural landmarks. The full\nspectral dataset can be used to develop more complex algorithms.

\n\n

For each pixel, invalid data is discarded, and\nremaining observations are mathematically summarised using the geomedian\nstatistic. Flyover coverage provided by collecting data over a period of time\nalso helps scope intermittently cloudy areas.

\n\n

Variations between the geomedian and the\nindividual measurements are captured by the three Median Absolute Deviation\n(MAD) layers. These are higher-order statistical measurements calculating\nvariation relative to the geomedian. The MAD layers can be used on their own or\ntogether with geomedian to gain insights about the land surface and understand\nchange over time.

Key Properties

Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2013 – 2020*
Spatial Resolution: 30 x 30 meter
Update frequency: Annual from 2013 - 2020
Product Type: Surface Reflectance (SR)
Product Level: Analysis Ready (ARD)
Number of Bands: 10 Bands
Parent Dataset: Landsat Collection 2 Level-2 Surface Reflectance
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

*Time is enabled on this service using UTC – Coordinated Universal Time. To assure you are seeing the correct year for each annual slice of data, the time zone must be set specifically to UTC in the Map Viewer settings each time this layer is opened in a new map. More information on this setting can be found here: Set the map time zone.

Applications

GeoMAD is the Digital Earth Africa (DE Africa) surface reflectance geomedian and triple Median Absolute Deviation data service. It is a cloud-free composite of satellite data compiled over specific timeframes. This service is ideal for:
  • Longer-term time series analysis
  • Cloud-free imagery
  • Statistical accuracy

Available Bands

Band ID

Description

Value range

Data type

No data value

SR_B2

Geomedian SR_B2 (Blue)

1 - 10000

uint16

0

SR_B3

Geomedian SR_B3 (Green)

1 - 10000

uint16

0

SR_B4

Geomedian SR_B4 (Red)

1 - 10000

uint16

0

SR_B5

Geomedian SR_B5 (NIR)

1 - 10000

uint16

0

SR_B6

Geomedian SR_B6 (SWIR 1)

1 - 10000

uint16

0

SR_B7

Geomedian SR_B7 (SWIR 2)

1 - 10000

uint16

0

SMAD

Spectral Median Absolute Deviation

0 - 1

float32

NaN

EMAD

Euclidean Median Absolute Deviation

0 - 31623

float32

NaN

BCMAD

Bray-Curtis Median Absolute Deviation

0 - 1

float32

NaN

COUNT

Number of clear observations

1 - 65535

uint16

0

Bands have been subdivided as follows:
Processing

All clear observations for the given time period\nare collated from the parent dataset. Cloudy pixels are identified and\nexcluded. The geomedian and MADs calculations are then performed by the hdstats package. Annual GeoMAD datasets for the period use hdstats version\n0.2.

Known Limitations

The Landsat 8 (& 9) GeoMAD has a known issue with data quality over marine regions. The GeoMAD algorithm uses pixel quality information from the input data to identify and mask pixels with poor quality obervations. Landsat 8 & 9 analysis ready satellite images over the ocean often contain negative surface reflectance values, and the GeoMAD masking procedures remove pixels where any negative values occur. Thus, in regions where pixels are persistently negative throughout the year, the GeoMAD product will contain a no-data value. An example of this can be seen in Image 7 below where a shallow marine system contains no-data values in the GeoMAD because the NIR band values in the input data are persistently negative.

More details on this dataset can be found here.

", "keyword": [ "Digital Earth Africa", "Africa", "GeoMAD", "Median Absolute Deviations", "Landsat 8", "DE Africa", "Annual GeoMAD", "Cloud-free" ], "issued": "2022-01-27T01:48:23.000Z", "modified": "2025-04-30T18:13:29.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-26.8639,-36.1644,65.6679,39.9686", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::digital-earth-africas-landsat-8-annual-geomad" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://di-deafrica.img.arcgis.com/arcgis/rest/services/deafrica/Landsat8_Geomedian_Annual/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e5f00871e63b4e28a236a3a8bcc74617", "landingPage": "https://afrigeo.africageoportal.com/datasets/africageoportal::water-observations-from-space-annual-statistics-for-africa-1", "title": "Water Observations from Space Annual Statistics for Africa", "description": "

Water\nObservations from Space (WOfS) is a service that draws on satellite imagery to\nprovide historical surface water observations of the whole African continent.\nWOfS allows users to understand the location and movement of inland and coastal\nwater present in the African landscape. It shows where water is usually\npresent; where it is seldom observed; and where inundation of the surface has\nbeen observed by satellite. 


WOfS annual summary shows the frequency of a pixel being classified as wet over an annual period (calendar year). This is calculated by looking at:


Key Properties

Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 1984 - 2022
Spatial Resolution: 30 x 30 meter
Update frequency: Annual from 1984 - 2022
Number of Bands: 3 Bands
Parent Dataset: Landsat Collection 2 Level-2 Surface Reflectance; WOfS Feature Layer
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
\n\n


Available Bands


Band ID

Description

Value range

Data type

No data value

count_wet

How many times a pixel was wet

0 - 32767

int16

-999

count_clear

How many times a pixel was clear

0 - 32767

int16

-999

frequency

Frequency of water detection at a location

0 - 1

float32

NaN

\n\n

Interpreting WOfS

The WOfS service should be interpreted with caveats in the following situations:

Note that WOfS is not intended for studying ocean. Validation has been centred around inland and near-coastal waterbodies.

\n\n

More details on this dataset can be found here.

", "keyword": [ "wofs_ls", "wofs_ls_summary_annual", "Digital Earth Africa", "Water Observation from Space", "Landsat", "DE Africa", "Surface water", "Open water" ], "issued": "2022-01-13T03:33:00.000Z", "modified": "2025-05-02T11:02:19.523Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-26.8639,-49.4462,65.6697,40.9521", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/africageoportal::water-observations-from-space-annual-statistics-for-africa-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://di-deafrica.img.arcgis.com/arcgis/rest/services/deafrica/WOFS_Annual_Frequency/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=4ca13f0e4e29403fa68c46d188c4be73", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::landsat-8-9-views", "title": "Landsat 8-9 Views", "description": "

This layer includes Landsat 8 and 9 imagery for use in visualization and analysis. This layer is time enabled and includes a number of band combinations and indices rendered on demand. The imagery includes eight multispectral bands from the Operational Land Imager (OLI) and two bands from the Thermal Infrared Sensor (TIRS).  It is updated daily with new imagery directly sourced from the USGS Landsat collection on AWS.

Geographic Coverage

Temporal Coverage

Product Level

Image Selection/Filtering

Visual Rendering

Multispectral Bands

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
\n

Band

\n 		\n

Description

\n 		\n

Wavelength\n (µm)

\n 		\n

Spatial\n Resolution (m)

\n
\n

1

\n 		\n

Coastal\n aerosol

\n 		\n

0.43 - 0.45

\n 		\n

30

\n
\n

2

\n 		\n

Blue

\n 		\n

0.45 - 0.51

\n 		\n

30

\n
\n

3

\n 		\n

Green

\n 		\n

0.53 - 0.59

\n 		\n

30

\n
\n

4

\n 		\n

Red

\n 		\n

0.64 - 0.67

\n 		\n

30

\n
\n

5

\n 		\n

Near Infrared\n (NIR)

\n 		\n

0.85 - 0.88

\n 		\n

30

\n
\n

6

\n 		\n

SWIR 1

\n 		\n

1.57 - 1.65

\n 		\n

30

\n
\n

7

\n 		\n

SWIR 2

\n 		\n

2.11 - 2.29

\n 		\n

30

\n
\n

8

\n 		\n

Cirrus (in\n OLI this is band 9)

\n 		\n

1.36 - 1.38

\n 		\n

30

\n
\n

9

\n 		\n

QA Band\n (available with Collection 1)*

\n 		\n

NA

\n 		\n

30

\n

*More about the Quality Assessment Band

TIRS Bands

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
\n

Band

\n 		\n

Description

\n 		\n

Wavelength\n (µm)

\n 		\n

Spatial\n Resolution (m)

\n
\n

10

\n 		\n

TIRS1

\n 		\n

10.60 - 11.19

\n 		\n

100 * (30)

\n
\n

11

\n 		\n

TIRS2

\n 		\n

11.50 - 12.51

\n 		\n

100 * (30)

\n

*TIRS bands are acquired at 100 meter resolution, but are resampled to 30 meter in delivered data product.

Additional Usage Notes


Data Source

Landsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted by the Amazon Web Services as part of their Public Data Sets program.

For information, see Landsat 8 and Landsat 9.

", "keyword": [ "imagery", "multispectral", "temporal", "landsat 8", "landsat", "landsat on aws", "amazon", "MS", "landsat 9" ], "issued": "2013-12-07T02:19:55.000Z", "modified": "2025-04-11T16:52:35.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-68.6273,180.0000,82.6557", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::landsat-8-9-views" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsat2.arcgis.com/arcgis/rest/services/Landsat8_Views/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8f0573e0c0b9491dbeafde9c72ccf02b&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/esri::geoglows-2-0-ecmwf-streamflow-model-10-day-forecast", "title": "GEOGLOWS 2.0 ECMWF Streamflow Model (10-Day Forecast)", "description": "The GEOGLOWS ECMWF Streamflow System provides a daily 51-member ensemble streamflow forecast for around 7 million reaches across the globe. The model uses gridded surface runoff provided by the European Centre for Medium-range Weather Forecasting (ECMWF) Integrated Forecast System (IFS) version 48R1. The runoff is mapped to vector catchment boundaries and routed using Matrix Muskingum Cunge method implemented in the RAPID software. A subset of TDX-Hydro reaches are used as the stream network and catchment boundaries. This animation layer shows the first 10-days of a 15-day forecast at 3-hr intervals. Additionally, a 80-yr historical simulation was produced based on ECMWF’s ERA5 dataset. From this historical simulation, return periods for each reach are calculated and used to color the stream segments when/where events exceed the 2, 10, 25, and 50-year return periods.

What can you do with this layer?

Revisions:
", "keyword": [ "GWM", "Forecast", "Flow", "Streamflow", "Flood", "ECMWF", "BYU", "ESRI", "River Discharge", "GEOGLOWS", "Surface Water", "Hydrology", "Hydro", "esri_environment", "environment", "water", "streams", "livefeeds3" ], "issued": "2024-06-07T16:51:27.000Z", "modified": "2025-04-11T16:50:38.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_environment", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-70.0000,180.0000,85.0000", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/esri::geoglows-2-0-ecmwf-streamflow-model-10-day-forecast" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://livefeeds3.arcgis.com/arcgis/rest/services/GEOGLOWS/GlobalWaterModel_Medium/MapServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8f0573e0c0b9491dbeafde9c72ccf02b/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8f0573e0c0b9491dbeafde9c72ccf02b/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8f0573e0c0b9491dbeafde9c72ccf02b/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8f0573e0c0b9491dbeafde9c72ccf02b/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=7bec35d76dd54ea584f98d286571eb84", "landingPage": "https://afrigeo.africageoportal.com/content/esri::european-space-agency-worldcover-2021-land-cover", "title": "European Space Agency WorldCover 2021 Land Cover", "description": "
WorldCover provides a baseline global land cover product at 10 m\n resolution for 2021 based on Sentinel-1 and 2 data. It was developed \nand validated in almost near-real time and at the same time maximizes \nthe impact and uptake for the end users. 

The \n2021 data features a new algorithm (v200) and is incompatible with the 2020 version. Therefore, no comparison can be drawn from a change in \npixel between the 2020 and 2021 versions of ESA WorldCover.

The 2021 version supersedes the earlier 2020 version. For more information about this new and improved update, please see ESA's website and webinar explaining the differences between this version and version 1.

Variable mapped: 11 land cover classes
Data Projection: WGS84 (WKID 4326)
Mosaic Projection: WGS84 (WKID 4326)
Extent: World
Cell Size: 8.33333333333333E-05 degrees (10m)
Source Type: 8 bit unsigned
Visible Scale: All scales are visible
Source: ESA (European Space Agency)
Publication Date: October 24, 2022

More Details from the WorldCover consortium: https://esa-worldcover.org/en

Classes

10. Tree Cover
This\n class includes any geographic area dominated by trees with a cover of \n10% or more. Other land cover classes (shrubs and/or herbs in the \nunderstorey, built-up, permanent water bodies, …) can be present below \nthe canopy, even with a density higher than trees. Areas planted with \ntrees for afforestation purposes and plantations (e.g. oil palm, olive \ntrees) are included in this class. This class also includes tree covered\n areas seasonally or permanently flooded with fresh water except for \nmangroves.

20. Shrubland
This\n class includes any geographic area dominated by natural shrubs having a\n cover of 10% or more. Shrubs are defined as woody perennial plants with\n persistent and woody stems and without any defined main stem being less\n than 5 m tall. Trees can be present in scattered form if their cover is\n less than 10%. Herbaceous plants can also be present at any density. \nThe shrub foliage can be either evergreen or deciduous.

30. Grassland
This\n class includes any geographic area dominated by natural herbaceous \nplants (Plants without persistent stem or shoots above ground and \nlacking definite firm structure): (grasslands, prairies, steppes, \nsavannahs, pastures) with a cover of 10% or more, irrespective of \ndifferent human and/or animal activities, such as: grazing, selective \nfire management etc. Woody plants (trees and/or shrubs) can be present \nassuming their cover is less than 10%. It may also contain uncultivated \ncropland areas (without harvest/ bare soil period) in the reference \nyear.

40. Cropland
Land covered with annual cropland that is sowed/planted and harvestable at least once within the 12 months after the
sowing/planting date. The annual cropland produces an herbaceous cover and is sometimes combined with some tree or woody
vegetation.\n Note that perennial woody crops will be classified as the appropriate \ntree cover or shrub land cover type. Greenhouses are considered as \nbuilt-up.

50. Built-up
Land\n covered by buildings, roads and other man-made structures such as \nrailroads. Buildings include both residential and industrial building. \nUrban green (parks, sport facilities) is not included in this class. \nWaste dump deposits and extraction sites are considered as bare.

60. Bare or sparse vegetation
Lands with exposed soil, sand, or rocks and never has more than 10 % vegetated cover during any time of the year.

70. Snow and Ice
This class includes any geographic area covered by snow or glaciers persistently.

80. Permanent water bodies
This\n class includes any geographic area covered for most of the year (more \nthan 9 months) by water bodies: lakes, reservoirs, and rivers. Can be \neither fresh or salt-water bodies. In some cases the water can be frozen\n for part of the year (less than 9 months).

90. Herbaceous wetland
Land\n dominated by natural herbaceous vegetation (cover of 10% or more) that \nis permanently or regularly flooded by fresh, brackish or salt water. It\n excludes unvegetated sediment (see 60), swamp forests (classified as \ntree cover) and mangroves see 95).

95. Mangroves
Taxonomically\n diverse, salt-tolerant tree and other plant species which thrive in \nintertidal zones of sheltered tropical shores,
"overwash" islands, and estuaries.

100. Moss and lichen
Land\n covered with lichens and/or mosses. Lichens are composite organisms \nformed from the symbiotic association of fungi and algae. Mosses contain\n photo-autotrophic land plants without true leaves, stems, roots but \nwith leaf-and stemlike organs.
", "keyword": [ "mangrove", "mangroves", "sentinel-2", "sentinel-1", "land cover", "landcover", "WorldCover", "ESA", "environment", "esri_environment", "hosted" ], "issued": "2024-05-09T03:28:47.000Z", "modified": "2025-04-03T17:47:19.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_environment", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-60.0000,180.0000,84.0000", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/content/esri::european-space-agency-worldcover-2021-land-cover" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiledimageservices.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/European_Space_Agency_WorldCover_2021_Land_Cover_WGS84_7/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=0dbae7dfbe4b48a098b556c7d41d60c3", "landingPage": "https://afrigeo.africageoportal.com/content/africageoportal::coastlines-service-for-africa", "title": "Coastlines Service for Africa", "description": "
The product combines satellite data from the Digital Earth Africa program with tidal modelling to map the typical location of the coastline at mean sea level each year. The product enables trends of coastal erosion and growth to be examined annually at both a local and continental scale, and for patterns of coastal change to be mapped historically and updated regularly as data continues to be acquired. This allows current rates of coastal change to be compared with that observed in previous years or decades.

The ability to map shoreline positions for each year provides valuable insights into whether changes to the coastline are the result of particular events or actions, or a process of more gradual change over time. This information can enable scientists, managers, and policy makers to assess impact from the range of drivers impacting the coastlines and potentially assist planning and forecasting for future scenarios.

Key Properties

Geographic Coverage: Continental Africa - approximately 37° North to 35° South
Temporal Coverage: 2000 to Present
Spatial Resolution: 30 x 30 meter
Update Frequency: Annual from 200 - Present; 6 months from end of previous year
Parent Dataset: Landsat Collection 2 Surface Reflectance
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

Coastlines Product Datasets

Product type

Product name

Data type

Annual coastlines

coastlines_v0.4.2_shorelines_annual

Vector - line

Rate of change statistics

coastlines_v0.4.2_rates_of_change

Vector - point

Coastal change hotspots zoom 1 (15 km)

coastlines_v0.4.2_hotspots_zoom_1

Vector - point

Coastal change hotspots zoom 2 (5 km)

coastlines_v0.4.2_hotspots_zoom_2

Vector - point

Coastal change hotspots zoom 3 (1 km)

coastlines_v0.4.2_hotspots_zoom_3

Vector - point


More details on this dataset can be found here.
", "keyword": [ "Digital Earth", "Digital Earth Africa", "Tidal modelling", "Africa", "DE Africa", "Landsat", "Time-series analysis", "Coastal change", "Coastal erosion", "Coastal monitoring", "Coastlines", "Coastline extraction" ], "issued": "2024-11-15T11:57:36.000Z", "modified": "2024-11-29T15:05:54.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "16.5761,-36.5397,21.3002,-32.5182", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/content/africageoportal::coastlines-service-for-africa" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=92598fbf6bd24ca3b41dad0e4112dbe0", "landingPage": "https://afrigeo.africageoportal.com/apps/africageoportal::coastlines-dashboard-african-coastlines-advance-and-retreat", "title": "Coastlines Dashboard: African Coastlines Advance and Retreat", "description": "

Building on the data from the Digital Earth Africa Coastlines service, which provides shorelines, rates of change, and coastal hotspots, this African Coastlines Advance and Retreat Dashboard presents a user-friendly visualization of shoreline movement trends from 2000 to 2021. The dashboard highlights significant areas of coastal advance and retreat across all African coastal countries, offering critical insights for coastal managers and policymakers in addressing the challenges of coastal erosion and change.

Further information on the Coastlines Service can be found on the Digital Earth Africa documentation page.

", "keyword": [ "Digital Earth Africa", "DE Africa", "Coastlines", "Annual_Shorelines", "Coastal change", "Coastal erosion", "Coastal monitoring" ], "issued": "2024-10-21T12:31:03.000Z", "modified": "2024-10-21T13:05:36.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/apps/africageoportal::coastlines-dashboard-african-coastlines-advance-and-retreat" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://africageoportal.maps.arcgis.com/apps/dashboards/c78e1a0f466b4cb787090ffb48e5225c" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=d0ea3d8df64d4ff0b4c94a5cf302a384", "landingPage": "https://afrigeo.africageoportal.com/apps/webapps::africa-streamflow-forecast-viewer", "title": "Africa Streamflow Forecast Viewer", "description": "", "keyword": [ "Africa", "Streamflow", "forecast", "flood" ], "issued": "2024-06-27T07:08:09.000Z", "modified": "2024-06-27T21:47:29.000Z", "publisher": { "name": "ArcGIS Instant Apps" }, "contactPoint": { "@type": "vcard:Contact", "fn": "steve_webapps", "hasEmail": "mailto:iwittenmyer@esri.com" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/apps/webapps::africa-streamflow-forecast-viewer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://webapps.maps.arcgis.com/apps/instant/streamflowviewer/index.html?appid=d0ea3d8df64d4ff0b4c94a5cf302a384" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ed5f49d93df6418592ad51dadbf5bf4b", "landingPage": "https://afrigeo.africageoportal.com/pages/africageoportal::rcmrd-map-competition-2023", "title": "RCMRD Map Competition 2023", "description": "RCMRD Map Competition 2023. The theme is Environmental and Biodiversity Conservation Efforts to Protect our Natural Resources", "keyword": [ "RCMRD", "OFESA", "BIOPAMA", "GMES", "GMES & Africa", "AUC", "Africa Union", "Regional Resource Hub", "Biodiversity", "Forestry", "Conservation", "Wildlife", "Nature", "Species", "Land", "Earth", "Space", "School", "Primary", "High School", "2023", "Map", "Competition" ], "issued": "2023-06-03T07:55:11.000Z", "modified": "2023-11-24T06:55:04.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "mkimani@rcmrd.org", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "", "license": "None", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/pages/africageoportal::rcmrd-map-competition-2023" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a5426c2281674b94ba587c5665df6ea6", "landingPage": "https://afrigeo.africageoportal.com/documents/africageoportal::6th-afrigeo-symposium", "title": "6th AfriGEO Symposium", "description": "The 6th AfriGEO symposium was privileged to take place during the 18th GEO week as a side event. It also had the privilege that the 18th GEO Week was hosted on the continent, in Accra, Ghana. The AfriGEO Secretariat had 6 sessions focused on AfriGEO’s priority topics: Climate Change, Disaster Risk Reduction, Agriculture and Food Security, Disaster Risk, Sustainable Water Resource Management, Sustainable Forest Management, Health, Sustainable Urban Development (Session 2), Land Cover/ Land Degradation Neutrality (Session 5) and Data Infrastructure (Session 6). The 6 sessions demonstrated actions that the continent is taking towards building sustainable and resilient: systems, communities, and resources using case studies that are scalable, methods that are reliable, and systems that are exemplars of working models that the continent needs to adopt while addressing gaps and what needs to be done to strengthen these gaps.", "keyword": [ "AfriGEO Symposium" ], "issued": "2023-02-08T12:38:30.000Z", "modified": "2023-02-08T12:49:24.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "SamanthaMusinzi", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/documents/africageoportal::6th-afrigeo-symposium" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://afrigeosymposium2022.rcmrd.org/#agenda" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=b68acae78a7b443093f42c87ac5e380c", "landingPage": "https://afrigeo.africageoportal.com/documents/africageoportal::afrigeo-ldn-inception-report-3-0", "title": "AfriGEO LDN Inception Report 3 0", "description": "
The land is a vital resource that provides many services to humanity and is put to many different uses, land has cultural value as well as production value, providing food and water, fuel and fiber, employment, waste purification, and many more services. However, globally it is estimated that 25% of the total land area has been degraded; every year, approximately 12 million hectares are added to the total area of degraded land. 


Land degradation, the deterioration or loss of the productive capacity of the soils for the present and future is a global challenge that affects everyone through food insecurity, higher food prices, climate change, environmental hazards, and the loss of biodiversity and ecosystem services. Land degradation is happening at an alarming pace, contributing to a dramatic decline in the productivity of croplands and rangelands worldwide. Land Degradation Neutrality (LDN) is a  concept that was developed to encourage the implementation of an optimal mix of measures designed to avoid, reduce, and/or reverse land degradation to achieve a state of no net loss of healthy and productive land. LDN aims to balance anticipated losses in land-based natural capital and associated ecosystem functions and services with measures that produce alternative gains through approaches such as land restoration and sustainable land management.

", "keyword": [ "Land Degradation Neutrality", "Land Degradation" ], "issued": "2023-02-07T05:50:44.000Z", "modified": "2023-02-08T12:27:56.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "SamanthaMusinzi", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/documents/africageoportal::afrigeo-ldn-inception-report-3-0" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=5f02e2aba151463aa35b935d14e6b86c", "landingPage": "https://afrigeo.africageoportal.com/documents/africageoportal::5th-afrigeo-symposium-2021-report", "title": "5th AfriGEO Symposium 2021 Report", "description": "

Under\nthe theme "Open Science for growing African Industries in Earth\nObservation"  the 5th AfriGEO symposium theme was strategic to\ncatalyze conversations leading to partnerships, sustainable economic growth,\nand enhancing utilization of EO data in supporting economic development in\nAfrica.

\n\n

The\n5th AfriGEO symposium 2021 therefore aimed at providing a platform to enhance\ncollaboration and integration by bringing together experts from the different\nspheres to discuss, unlock and activate the growth of African Industries in\nEO. AfriGEO invited submissions of abstracts for virtual presentation by\nAfrican institutions, partners, and researchers working on addressing regional\ndevelopment challenges in the 5th AfriGEO Symposium’s thematic\nareas of focus as listed:

\n\n
    \n
  1.      Climate Change
    2. \n
  2.      Agriculture and\n Food Security
    3. \n
  3.      Industry (SMME)\n focus
    4. \n
  4.      EO for Health
    5. \n
  5.      Disaster Risk\n Reductions
    6. \n
  6.      Data and\n Infrastructure (Cross-cutting)
    7. \n

\n\n\n\n\n\n\n\n\n\n
", "keyword": [ "AfriGEO Symposium", "Symposium", "AfriGEO" ], "issued": "2023-02-08T09:24:41.000Z", "modified": "2023-02-08T09:43:38.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "SamanthaMusinzi", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/documents/africageoportal::5th-afrigeo-symposium-2021-report" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=bb86721588ea49b6b44b10b7d5d2b0b1&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/bb86721588ea49b6b44b10b7d5d2b0b1_0", "title": "OpenStreetMap Buildings for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) buildings data for Africa, which is updated every 1 minute with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM polygon (closed way) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes building features defined as a query against the hosted feature layer (i.e. building is not blank).

In OSM, a building is a man-made structure with a roof, standing more or less permanently in one place.  These features are identified with a building tag.  There are thousands of different tag values for building used in the OSM database.  In this feature layer, unique symbols are used for several of the most popular building types, while lesser used types are grouped in an "other" category.

Zoom in to large scales (e.g. Streets level or 1:10k scale) to see the building features display.  You can click on a feature to get the name of the building (if available).  The name of the building will display by default at large scales (e.g. Street level of 1:5k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this buildings layer displaying just one or two building types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. building is apartments), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.  Esri may publish a few such layers (e.g. parks) that are ready to use, but not for every type of building.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "buildings", "Africa", "OpenStreetMap" ], "issued": "2021-05-17T19:41:41.000Z", "modified": "2026-11-11T04:34:05.378Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-26.9338,-55.4431,74.1261,53.9887", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/bb86721588ea49b6b44b10b7d5d2b0b1_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Buildings/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/bb86721588ea49b6b44b10b7d5d2b0b1/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/bb86721588ea49b6b44b10b7d5d2b0b1/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/bb86721588ea49b6b44b10b7d5d2b0b1/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/bb86721588ea49b6b44b10b7d5d2b0b1/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=f7796e1367d24b95a55e2f60c1ee30cb&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/f7796e1367d24b95a55e2f60c1ee30cb_0", "title": "OpenStreetMap Medical Facilities for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) polygon data of medical facilities for Africa, which is updated every 15 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM polygon (way) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes amenity and building features defined as a query against the hosted feature layer where amenity or building value is any of 'hospital', 'clinic', 'doctors', or 'pharmacy'.

In OSM, amenities are useful and important facilities for visitors and residents, such as hospitals and clinics.  These features are identified with an amenity tag.  In OSM, a building is a man-made structure with a roof, standing more or less permanently in one place.  These features are identified with a building tag.  There are thousands of different tag values used in the OSM database.  In this feature layer, unique symbols are used for the most common amenity and building tags used for medical facilities.

Zoom in to large scales (e.g. City level or 1:160k scale) to see the amenity features display.  You can click on a feature to get the name of the feature.  The name of the feature will display by default at very large scales (e.g. Building level of 1:2k scale).  Labels can be turned off in your map if you prefer.
", "keyword": [ "osm", "medical", "Africa", "OpenStreetMap", "hospital", "clinic", "doctor" ], "issued": "2021-05-17T19:45:24.000Z", "modified": "2026-11-11T04:34:05.378Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-26.9338,-55.4431,74.1261,53.9887", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/f7796e1367d24b95a55e2f60c1ee30cb_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Medical_Areas/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/f7796e1367d24b95a55e2f60c1ee30cb/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/f7796e1367d24b95a55e2f60c1ee30cb/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/f7796e1367d24b95a55e2f60c1ee30cb/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/f7796e1367d24b95a55e2f60c1ee30cb/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=90cf6859117c4e05ad474b55fd13553c&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/90cf6859117c4e05ad474b55fd13553c_0", "title": "OpenStreetMap Educational Establishments for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) educational establishment point data for Africa, which is updated every 15 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM point (node) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes amenity features defined as a query against the hosted feature layer where the amenity value is any of 'school', 'university', 'college', or 'kindergarten'.

In OSM, amenities are useful and important facilities for visitors and residents, such as schools and universities.  These features are identified with an amenity tag.  In OSM, amenity=school is used to identify a place where pupils, normally between the ages of about 6 and 18 are taught under the supervision of teachers. This includes primary and secondary schools. See amenity=college, amenity=university, and amenity=kindergarten for other educational establishments.

Zoom in to large scales (e.g. Cities level or 1:160k scale) to see the educational features display.  You can click on a feature to get the name and any other available attributes of the feature.  The name of the feature will display by default at very large scales (e.g. Building level of 1:2k scale).  Labels can be turned off in your map if you prefer.
", "keyword": [ "osm", "education", "Africa", "OpenStreetMap", "school", "college", "university" ], "issued": "2021-05-17T19:40:13.000Z", "modified": "2026-11-11T04:33:20.143Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-25.7372,-58.8227,73.9120,43.4042", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/90cf6859117c4e05ad474b55fd13553c_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Educational/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/90cf6859117c4e05ad474b55fd13553c/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/90cf6859117c4e05ad474b55fd13553c/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/90cf6859117c4e05ad474b55fd13553c/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/90cf6859117c4e05ad474b55fd13553c/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9fa71eb921f14973b27f2bb33b7f543d&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/9fa71eb921f14973b27f2bb33b7f543d_0", "title": "OpenStreetMap Shops for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) shops data for Africa, which is updated every 5 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM point (node) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes shop features defined as a query against the hosted feature layer (i.e. shop is not blank).

In OSM, a shop is a place selling retail products or services, such as a supermarket, bakery, or florist.  These features are identified with a shop tag.  There are thousands of different tag values for shop used in the OSM database.  In this feature layer, unique symbols are used for several of the most popular shop types, while lesser used types are grouped in an "other" category.

Zoom in to large scales (e.g. Neighborhood level or 1:80k scale) to see the shop features display.  You can click on the feature to get the name of the shop.  The name of the shop will display by default at very large scales (e.g. Building level of 1:2k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this shop layer displaying just one or two shop types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. shop is jewelry), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.  Esri may publish a few such layers (e.g. supermarket or convenience shop) that are ready to use, but not for every type of shop.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "shop", "Africa", "OpenStreetMap" ], "issued": "2021-05-17T19:34:55.000Z", "modified": "2026-11-11T04:33:20.143Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-25.7372,-58.8227,73.9120,43.4042", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/9fa71eb921f14973b27f2bb33b7f543d_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Shops/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9fa71eb921f14973b27f2bb33b7f543d/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9fa71eb921f14973b27f2bb33b7f543d/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9fa71eb921f14973b27f2bb33b7f543d/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9fa71eb921f14973b27f2bb33b7f543d/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=5f23ebcc16ab4ee79534f2d1cc686a6c&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/5f23ebcc16ab4ee79534f2d1cc686a6c_0", "title": "OpenStreetMap Medical Facilities for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) point data of medical facilities for Africa, which is updated every 15 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM point (node) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes amenity features defined as a query against the hosted feature layer where the amenity value is any of 'hospital', 'clinic', 'doctors', or 'pharmacy'.

In OSM, amenities are useful and important facilities for visitors and residents, such as hospitals and clinics.  These features are identified with an amenity tag.  There are thousands of different tag values used in the OSM database.  In this feature layer, unique symbols are used for the most common amenity tags used for medical facilities.

Zoom in to large scales (e.g. Neighborhood level or 1:20k scale) to see the amenity features display.  You can click on a feature to get the name of the amenity.  The name of the amenity will display by default at very large scales (e.g. Building level of 1:2k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this medical facilities layer displaying just one or two amenity types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. amenity is hospital), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.  Esri will publish a few such layers (e.g. Places of Worship, Schools, and Parking) that are ready to use, but not for every type of amenity.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "medical", "Africa", "OpenStreetMap", "hospital", "clinic", "doctor" ], "issued": "2021-05-17T19:37:55.000Z", "modified": "2026-11-11T04:33:20.143Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-25.7372,-58.8227,73.9120,43.4042", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/5f23ebcc16ab4ee79534f2d1cc686a6c_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Medical/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/5f23ebcc16ab4ee79534f2d1cc686a6c/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/5f23ebcc16ab4ee79534f2d1cc686a6c/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/5f23ebcc16ab4ee79534f2d1cc686a6c/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/5f23ebcc16ab4ee79534f2d1cc686a6c/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=1825495e3c1a4238a2b234d4fdc1861d&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/1825495e3c1a4238a2b234d4fdc1861d_0", "title": "OpenStreetMap Landuse Areas for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) landuse areas data for Africa, which is updated every 15 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM polygon (closed way) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes landuse features defined as a query against the hosted feature layer (i.e. landuse is not blank).

In OSM, landuse describes the primary use of land by humans.  These features are identified with a landuse tag.  There are thousands of different tag values for landuse used in the OSM database.  In this feature layer, unique symbols are used for several of the most popular landuse types, while lesser used types are grouped in an "other" category.

Zoom in to large scales (e.g. City level or 1:80k scale) to see the landuse area features display.  You can click on a feature to get the name of the landuse area (if available).  The name of the landuse area will display by default at large scales (e.g. Street level of 1:5k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this landuse areas layer displaying just one or two landuse types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. landuse is commercial), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.  Esri may publish a few such layers (e.g. residential, forest) that are ready to use, but not for every type of landuse area.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "landuse", "Africa", "OpenStreetMap" ], "issued": "2021-05-17T19:44:04.000Z", "modified": "2026-11-11T04:34:05.378Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-26.9338,-55.4431,74.1261,53.9887", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/1825495e3c1a4238a2b234d4fdc1861d_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Landuse/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/1825495e3c1a4238a2b234d4fdc1861d/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/1825495e3c1a4238a2b234d4fdc1861d/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/1825495e3c1a4238a2b234d4fdc1861d/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/1825495e3c1a4238a2b234d4fdc1861d/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6d78851a40f54041a775d7c6f4b2633e&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/6d78851a40f54041a775d7c6f4b2633e_0", "title": "OpenStreetMap Highways for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) highways data for Africa, which is updated every 5 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM line (way) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes highway features defined as a query against the hosted feature layer (i.e. highway is not blank).

In OSM, a highway describes any kind of motorway, road, street or path.  These features are identified with a highway tag.  There are hundreds of different tag values for highway used in the OSM database.  In this feature layer, unique symbols are used for several of the most popular highway types, while lesser used types are grouped in an "other" category.

Zoom in to large scales (e.g. Streets level or 1:20k scale) to see the highway features display.  You can click on a feature to get the name of the highway (if available).  The name of the highway will display by default at large scales (e.g. Street level of 1:5k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this highway layer displaying just one or two highway types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. highway is path), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.  Esri may publish a few such layers (e.g. cycleway and pedestrian) that are ready to use, but not for every type of highway.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "highways", "Africa", "OpenStreetMap", "road", "path" ], "issued": "2021-05-17T19:47:10.000Z", "modified": "2026-11-11T04:34:20.089Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-179.0000,-78.1668,179.0000,80.9902", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/6d78851a40f54041a775d7c6f4b2633e_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Highways/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6d78851a40f54041a775d7c6f4b2633e/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6d78851a40f54041a775d7c6f4b2633e/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6d78851a40f54041a775d7c6f4b2633e/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6d78851a40f54041a775d7c6f4b2633e/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=82232d0415c04e7086414dff7eb1310f&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/82232d0415c04e7086414dff7eb1310f_0", "title": "OpenStreetMap Waterways for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) waterways data for Africa, which is updated every 15 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM line (way) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes waterway features defined as a query against the hosted feature layer (i.e. waterway is not blank).

In OSM, a waterway describes rivers, streams and ditches with a flow of water from one place to another.  These features are identified with a waterway tag.  There are hundreds of different tag values for waterway used in the OSM database.  In this feature layer, unique symbols are used for several of the most popular waterway types, while lesser used types are grouped in an "other" category.

Zoom in to large scales (e.g. City level or 1:80k scale) to see the waterway features display.  You can click on a feature to get the name of the waterway (if available).  The name of the waterway will display by default at large scales (e.g. Street level of 1:5k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this waterway layer displaying just one or two waterway types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. waterway is dam), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.  Esri may publish a few such layers (e.g. streams and rivers) that are ready to use, but not for every type of waterway.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "waterways", "Africa", "OpenStreetMap", "water", "river", "stream" ], "issued": "2021-05-17T19:48:31.000Z", "modified": "2026-11-11T04:34:20.089Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-179.0000,-78.1668,179.0000,80.9902", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/82232d0415c04e7086414dff7eb1310f_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Waterways/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/82232d0415c04e7086414dff7eb1310f/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/82232d0415c04e7086414dff7eb1310f/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/82232d0415c04e7086414dff7eb1310f/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/82232d0415c04e7086414dff7eb1310f/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=f5ffdff732c34885bcac4c5a87ae78e0&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/f5ffdff732c34885bcac4c5a87ae78e0_0", "title": "OpenStreetMap Amenities for Africa", "description": "This feature layer provides access to OpenStreetMap (OSM) amenity data for Africa, which is updated every 5 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM point (node) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file.  This feature layer view includes amenity features defined as a query against the hosted feature layer (i.e. amenity is not blank).

In OSM, amenities are useful and important facilities for visitors and residents, such as places of worship, restaurants, banks, and schools.  These features are identified with an amenity tag.  There are thousands of different tag values used in the OSM database.  In this feature layer, unique symbols are used for several of the most popular amenity types, while lesser used types are grouped in an "other" category.

Zoom in to large scales (e.g. City level or 1:80k scale) to see the amenity features display.  You can click on a feature to get the name of the amenity.  The name of the amenity will display by default at very large scales (e.g. Building level of 1:2k scale).  Labels can be turned off in your map if you prefer.

Create New Layer
If you would like to create a more focused version of this amenity layer displaying just one or two amenity types, you can do that easily!  Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. amenity is fire station), rename the layer as appropriate, and save layer.  You can also change the layer symbols or popup if you like.  Esri will publish a few such layers (e.g. Schools, Medical Facilities, and Places of Worship) that are ready to use, but not for every type of amenity.

Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer.  You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
", "keyword": [ "osm", "amenity", "Africa", "OpenStreetMap" ], "issued": "2021-05-17T19:33:13.000Z", "modified": "2026-11-11T04:33:20.143Z", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "smoore2_osm", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-25.7372,-58.8227,73.9120,43.4042", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/f5ffdff732c34885bcac4c5a87ae78e0_0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services-eu1.arcgis.com/zci5bUiJ8olAal7N/arcgis/rest/services/OSM_AF_Amenities/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/f5ffdff732c34885bcac4c5a87ae78e0/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/f5ffdff732c34885bcac4c5a87ae78e0/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/f5ffdff732c34885bcac4c5a87ae78e0/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/f5ffdff732c34885bcac4c5a87ae78e0/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ba42ac44def64a69aa1eb326ad0e740f", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-south-africa-social-distancing-layers-version-1-0", "title": "GRID3 South Africa Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in South Africa. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "South Africa", "ZAF", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T15:02:51.000Z", "modified": "2022-02-01T10:46:43.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "18.3072,-34.2093,31.9961,-23.7549", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-south-africa-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/ZAF_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ba42ac44def64a69aa1eb326ad0e740f&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-south-africa-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 South Africa Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in South Africa. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "South Africa", "ZAF", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T15:02:51.000Z", "modified": "2021-07-20T15:08:40.077Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "18.4958,-34.1760,31.9109,-23.8698", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-south-africa-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/ZAF_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/ba42ac44def64a69aa1eb326ad0e740f/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/ba42ac44def64a69aa1eb326ad0e740f/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/ba42ac44def64a69aa1eb326ad0e740f/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/ba42ac44def64a69aa1eb326ad0e740f/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ba42ac44def64a69aa1eb326ad0e740f&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-south-africa-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 South Africa Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in South Africa. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in South Africa. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "South Africa", "ZAF", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T15:02:51.000Z", "modified": "2022-02-01T10:46:42.682Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "18.3072,-34.2093,31.9961,-23.7549", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-south-africa-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/ZAF_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/ba42ac44def64a69aa1eb326ad0e740f/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/ba42ac44def64a69aa1eb326ad0e740f/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/ba42ac44def64a69aa1eb326ad0e740f/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/ba42ac44def64a69aa1eb326ad0e740f/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=25b3e351f89a474095beda89d6c641c7", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-sub-saharan-africa-social-distancing-layers-version-1-0", "title": "GRID3 Sub-Saharan Africa Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas across Sub-Saharan Africa. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Sub-Saharan Africa", "SSA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-08-24T09:36:42.000Z", "modified": "2021-08-24T10:13:22.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-25.0252,-34.2093,57.6438,26.1684", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-sub-saharan-africa-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SSA50_SocialDistancing_v1_0_SLEv1_1/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=25b3e351f89a474095beda89d6c641c7&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-sub-saharan-africa-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Sub-Saharan Africa Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas across Sub-Saharan Africa. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Sub-Saharan Africa", "SSA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-08-24T09:36:42.000Z", "modified": "2021-08-24T10:06:48.252Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-24.9846,-34.1760,57.4878,26.1277", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-sub-saharan-africa-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SSA50_SocialDistancing_v1_0_SLEv1_1/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/25b3e351f89a474095beda89d6c641c7/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/25b3e351f89a474095beda89d6c641c7/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/25b3e351f89a474095beda89d6c641c7/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/25b3e351f89a474095beda89d6c641c7/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=25b3e351f89a474095beda89d6c641c7&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-sub-saharan-africa-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Sub-Saharan Africa Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas across Sub-Saharan Africa. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Sub-Saharan Africa", "SSA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-08-24T09:36:42.000Z", "modified": "2021-11-23T13:47:22.888Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-25.0252,-34.2093,57.6438,26.1684", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-sub-saharan-africa-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SSA50_SocialDistancing_v1_0_SLEv1_1/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/25b3e351f89a474095beda89d6c641c7/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/25b3e351f89a474095beda89d6c641c7/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/25b3e351f89a474095beda89d6c641c7/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/25b3e351f89a474095beda89d6c641c7/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=58ca8cb3343a4a7b835d91934a996d7a", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-namibia-social-distancing-layers-version-1-0", "title": "GRID3 Namibia Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Namibia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Namibia", "NAM", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T09:33:46.000Z", "modified": "2021-07-21T09:40:45.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "14.4505,-23.0068,17.1574,-22.4522", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-namibia-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/NAM_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=25b3e351f89a474095beda89d6c641c7&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-sub-saharan-africa-social-distancing-layers-index-version-1-0", "title": "GRID3 Sub-Saharan Africa Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas across Sub-Saharan Africa. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Sierra Leone. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Sierra Leone", "SLE", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-08-17T15:21:32.000Z", "modified": "2021-08-24T09:33:48.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-13.2985,7.8030,-10.8036,8.9536", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-sierra-leone-social-distancing-layers-version-1-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SLE_SocialDistancing_v1_1abc/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=b9afec6bcfba442b9ed557b6c27e163b&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-sierra-leone-social-distancing-layers-urban-points-version-1-1", "title": "GRID3 Sierra Leone Social Distancing Layers (Urban Points), Version 1.1", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Sierra Leone. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Sierra Leone", "SLE", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-08-17T15:21:32.000Z", "modified": "2021-08-17T15:48:31.798Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-13.2000,7.8743,-10.8432,8.8865", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-sierra-leone-social-distancing-layers-urban-points-version-1-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SLE_SocialDistancing_v1_1abc/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=b9afec6bcfba442b9ed557b6c27e163b&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::-grid3-sierra-leone-social-distancing-layers-urban-extents-version-1-1", "title": " GRID3 Sierra Leone Social Distancing Layers (Urban Extents), Version 1.1", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Sierra Leone. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Sierra Leone", "SLE", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-08-17T15:21:32.000Z", "modified": "2021-08-17T15:49:20.507Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-13.2985,7.8030,-10.8036,8.9536", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::-grid3-sierra-leone-social-distancing-layers-urban-extents-version-1-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SLE_SocialDistancing_v1_1abc/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=b9afec6bcfba442b9ed557b6c27e163b&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::-grid3-sierra-leone-social-distancing-layers-index-version-1-1", "title": " GRID3 Sierra Leone Social Distancing Layers (Index), Version 1.1", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Sierra Leone. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Sierra Leone", "SLE", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-08-17T15:21:32.000Z", "modified": "2021-08-17T15:50:01.639Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-13.2985,7.8030,-10.8036,8.9536", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::-grid3-sierra-leone-social-distancing-layers-index-version-1-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SLE_SocialDistancing_v1_1abc/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/b9afec6bcfba442b9ed557b6c27e163b/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ab927e6b62fe41898a20502c80d0d7f3", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-uganda-social-distancing-layers-version-1-0", "title": "GRID3 Uganda Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Uganda. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Uganda", "UGA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T14:43:24.000Z", "modified": "2021-07-21T10:04:24.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "30.0262,-0.6742,34.2247,3.5954", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-uganda-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/UGA_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ab927e6b62fe41898a20502c80d0d7f3&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-uganda-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Uganda Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Uganda. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Uganda. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Uganda. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Tanzania. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Tanzania", "TZA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T14:36:04.000Z", "modified": "2021-07-21T10:03:25.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "29.5947,-10.7267,40.2393,-1.2210", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::-grid3-tanzania-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/TZA_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9d2b92cb688842ebbe291555d8466d87&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-tanzania-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Tanzania Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Tanzania. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Tanzania", "TZA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T14:36:04.000Z", "modified": "2021-07-20T14:38:52.240Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "29.6474,-10.6674,40.1784,-1.2658", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-tanzania-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/TZA_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9d2b92cb688842ebbe291555d8466d87&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-tanzania-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Tanzania Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Tanzania. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Tanzania", "TZA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T14:36:04.000Z", "modified": "2021-07-20T14:38:52.170Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "29.5947,-10.7267,40.2393,-1.2210", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-tanzania-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/TZA_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9d2b92cb688842ebbe291555d8466d87&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-tanzania-social-distancing-layers-index-version-1-0", "title": "GRID3 Tanzania Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Tanzania. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Tanzania", "TZA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T14:36:04.000Z", "modified": "2021-07-21T10:03:23.604Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "29.5947,-10.7267,40.2393,-1.2210", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-tanzania-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/TZA_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9d2b92cb688842ebbe291555d8466d87/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=64052dc39f394800bd9f5e2b9706d735", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::-grid3-somalia-social-distancing-layers-version-1-0", "title": " GRID3 Somalia Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Somalia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Somalia", "SOM", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T13:03:12.000Z", "modified": "2021-07-21T09:56:39.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "41.8316,-0.3923,49.2295,11.2987", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::-grid3-somalia-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SOM_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=64052dc39f394800bd9f5e2b9706d735&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-somalia-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Somalia Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Somalia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Somalia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Somalia", "SOM", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T13:03:12.000Z", "modified": "2021-07-20T13:11:11.119Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "41.8316,-0.3923,49.2295,11.2987", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-somalia-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SOM_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/64052dc39f394800bd9f5e2b9706d735/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/64052dc39f394800bd9f5e2b9706d735/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/64052dc39f394800bd9f5e2b9706d735/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/64052dc39f394800bd9f5e2b9706d735/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=64052dc39f394800bd9f5e2b9706d735&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-somalia-social-distancing-layers-index-version-1-0", "title": "GRID3 Somalia Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Somalia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Somalia", "SOM", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T13:03:12.000Z", "modified": "2021-07-21T09:56:37.988Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "41.8316,-0.3923,49.2295,11.2987", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-somalia-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SOM_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/64052dc39f394800bd9f5e2b9706d735/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/64052dc39f394800bd9f5e2b9706d735/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/64052dc39f394800bd9f5e2b9706d735/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/64052dc39f394800bd9f5e2b9706d735/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=afb63a401a234c9db373280097fb6159", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-senegal-social-distancing-layers-version-1-0", "title": "GRID3 Senegal Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Senegal. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Senegal", "SEN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T12:44:01.000Z", "modified": "2021-07-21T09:54:22.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-17.5444,12.5067,-12.1357,16.6916", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-senegal-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SEN_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=afb63a401a234c9db373280097fb6159&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-senegal-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Senegal Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Senegal. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Senegal", "SEN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T12:44:01.000Z", "modified": "2021-07-20T12:45:47.100Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-17.3795,12.5552,-12.1852,16.6536", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-senegal-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SEN_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/afb63a401a234c9db373280097fb6159/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/afb63a401a234c9db373280097fb6159/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/afb63a401a234c9db373280097fb6159/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/afb63a401a234c9db373280097fb6159/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=afb63a401a234c9db373280097fb6159&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-senegal-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Senegal Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Senegal. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Senegal", "SEN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T12:44:01.000Z", "modified": "2021-07-20T12:45:47.244Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-17.5444,12.5067,-12.1357,16.6916", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-senegal-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/SEN_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/afb63a401a234c9db373280097fb6159/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/afb63a401a234c9db373280097fb6159/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/afb63a401a234c9db373280097fb6159/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/afb63a401a234c9db373280097fb6159/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=58ca8cb3343a4a7b835d91934a996d7a&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-namibia-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Namibia Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Namibia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Senegal. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Rwanda. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Rwanda", "RWA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T11:10:06.000Z", "modified": "2021-07-21T09:51:59.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "28.8568,-2.7596,30.2807,-1.4530", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-rwanda-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/RWA_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=492a58f37f54480ba2529fb8e17fe02a&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-rwanda-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Rwanda Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Rwanda. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Rwanda", "RWA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T11:10:06.000Z", "modified": "2021-07-20T11:10:40.225Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "29.3451,-2.6352,30.2312,-1.4991", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-rwanda-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/RWA_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=492a58f37f54480ba2529fb8e17fe02a&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-rwanda-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Rwanda Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Rwanda. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Rwanda", "RWA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T11:10:06.000Z", "modified": "2021-07-20T11:10:51.369Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "28.8568,-2.7596,30.2807,-1.4530", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-rwanda-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/RWA_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=492a58f37f54480ba2529fb8e17fe02a&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-rwanda-social-distancing-layers-index-version-1-0", "title": "GRID3 Rwanda Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Rwanda. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Rwanda", "RWA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T11:10:06.000Z", "modified": "2021-07-21T09:51:58.021Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "28.8568,-2.7596,30.2807,-1.4530", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-rwanda-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/RWA_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/492a58f37f54480ba2529fb8e17fe02a/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=06c201213f3c4811a51751f4de5c171e", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-nigeria-social-distancing-layers-version-1-0", "title": "GRID3 Nigeria Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Nigeria. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Nigeria. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Nigeria. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Nigeria", "NGA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T10:24:29.000Z", "modified": "2021-07-20T10:30:57.852Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "2.7063,4.2783,14.2607,13.7939", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-nigeria-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/NGA_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/06c201213f3c4811a51751f4de5c171e/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/06c201213f3c4811a51751f4de5c171e/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/06c201213f3c4811a51751f4de5c171e/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/06c201213f3c4811a51751f4de5c171e/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=06c201213f3c4811a51751f4de5c171e&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-nigeria-social-distancing-layers-index-version-1-0", "title": "GRID3 Nigeria Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Nigeria. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Nigeria", "NGA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T10:24:29.000Z", "modified": "2021-07-21T09:42:31.510Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "2.7063,4.2783,14.2607,13.7939", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-nigeria-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/NGA_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/06c201213f3c4811a51751f4de5c171e/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/06c201213f3c4811a51751f4de5c171e/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/06c201213f3c4811a51751f4de5c171e/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/06c201213f3c4811a51751f4de5c171e/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8b2d3af8394f4b239b09a46aca3e67a5", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-niger-social-distancing-layers-version-1-0", "title": "GRID3 Niger Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Niger. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Niger", "NER", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T10:08:30.000Z", "modified": "2021-07-21T09:41:28.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "0.7041,11.8540,13.1505,17.0179", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-niger-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/NER_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8b2d3af8394f4b239b09a46aca3e67a5&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-niger-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Niger Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Niger. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Niger", "NER", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T10:08:30.000Z", "modified": "2021-07-20T10:11:18.805Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "0.7522,11.8859,13.1087,16.9697", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-niger-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/NER_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2d3af8394f4b239b09a46aca3e67a5/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2d3af8394f4b239b09a46aca3e67a5/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2d3af8394f4b239b09a46aca3e67a5/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2d3af8394f4b239b09a46aca3e67a5/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8b2d3af8394f4b239b09a46aca3e67a5&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-niger-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Niger Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Niger. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Niger. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Namibia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Namibia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Namibia", "NAM", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T09:33:46.000Z", "modified": "2021-07-21T09:40:44.542Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "14.4505,-23.0068,17.1574,-22.4522", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-namibia-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/NAM_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/58ca8cb3343a4a7b835d91934a996d7a/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/58ca8cb3343a4a7b835d91934a996d7a/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/58ca8cb3343a4a7b835d91934a996d7a/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/58ca8cb3343a4a7b835d91934a996d7a/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=81424461c72442568db3dccdee8bb206", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-mauritius-social-distancing-layers-version-1-0", "title": "GRID3 Mauritius Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Mauritius. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Mauritius", "MUS", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T09:15:39.000Z", "modified": "2021-07-21T09:31:30.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "57.3761,-20.3785,57.6438,-20.0012", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-mauritius-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MUS_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=81424461c72442568db3dccdee8bb206&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mauritius-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Mauritius Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Mauritius. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Mauritius", "MUS", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T09:15:39.000Z", "modified": "2021-07-20T09:16:48.064Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "57.4878,-20.2891,57.4878,-20.2891", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mauritius-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MUS_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=81424461c72442568db3dccdee8bb206&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mauritius-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Mauritius Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Mauritius. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Mauritius", "MUS", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T09:15:39.000Z", "modified": "2021-07-20T09:17:52.079Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "57.3761,-20.3785,57.6438,-20.0012", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mauritius-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MUS_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=81424461c72442568db3dccdee8bb206&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mauritius-social-distancing-layers-index-version-1-0", "title": "GRID3 Mauritius Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Mauritius. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Mauritius", "MUS", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T09:15:39.000Z", "modified": "2021-07-21T09:31:28.787Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "57.3761,-20.3785,57.6438,-20.0012", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mauritius-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MUS_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/81424461c72442568db3dccdee8bb206/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e1c5485c2d29491d80a9c73f8d1fd85c", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-mali-social-distancing-layers-version-1-0", "title": "GRID3 Mali Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Mali. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Mali", "MLI", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T08:29:40.000Z", "modified": "2021-07-21T09:28:10.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-11.5294,11.2508,0.0076,16.8205", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-mali-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MLI_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e1c5485c2d29491d80a9c73f8d1fd85c&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mali-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Mali Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Mali. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Mali", "MLI", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T08:29:40.000Z", "modified": "2021-07-20T08:40:27.121Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-11.4417,11.3148,-0.0436,16.7720", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mali-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MLI_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e1c5485c2d29491d80a9c73f8d1fd85c&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mali-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Mali Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Mali. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Mali", "MLI", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T08:29:40.000Z", "modified": "2021-07-20T08:40:27.763Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-11.5294,11.2508,0.0076,16.8205", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mali-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MLI_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e1c5485c2d29491d80a9c73f8d1fd85c&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mali-social-distancing-layers-index-version-1-0", "title": "GRID3 Mali Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Mali. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Mali", "MLI", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-20T08:29:40.000Z", "modified": "2021-07-21T09:27:56.628Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-11.5294,11.2508,0.0076,16.8205", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-mali-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MLI_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/e1c5485c2d29491d80a9c73f8d1fd85c/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=05e936f25cdd4a5db6c312ce0b5eac80", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-madagascar-social-distancing-layers-version-1-0", "title": "GRID3 Madagascar Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Madagascar. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Madagascar", "MDG", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T15:50:40.000Z", "modified": "2021-07-21T09:26:50.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "43.6223,-23.4024,49.7860,-13.3562", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-madagascar-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MDG_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=05e936f25cdd4a5db6c312ce0b5eac80&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-madagascar-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Madagascar Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Madagascar. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Madagascar. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Madagascar. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Madagascar", "MDG", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T15:50:40.000Z", "modified": "2021-07-21T09:26:49.144Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "43.6223,-23.4024,49.7860,-13.3562", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-madagascar-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/MDG_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/05e936f25cdd4a5db6c312ce0b5eac80/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/05e936f25cdd4a5db6c312ce0b5eac80/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/05e936f25cdd4a5db6c312ce0b5eac80/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/05e936f25cdd4a5db6c312ce0b5eac80/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=33ea771867fc4059a7a09b01643aad36", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::-grid3-kenya-social-distancing-layers-version-1-0", "title": " GRID3 Kenya Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Kenya. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Kenya", "KEN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T15:05:15.000Z", "modified": "2021-07-21T09:23:46.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "34.0882,-4.3788,41.8875,3.9587", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::-grid3-kenya-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/KEN_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=33ea771867fc4059a7a09b01643aad36&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-kenya-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Kenya Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Kenya. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Kenya", "KEN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T15:05:15.000Z", "modified": "2021-07-19T15:09:22.356Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "34.0991,-4.2862,41.8519,3.9243", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-kenya-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/KEN_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=33ea771867fc4059a7a09b01643aad36&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-kenya-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Kenya Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Kenya. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Kenya", "KEN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T15:05:15.000Z", "modified": "2021-07-19T15:09:22.607Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "34.0882,-4.3788,41.8875,3.9587", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-kenya-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/KEN_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=33ea771867fc4059a7a09b01643aad36&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-kenya-social-distancing-layers-index-version-1-0", "title": "GRID3 Kenya Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Kenya. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Kenya", "KEN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T15:05:15.000Z", "modified": "2021-07-21T09:23:44.618Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "34.0882,-4.3788,41.8875,3.9587", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-kenya-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/KEN_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/33ea771867fc4059a7a09b01643aad36/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=53d4eeb93d224edd889b4271193fce25", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-gambia-social-distancing-layers-version-1-0", "title": "GRID3 Gambia Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Gambia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Gambia", "GMB", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T14:35:24.000Z", "modified": "2021-07-21T09:11:56.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-16.7997,13.2091,-15.5579,13.5869", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-gambia-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/GMB_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=53d4eeb93d224edd889b4271193fce25&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-gambia-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Gambia Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Gambia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Gambia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Gambia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Gambia", "GMB", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T14:35:24.000Z", "modified": "2021-07-21T09:11:54.918Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-16.7997,13.2091,-15.5579,13.5869", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-gambia-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/GMB_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/53d4eeb93d224edd889b4271193fce25/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/53d4eeb93d224edd889b4271193fce25/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/53d4eeb93d224edd889b4271193fce25/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/53d4eeb93d224edd889b4271193fce25/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=693123b9cd5b4f19b2dcdc54c09029a8", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::-grid3-guinea-social-distancing-layers-version-1-0", "title": " GRID3 Guinea Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Guinea. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Guinea", "GIN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T14:13:25.000Z", "modified": "2021-07-21T09:09:38.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-14.6464,7.2177,-8.2255,11.4762", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::-grid3-guinea-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/GIN_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=693123b9cd5b4f19b2dcdc54c09029a8&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-guinea-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Guinea Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Guinea. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Guinea", "GIN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T14:13:25.000Z", "modified": "2021-07-19T14:16:31.133Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-14.5787,7.7554,-8.2700,11.4226", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-guinea-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/GIN_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/693123b9cd5b4f19b2dcdc54c09029a8/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/693123b9cd5b4f19b2dcdc54c09029a8/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/693123b9cd5b4f19b2dcdc54c09029a8/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/693123b9cd5b4f19b2dcdc54c09029a8/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=693123b9cd5b4f19b2dcdc54c09029a8&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-guinea-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Guinea Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Guinea. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Guinea. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Guinea", "GIN", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T14:13:25.000Z", "modified": "2021-07-21T09:09:29.766Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-14.6464,7.2177,-8.2255,11.4762", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-guinea-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/GIN_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/693123b9cd5b4f19b2dcdc54c09029a8/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/693123b9cd5b4f19b2dcdc54c09029a8/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/693123b9cd5b4f19b2dcdc54c09029a8/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/693123b9cd5b4f19b2dcdc54c09029a8/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8b2b678bab5e49faa77fd00b2c2c7700", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::-grid3-ghana-social-distancing-layers-version-1-0", "title": " GRID3 Ghana Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Ghana. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Ghana. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Ghana", "GHA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T14:05:01.000Z", "modified": "2021-07-19T14:09:53.502Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-2.8776,4.9335,0.8037,11.0593", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-ghana-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/GHA_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8b2b678bab5e49faa77fd00b2c2c7700&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-ghana-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Ghana Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Ghana. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Ghana", "GHA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T14:05:01.000Z", "modified": "2021-07-19T14:09:53.773Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-2.9453,4.8543,1.1918,11.1013", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-ghana-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/GHA_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8b2b678bab5e49faa77fd00b2c2c7700&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::-grid3-ghana-social-distancing-layers-index-version-1-0", "title": " GRID3 Ghana Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Ghana. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Ghana", "GHA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T14:05:01.000Z", "modified": "2021-07-21T09:08:12.996Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-2.9453,4.8543,1.1918,11.1013", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::-grid3-ghana-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/GHA_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8b2b678bab5e49faa77fd00b2c2c7700/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=672a9cbb360b4c809b684768ffb5645d", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-ethiopia-social-distancing-layers-version-1-0", "title": "GRID3 Ethiopia Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Ethiopia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Ethiopia", "ETH", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T13:48:13.000Z", "modified": "2021-07-21T09:06:05.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "34.4896,3.5187,44.3186,14.3347", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-ethiopia-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/ETH_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=672a9cbb360b4c809b684768ffb5645d&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-ethiopia-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Ethiopia Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Ethiopia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Ethiopia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Ethiopia. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Republic of Congo. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Republic of Congo", "COG", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:37:50.000Z", "modified": "2021-07-21T08:59:20.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "11.8155,-4.8982,18.5521,3.1091", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-republic-of-congo-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/COG_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=c7245feeb149490787409870457dd1ba&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-republic-of-congo-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Republic of Congo Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Republic of Congo. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Republic of Congo", "COG", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:37:50.000Z", "modified": "2021-07-19T11:45:49.153Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "11.8714,-4.7977,18.5163,3.0617", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-republic-of-congo-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/COG_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=c7245feeb149490787409870457dd1ba&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-republic-of-congo-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Republic of Congo Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Republic of Congo. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Republic of Congo", "COG", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:37:50.000Z", "modified": "2021-07-19T11:45:49.156Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "11.8155,-4.8982,18.5521,3.1091", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-republic-of-congo-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/COG_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=c7245feeb149490787409870457dd1ba&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-republic-of-congo-social-distancing-layers-index-version-1-0", "title": "GRID3 Republic of Congo Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Republic of Congo. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Republic of Congo", "COG", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:37:50.000Z", "modified": "2021-07-21T08:59:19.231Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "11.8155,-4.8982,18.5521,3.1091", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-republic-of-congo-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/COG_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/c7245feeb149490787409870457dd1ba/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9bde14f7138e41eeb33411bda9789cf4", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-cameroon-social-distancing-layers-version-1-0", "title": "GRID3 Cameroon Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Cameroon. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Cameroon", "CMR", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:17:04.000Z", "modified": "2021-07-21T08:54:42.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "9.0684,2.8687,15.3906,12.4140", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-cameroon-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CMR_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9bde14f7138e41eeb33411bda9789cf4&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-cameroon-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Cameroon Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Cameroon. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Cameroon. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Cameroon", "CMR", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:17:04.000Z", "modified": "2021-07-19T11:21:39.740Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "9.0684,2.8687,15.3906,12.4140", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-cameroon-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CMR_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9bde14f7138e41eeb33411bda9789cf4/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9bde14f7138e41eeb33411bda9789cf4/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9bde14f7138e41eeb33411bda9789cf4/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9bde14f7138e41eeb33411bda9789cf4/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9bde14f7138e41eeb33411bda9789cf4&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-cameroon-social-distancing-layers-index-version-1-0", "title": "GRID3 Cameroon Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small spatial units within urban areas in Cameroon. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Cameroon", "CMR", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:17:04.000Z", "modified": "2021-07-21T08:54:19.594Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "9.0684,2.8687,15.3906,12.4140", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-cameroon-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CMR_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9bde14f7138e41eeb33411bda9789cf4/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9bde14f7138e41eeb33411bda9789cf4/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9bde14f7138e41eeb33411bda9789cf4/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/9bde14f7138e41eeb33411bda9789cf4/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8146cc3b7f8d43daaa6fbf817af89c90", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-côte-divoire-social-distancing-layers-version-1-0", "title": "GRID3 Côte d'Ivoire Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small\nspatial units within urban areas in Côte d'Ivoire. Measures of population\ndensity were calculated from high-resolution gridded population datasets from\nWorldPop, and the space available around buildings was calculated using\nbuilding footprint polygons derived from satellite imagery (Ecopia.AI and Maxar\nTechnologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Côte d'Ivoire", "CIV", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:07:48.000Z", "modified": "2021-07-21T08:53:09.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-8.1996,4.7089,-2.7534,10.5232", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-côte-divoire-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CIV_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8146cc3b7f8d43daaa6fbf817af89c90&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-côte-divoire-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Côte d'Ivoire Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small\nspatial units within urban areas in Côte d'Ivoire. Measures of population\ndensity were calculated from high-resolution gridded population datasets from\nWorldPop, and the space available around buildings was calculated using\nbuilding footprint polygons derived from satellite imagery (Ecopia.AI and Maxar\nTechnologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Côte d'Ivoire", "CIV", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:07:48.000Z", "modified": "2021-07-19T11:10:51.047Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-8.1509,4.7591,-2.8029,10.4828", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-côte-divoire-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CIV_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8146cc3b7f8d43daaa6fbf817af89c90&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-côte-divoire-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Côte d'Ivoire Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small\nspatial units within urban areas in Côte d'Ivoire. Measures of population\ndensity were calculated from high-resolution gridded population datasets from\nWorldPop, and the space available around buildings was calculated using\nbuilding footprint polygons derived from satellite imagery (Ecopia.AI and Maxar\nTechnologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Côte d'Ivoire", "CIV", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:07:48.000Z", "modified": "2021-07-19T11:10:51.173Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-8.1996,4.7089,-2.7534,10.5232", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-côte-divoire-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CIV_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8146cc3b7f8d43daaa6fbf817af89c90&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-côte-divoire-social-distancing-layers-index-version-1-0", "title": "GRID3 Côte d'Ivoire Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 

This dataset provides index values for small\nspatial units within urban areas in Côte d'Ivoire. Measures of population\ndensity were calculated from high-resolution gridded population datasets from\nWorldPop, and the space available around buildings was calculated using\nbuilding footprint polygons derived from satellite imagery (Ecopia.AI and Maxar\nTechnologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Côte d'Ivoire", "CIV", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T11:07:48.000Z", "modified": "2021-07-21T08:53:07.748Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-8.1996,4.7089,-2.7534,10.5232", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-côte-divoire-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CIV_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8146cc3b7f8d43daaa6fbf817af89c90/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6f6a890e2adb4279bf7afa83a47d57ee", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-central-african-republic-social-distancing-layers-version-1-0", "title": "GRID3 Central African Republic Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 
This dataset provides index values for small spatial units within urban areas in Central African Republic. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Central African Republic", "CAF", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T10:53:45.000Z", "modified": "2021-07-21T08:46:59.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "14.5082,4.1191,22.4685,6.5836", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-central-african-republic-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CAF_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6f6a890e2adb4279bf7afa83a47d57ee&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-central-african-republic-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Central African Republic Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 
This dataset provides index values for small spatial units within urban areas in Central African Republic. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Central African Republic", "CAF", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T10:53:45.000Z", "modified": "2021-07-19T10:58:38.275Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "15.5943,4.3739,21.9902,6.5398", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-central-african-republic-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CAF_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6f6a890e2adb4279bf7afa83a47d57ee&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-central-african-republic-social-distancing-layers-urban-extents-version-1-0", "title": "GRID3 Central African Republic Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 
This dataset provides index values for small spatial units within urban areas in Central African Republic. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Central African Republic", "CAF", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T10:53:45.000Z", "modified": "2021-07-19T10:58:38.476Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "14.5082,4.1191,22.4685,6.5836", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-central-african-republic-social-distancing-layers-urban-extents-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CAF_SocialDistancing_v1_0/FeatureServer/1" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/csv?layers=1" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/shapefile?layers=1" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/geojson?layers=1" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/kml?layers=1" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6f6a890e2adb4279bf7afa83a47d57ee&sublayer=2", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-central-african-republic-social-distancing-layers-index-version-1-0", "title": "GRID3 Central African Republic Social Distancing Layers (Index), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 
This dataset provides index values for small spatial units within urban areas in Central African Republic. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Central African Republic", "CAF", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T10:53:45.000Z", "modified": "2021-07-21T08:46:52.401Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "14.5082,4.1191,22.4685,6.5836", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-central-african-republic-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/CAF_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/6f6a890e2adb4279bf7afa83a47d57ee/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8d8eaef8354f43178de59d1b3a277aa7", "landingPage": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-burkina-faso-social-distancing-layers-version-1-0", "title": "GRID3 Burkina Faso Social Distancing Layers, Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 
This dataset provides index values for small spatial units within urban areas in Burkina Faso. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Burkina Faso", "BFA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T10:35:43.000Z", "modified": "2021-07-21T08:45:02.000Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-4.9655,10.2329,0.7643,14.1383", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/maps/WorldPop::grid3-burkina-faso-social-distancing-layers-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/BFA_SocialDistancing_v1_0/FeatureServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8d8eaef8354f43178de59d1b3a277aa7&sublayer=0", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-burkina-faso-social-distancing-layers-urban-points-version-1-0", "title": "GRID3 Burkina Faso Social Distancing Layers (Urban Points), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 
This dataset provides index values for small spatial units within urban areas in Burkina Faso. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Burkina Faso", "BFA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T10:35:43.000Z", "modified": "2021-08-19T16:14:18.713Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-4.9170,10.2779,0.7238,14.0989", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-burkina-faso-social-distancing-layers-urban-points-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/BFA_SocialDistancing_v1_0/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8d8eaef8354f43178de59d1b3a277aa7/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8d8eaef8354f43178de59d1b3a277aa7/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8d8eaef8354f43178de59d1b3a277aa7/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8d8eaef8354f43178de59d1b3a277aa7/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8d8eaef8354f43178de59d1b3a277aa7&sublayer=1", "landingPage": "https://afrigeo.africageoportal.com/datasets/WorldPop::-grid3-burkina-faso-social-distancing-layers-urban-extents-version-1-0", "title": " GRID3 Burkina Faso Social Distancing Layers (Urban Extents), Version 1.0", "description": "
Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 
This dataset provides index values for small spatial units within urban areas in Burkina Faso. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
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Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. 

To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. 
This dataset provides index values for small spatial units within urban areas in Burkina Faso. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). 

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.
", "keyword": [ "GRID3", "Burkina Faso", "BFA", "Social Distancing", "Index", "Urban Extents" ], "issued": "2021-07-19T10:35:43.000Z", "modified": "2021-07-21T08:45:00.784Z", "publisher": { "name": "WorldPop" }, "contactPoint": { "@type": "vcard:Contact", "fn": "WorldPop_Soton", "hasEmail": "mailto:noreply@worldpop.org" }, "accessLevel": "public", "spatial": "-4.9655,10.2329,0.7643,14.1383", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://afrigeo.africageoportal.com/datasets/WorldPop::grid3-burkina-faso-social-distancing-layers-index-version-1-0" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/kOvusPqAUjVWKF9D/arcgis/rest/services/BFA_SocialDistancing_v1_0/FeatureServer/2" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8d8eaef8354f43178de59d1b3a277aa7/csv?layers=2" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8d8eaef8354f43178de59d1b3a277aa7/shapefile?layers=2" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8d8eaef8354f43178de59d1b3a277aa7/geojson?layers=2" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://afrigeo.africageoportal.com/api/download/v1/items/8d8eaef8354f43178de59d1b3a277aa7/kml?layers=2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=84ba9c03786e462d960e3172bc1b2204", "landingPage": "https://afrigeo.africageoportal.com/apps/EsriOceans::coral-bleaching-locations", "title": "Coral Bleaching Locations", "description": "
Coral reefs are one of the most diverse and ecologically important areas of the world. However, many reefs, are threatened by ocean temperatures that are increasingly becoming warmer than the coral animals' natural tolerance. According to NOAA, when water is too warm, corals will expel the algae (zooxanthellae) living in their tissues causing the coral to turn completely white. This is called coral bleaching. When a coral bleaches, it is not dead. Corals can survive a bleaching event, but they are under more stress and are subject to mortality.

The NOAA Coral Reef Watch program uses satellite data to provide current reef environmental conditions to quickly identify areas at risk for coral bleaching. The station data displayed in this map are derived from satellite based measurements of ocean temperature. These "virtual stations" are not actual buoys or in situ stations transmitting data, rather a spatial analyses for reef locations around the world are derived from 5-km resolution raster data. 

Each station has several variables: 
Alert Level: an index of the likelihood of coral bleaching, scaled from 0 (no heat stress) to 4 (coral mortality likely) based on the attributes below

Sea surface temperature: average nighttime temperature of the ocean surface derived from satellite measurements

Temperature anomaly: a comparison of the current surface temperature to the historical average measured by satellites

Hotspot: number of degrees above the coral's threshold tolerance (a long-term historical summer-time average)

Degree Heating Week: amount of accumulated heat stress experienced by corals (i.e., a sum of Hotspots). Values above 8 deg C-weeks are associated with widespread bleaching and mortality

", "keyword": [ "NOAA", "Coral", "Bleaching", "satellite", "ocean", "heat stress", "web app" ], "issued": "2019-03-05T20:13:52.000Z", "modified": "2020-07-09T02:05:20.000Z", "publisher": { "name": "Esri Ocean and Coastal Environments" }, "contactPoint": { "@type": "vcard:Contact", "fn": "kvangraafeiland_oceans", "hasEmail": "mailto:KVanGraafeiland@esri.com" }, "accessLevel": "public", "spatial": "", "license": "Esri logo This work is licensed under the Esri Master License Agreement.
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