Annual Land Use and Urban Land Cover: Ethiopia, Nigeria, and South Africa, 2016-2020
This dataset provides a two-tier annual Land Use (LU) and Urban Land Cover (LC) product suite over three African countries, Ethiopia, Nigeria, and South Africa, across a 5-year period of 2016-2020. Remote sensing data sources were used to create 30-m resolution LU maps (Tier-1), which were then utilized to delineate urban boundaries for 10-m resolution LC classes (Tier-2). Random Forest machine learning classifier models were trained on reference data for each tier and country (but one model was trained across all years); models were validated using a separate reference data set for each tier and country. Tier-1 LU maps were based on the 30-m Landsat time series, and Tier-2 urban LC maps were based on the 10-m Sentinel-2 time series. Additional data sources included climate, topography, night-time light, and soils. The overall map accuracy was 65-80% for Tier-1 maps and 60-80% for Tier-2 maps, depending on the year and country. The data are provided in cloud optimized GeoTIFF (COG) format.
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Original Metadata
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "026:00" ] |
| contactPoint |
{ "fn": "Earthdata Forum", "@type": "vcard:Contact", "hasEmail": "mailto:earthdata-support@nasa.gov" } |
| description | This dataset provides a two-tier annual Land Use (LU) and Urban Land Cover (LC) product suite over three African countries, Ethiopia, Nigeria, and South Africa, across a 5-year period of 2016-2020. Remote sensing data sources were used to create 30-m resolution LU maps (Tier-1), which were then utilized to delineate urban boundaries for 10-m resolution LC classes (Tier-2). Random Forest machine learning classifier models were trained on reference data for each tier and country (but one model was trained across all years); models were validated using a separate reference data set for each tier and country. Tier-1 LU maps were based on the 30-m Landsat time series, and Tier-2 urban LC maps were based on the 10-m Sentinel-2 time series. Additional data sources included climate, topography, night-time light, and soils. The overall map accuracy was 65-80% for Tier-1 maps and 60-80% for Tier-2 maps, depending on the year and country. The data are provided in cloud optimized GeoTIFF (COG) format. |
| distribution |
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| identifier | 10.3334/ORNLDAAC/2367 |
| keyword |
[ "earth-science-ecosystems-biosphere-anthropogenic-human-influenced-ecosystems", "earth-science-environmental-governance-management-human-dimensions-land-management", "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification" ] |
| license | https://www.usa.gov/government-works |
| modified | 2026-06-22 |
| programCode |
[ "026:000" ] |
| publisher |
{ "name": "ORNL_DAAC", "@type": "org:Organization" } |
| spatial |
"["CARTESIAN", [{"WestBoundingCoordinate": 2.5725, "NorthBoundingCoordinate": 16.2061, "EastBoundingCoordinate": 49.6875, "SouthBoundingCoordinate": -35.3369}]]"
|
| temporal | 2016-01-01/2020-12-31 |
| theme |
[ "Earth Science" ] |
| title | Annual Land Use and Urban Land Cover: Ethiopia, Nigeria, and South Africa, 2016-2020 |
