Overview
DOI | https://doi.org/10.3334/ORNLDAAC/2367 |
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Version | 1 |
Project | |
Published | 2024-09-06 |
Usage | 18 downloads |
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.
Science Keywords
- LAND SURFACE
- LAND USE/LAND COVER
- LAND USE/LAND COVER CLASSIFICATION
- HUMAN DIMENSIONS
- ENVIRONMENTAL GOVERNANCE/MANAGEMENT
- LAND MANAGEMENT
- LAND USE/LAND COVER CLASSIFICATION
- BIOSPHERE
- ECOSYSTEMS
- ANTHROPOGENIC/HUMAN INFLUENCED ECOSYSTEMS
- URBAN LANDS
Data Use and Citation
This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use Policy. See our Data Use and Citation Policy for more information.
Data Files
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Companion Files
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Dataset Companion Files
Dataset has 1 companion files.
- LULC_Nigeria_Ethiopia_SAfrica.pdf