An Unexpectedly Large Count of Trees in the West African Sahara and Sahel
This dataset provides georeferenced polygon vectors of individual tree canopy geometries for dryland areas in West African Sahara and Sahel that were derived using deep learning applied to 50-cm resolution satellite imagery. More than 1.8 billion non-forest trees (i.e., woody plants with a crown size over 3 m2) over about 1.3 million km2 were identified from panchromatic and pansharpened normalized difference vegetation index (NDVI) images at 0.5-m spatial resolution using an automatic tree detection framework based on supervised deep-learning techniques. Combined with existing and future fieldwork, these data lay the foundation for a comprehensive database that contains information on all individual trees outside of forests and could provide accurate estimates of woody carbon in arid and semi-arid areas throughout the Earth for the first time.
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Original Metadata
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PNG -
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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 georeferenced polygon vectors of individual tree canopy geometries for dryland areas in West African Sahara and Sahel that were derived using deep learning applied to 50-cm resolution satellite imagery. More than 1.8 billion non-forest trees (i.e., woody plants with a crown size over 3 m2) over about 1.3 million km2 were identified from panchromatic and pansharpened normalized difference vegetation index (NDVI) images at 0.5-m spatial resolution using an automatic tree detection framework based on supervised deep-learning techniques. Combined with existing and future fieldwork, these data lay the foundation for a comprehensive database that contains information on all individual trees outside of forests and could provide accurate estimates of woody carbon in arid and semi-arid areas throughout the Earth for the first time. |
| distribution |
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| identifier | 10.3334/ORNLDAAC/1832 |
| keyword |
[ "earth-science-ecosystems-biosphere-terrestrial-ecosystems", "earth-science-vegetation-biosphere-canopy-characteristics", "earth-science-vegetation-biosphere-forest-composition-vegetation-structure", "earth-science-vegetation-biosphere-vegetation-cover" ] |
| license | https://www.usa.gov/government-works |
| modified | 2026-06-22 |
| programCode |
[ "026:000" ] |
| publisher |
{ "name": "ORNL_DAAC", "@type": "org:Organization" } |
| spatial |
"["CARTESIAN", [{"WestBoundingCoordinate": -18.0, "NorthBoundingCoordinate": 24.0294, "EastBoundingCoordinate": -5.48513, "SouthBoundingCoordinate": 11.3531}]]"
|
| temporal | 2005-11-01/2018-03-31 |
| theme |
[ "Earth Science" ] |
| title | An Unexpectedly Large Count of Trees in the West African Sahara and Sahel |
