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    • An Unexpectedly Large Count of Trees in the West African Sahara and Sahel

    Metadata Updated: December 6, 2023

    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.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

    Downloads & Resources

    Dates

    Metadata Created Date September 14, 2023
    Metadata Updated Date December 6, 2023

    Metadata Source

    Harvested from NASA Data.json

    Other Data Resources

    Graphic Preview

    The tree density per hectare is shown for different crown size classes: (a) 3-15 m2, (b) 15-50 m2, (c) 50-200 m2, (d) >200 m2. Source: Brandt et al. (2020)

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date September 14, 2023
    Metadata Updated Date December 6, 2023
    Publisher ORNL_DAAC
    Maintainer
    Identifier C2761798565-ORNL_CLOUD
    Data First Published 2020-12-03
    Language en-US
    Data Last Modified 2023-09-06
    Category Vegetation, geospatial
    Public Access Level public
    Bureau Code 026:00
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Metadata Catalog ID https://data.nasa.gov/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Citation Brandt, M., C.J. Tucker, A. Kariryaa, K. Rasmussen, C. Abel, J.L. Small, J. Chave, L.V. Rasmussen, P. Hiernaux, A.A. Diouf, L. Kergoat, O. Mertz, C. Igel, F. Gieseke, J. Schöning, S. Li, K.A. Melocik, J.R. Meyer, S. Sinno, E. Romero, E.N. Glennie, A. Montagu, M. Dendoncker, and R. Fensholt. 2020. An Unexpectedly Large Count of Trees in the West African Sahara and Sahel. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1832
    Graphic Preview Description The tree density per hectare is shown for different crown size classes: (a) 3-15 m2, (b) 15-50 m2, (c) 50-200 m2, (d) >200 m2. Source: Brandt et al. (2020)
    Graphic Preview File https://daac.ornl.gov/VEGETATION/guides/Non-Forest_Trees_Sahara_Sahel_Fig1.png
    Harvest Object Id 0d3429ff-addc-4cae-8b2e-46c66c7123f6
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://doi.org/10.3334/ORNLDAAC/1832
    Metadata Type geospatial
    Old Spatial -18.0 11.35 -5.49 24.03
    Program Code 026:001
    Source Datajson Identifier True
    Source Hash 63fc5a5c83f250f4c18515c8bacef2797990a7098cb9e424719d3981ba82143b
    Source Schema Version 1.1
    Spatial
    Temporal 2005-11-01T00:00:00Z/2018-03-31T23:59:59Z

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