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    • Tree Cover Estimates at 30 m Resolution for Mexico, 2016-2018

    Metadata Updated: December 6, 2023

    The data set provides multi-year (2016-2018) percent tree cover (TC) estimates for entire Mexico at 30 m spatial resolution. The TC data (hereafter, NEX-TC) was derived from the 30 m Landsat Collection 1 product and a hierarchical deep learning approach (U-Net) developed in a previous CMS effort for the conterminous United States (CONUS) (Park et al., 2022). The hierarchical U-Net framework first developed a U-Net model for very high-resolution aerial images (NAIP) using training labels derived from previous work based on an interactive image segmentation tool and iterative updates with expert knowledge (Basu et al., 2015). The developed NAIP U-Net model and NAIP data produced 1-m NAIP TC across all lower 48 CONUS states. A Landsat U-Net model was developed for multi-year and large-scale TC mapping based on the very high-resolution NAIP TC made in the earlier stage. The Landsat U-Net model developed was adopted over the CONUS for testing its transferability, validation, and improvement across Mexico. This dataset provides national-scale percent tree cover estimates over Mexico and can be helpful for studies of carbon cycling, land cover and land use change, etc. The team has been working on improving temporal stability of the product and will update the product once the next version is ready to be shared.

    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 May 30, 2023
    Metadata Updated Date December 6, 2023

    Metadata Source

    Harvested from NASA Data.json

    Other Data Resources

    Graphic Preview

    Multi-year mean (2016-2018) of percent tree cover maps for Mexico.

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date May 30, 2023
    Metadata Updated Date December 6, 2023
    Publisher ORNL_DAAC
    Maintainer
    Identifier C2612824717-ORNL_CLOUD
    Data First Published 2023-02-15
    Language en-US
    Data Last Modified 2023-06-12
    Category CMS, 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 Park, T., and R. Vargas. 2022. Tree Cover Estimates at 30 m Resolution for Mexico, 2016-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2137
    Graphic Preview Description Multi-year mean (2016-2018) of percent tree cover maps for Mexico.
    Graphic Preview File https://daac.ornl.gov/CMS/guides/Tree_Canopy_Cover_Mexico_Fig1.png
    Harvest Object Id 9d96febe-7729-409c-b950-3f25ee117b18
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://doi.org/10.3334/ORNLDAAC/2137
    Metadata Type geospatial
    Old Spatial -118.4 14.53 -86.7 32.72
    Program Code 026:001
    Source Datajson Identifier True
    Source Hash d8b478b508f4b4016226847a4e879702134a70752494df0ee36ce3c4b69f5cae
    Source Schema Version 1.1
    Spatial
    Temporal 2016-01-01T00:00:00Z/2018-12-31T23:59:59Z

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