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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


Metadata Created Date May 30, 2023
Metadata Updated Date December 6, 2023

Metadata Source

Harvested from NASA Data.json

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
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
Metadata Catalog ID
Schema Version
Catalog Describedby
Citation Park, T., and R. Vargas. 2022. Tree Cover Estimates at 30 m Resolution for Mexico, 2016-2018. ORNL DAAC, Oak Ridge, Tennessee, USA.
Graphic Preview Description Multi-year mean (2016-2018) of percent tree cover maps for Mexico.
Graphic Preview File
Harvest Object Id 9d96febe-7729-409c-b950-3f25ee117b18
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL
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
Temporal 2016-01-01T00:00:00Z/2018-12-31T23:59:59Z

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