Mexico Tree Cover Estimates at 30-Meter Resolution

Multi-year (2016-2018) percent tree cover estimates for all of Mexico at a 30-meter spatial resolution. NASA developed this dataset using a hierarchical deep learning (U-Net) model trained on Landsat and high-resolution NAIP imagery. The product supports national-scale studies of carbon cycling and land use change.

Use Cases

• Modeling carbon sequestration and emissions using percent tree cover as a key variable.
• Analyzing land cover and land use change patterns across Mexico from 2016 to 2018.
• Validating regional or global forest cover products with a higher-resolution national dataset.
• Assessing forest canopy characteristics and vegetation cover for ecological studies.

Strengths

• Provides national coverage for the entire country of Mexico.
• Uses a hierarchical deep learning method (U-Net) trained on very high-resolution 1-meter NAIP imagery.
• Offers a multi-year composite estimate for the 2016-2018 period.

Limitations

• Sources conflict on the last updated date: one lists 2018-12-31, another lists 2026-03-12, indicating potential metadata inconsistency.
• Specific column names, row counts, and file sizes are not provided by any source.

Provenance

Source

National Aeronautics and Space Administration

Collection Method

Derived from 30-meter Landsat Collection 1 imagery using a hierarchical U-Net deep learning model.

Time Range

2016-2018

Freshness

2026-03-12 20:59:23.648868

Geography

Mexico