Description
This dataset provides a comparison of forest extent agreement from seven remote sensing-based products across Mexico. These satellite-derived products include European Space Agency 2020 Land Cover Map for Mexico (ESA), Globeland30 2020 (Globeland30), Commission for Environmental Cooperation 2015 Land Cover Map (CEC), Impact Observatory 2020 Land Cover Map (IO), NAIP Trained Mean Percent Cover Map (NEX-TC), Global Land Analysis and Discovery Global 2010 Tree Cover (Hansen-TC), and Global Forest Cover Change Tree Cover 30 m Global (GFCC-TC). All products included data at 10-30 m resolution and represented the state of forest or tree cover from 2010 to 2020. These seven products were chosen based on: a) feedback from end-users in Mexico; b) availability and FAIR (findable, accessible, interoperable, and replicable) data principles; and c) products representing different methodological approaches from global to regional scales. The combined agreement map documents forest cover for each satellite-derived product at 30-m resolution across Mexico. The data are in cloud optimized GeoTIFF format and cover the period 2010-2020. A shapefile is included that outlines Mexico mainland areas.
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| Get a related visualization | JPG | Percent agreement among seven satellite-based forest cover products (A). The percentage represents how many products identified each pixel as being forested. An enlarged representation of Edomex (Estado de Mexico) for the forest extent agreement map (B). Source: Braden et al. (2024). | Open resource |
| View documentation related to this dataset | HTML | ORNL DAAC Data Set Documentation | Open resource |
| Download this dataset | HTML | This link allows direct data access via Earthdata login | Open resource |
| View documentation related to this dataset | Satellite-Derived Forest Extent Likelihood Map for Mexico: SatelliteDerived_Forest_Mexico.pdf | Open resource | |
| This dataset's landing page | HTML | Data set Landing Page DOI URL | Open resource |
| Google Scholar search results | HTML | Search results for publications that cite this dataset by its DOI. | Open resource |