GEOS-EUDR: Forest Agreement Layer (FAL) - Google Earth Engine Script

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Authors: Juliana Freitas Beyer, Margret Köthke, Melvin Lippe
Cited by: 0

Abstract

The Forest Agreement Layer (FAL) is a set of open access Google Earth Engine (GEE) scripts that merges global forest datasets (currently up to 9) into one single map, separating steps requiring user input from automated tasks. The term forest agreement refers to a multi-source blend of global forest and tree-cover datasets to highlight where maps agree or disagree on forest/tree cover. A FAL can be for example used for due diligence purposes relating to the Regulation on Deforestation-free Products (EUDR), as it refers to the cut-off year and the definitions set out in the regulation. It can also be used to monitor compliance with deforestation-free requirements that fall outside the scope of the EUDR, or for other purposes defined by the user, e.g., using other maps at landscape, national or administrative-level. The approach builds on the work of Freitas Beyer et al. (2025), who identified eight datasets as particularly well suited for compliance verification under the EUDR. The current version of the collection extends this foundation by adding a ninth dataset Global Forest Types 2020, v0 (Bourgoin et al., 2024) which is available through the JRC portal and the Google Earth Engine catalog. The current FAL product here remains closely aligned with the criteria defined in the original study by Freitas Beyer et al. (2025). However, as the Global Forest Types 2020 dataset was released after the article’s final compilation in November 2024, it could not be included in their assessment. Nevertheless, the GEE script allows users to expand the nine currently curated datasets according to their FAL needs or data requirements.

Fields of Study & Subjects

Conservation Biodiversity and Resource Management Remote Sensing in Agriculture Remote Sensing and LiDAR Applications

Publication details

Journal / source
OpenAgrar
Publication date
26 January 2026
Language
EN
Document type
Dataset