
Ensuring EUDR Compliance: Evaluating Global Forest Maps for Deforestation Monitoring The European Union Deforestation Regulation (EUDR) mandates that products derived from the commodities beef, cocoa, coffee, soy, timber, rubber, palm oil and their derivates must be deforestation-free after 31 December 2020. This regulation places new demands on both producers and regulators to prove and verify compliance using spatial data and maps. This technical and policy brief is published as part of the GEOS-EUDR project and draws on a systematic review of 21 global forest tree cover datasets and their assessment of applicability as EUDR-reference maps (Freitas Beyer et al. 2025)[1]. Only eight datasets meet key spatial, temporal, and definitional criteria for EUDR compliance checks, and only two datasets matched all three EUDR forest definition criteria: canopy cover (≥10%), tree height (≥5m), and minimum mapping unit (≥0.5 ha). The findings reveal significant over- and underestimation patterns, inconsistencies in forest definitions, and regional data limitations. The brief provides actionable recommendations for operators and competent authorities when applying map products for deforestation verification, and outlines key insights for decision and policy makers how to support deforestation monitoring. The assessment of global forest and tree cover datasets reveals that dataset selection matters immensely for EUDR compliance. While Earth Observation maps offer powerful tools for monitoring, their limitations (especially regarding resolution, forest definitions, and regional suitability) must be carefully considered. This technical and policy brief underscores the need for context-aware, multi-source verification approaches, and stronger coordination between data providers, map users such as operators, and regulators. [1] Freitas Beyer, J., Köthke, M., & Lippe, M. (2025). Assessing the Suitability of Available Global Forest Maps as Reference Tools for EUDR-Compliant Deforestation Monitoring. Remote Sensing 17, 3012. DOI: 10.3390/rs17173012
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