Natural forests of the world – a 2020 baseline for deforestation and degradation monitoring

Informed decisions to reduce deforestation, protect biodiversity, and curb carbon emissions require not just knowing where forests are, but understanding their composition. Identifying natural forests, which serve as critical biodiversity hotspots and major carbon sinks, is particularly valuable. We developed a novel global natural forest map for 2020 at 10 m resolution. This map can support initiatives like the European Union's Deforestation Regulation (EUDR) and other forest monitoring or conservation efforts that require a comprehensive baseline for monitoring deforestation and degradation. The globally consistent map represents the probability of natural forest presence, enabling nuanced analysis and regional adaptation for decision-making. Evaluation using a global independent validation dataset demonstrated an overall accuracy of about 92%.

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Publication Details

Journal
Scientific Data
Published
2025-11-13
DOI
https://doi.org/10.1038/s41597-025-06097-z
Citations
2
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
1.60

Funders

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article

Natural forests of the world – a 2020 baseline for deforestation and degradation monitoring

Nicholas Clinton, Elizabeth Goldman, Charlotte Stanton, Mickael Rey et al.
2 citations
Scientific Data
Remote Sensing and LiDAR Applications
1.60
article

Natural forests of the world – a 2020 baseline for deforestation and degradation monitoring

Nicholas Clinton, Elizabeth Goldman, Charlotte Stanton, Mickael Rey, Keith Anderson, Drew W. Purves, Steffen Fritz, Yuchang Jiang, Sarah Carter, Myroslava Lesiv, Radost Stanimirova, Katelyn Tarrio, Anton Raichuk, Maxim Neumann, Michelle Sims, Dan Morris, Petra Poklukar
article en
2 citations

Abstract

Informed decisions to reduce deforestation, protect biodiversity, and curb carbon emissions require not just knowing where forests are, but understanding their composition. Identifying natural forests, which serve as critical biodiversity hotspots and major carbon sinks, is particularly valuable. We developed a novel global natural forest map for 2020 at 10 m resolution. This map can support initiatives like the European Union's Deforestation Regulation (EUDR) and other forest monitoring or conservation efforts that require a comprehensive baseline for monitoring deforestation and degradation. The globally consistent map represents the probability of natural forest presence, enabling nuanced analysis and regional adaptation for decision-making. Evaluation using a global independent validation dataset demonstrated an overall accuracy of about 92%.

Scientific DataVol. 12(1)
Google (United States) (US), International Institute for Applied Systems Analysis (AT), World Resources Institute (US), University of Zurich (CH), Google (Switzerland) (CH)
U.S. Forest Service
Openalex Percentile: Top 15%
Remote Sensing and LiDAR Applications
1.60
DOIOpen Access PDFOpenAlex
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