Neumann, M., Raichuk, A., Jiang, Y., Rey, M., Stanimirova, R., Sims, M.J., Carter, S., Goldman, E., Anderson, K., Poklukar, P., Tarrio, K., Lesiv, M.
ORCID: https://orcid.org/0000-0001-9846-3342, Fritz, S.
ORCID: https://orcid.org/0000-0003-0420-8549, Clinton, N., Stanton, C., Morris, D., & Purves, D.
(2025).
Natural forests of the world – a 2020 baseline for deforestation and degradation monitoring.
Scientific Data 12 (1) e114081. 10.1038/s41597-025-06097-z.
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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%.
| Item Type: | Article |
|---|---|
| Research Programs: | Advancing Systems Analysis (ASA) Advancing Systems Analysis (ASA) > Novel Data Ecosystems for Sustainability (NODES) Strategic Initiatives (SI) |
| Depositing User: | Luke Kirwan |
| Date Deposited: | 17 Nov 2025 09:02 |
| Last Modified: | 17 Nov 2025 09:02 |
| URI: | https://pure.iiasa.ac.at/20989 |
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