A gridded dataset of European Forest Types to support forest monitoring, modelling and reporting

Abstract. A standardized system of nomenclature for forest types is essential for effectively monitoring and understanding the impacts of climate change on diverse ecosystems in Europe and beyond. A comprehensive classification system, such as the European Forest Types (EFTs) scheme, is essential for assessing baseline conditions, tracking changes, and guiding conservation decisions. A unified forest type nomenclature supports international collaboration, enables researchers and policymakers to accurately compare data across regions and time periods, and enhances the development of targeted conservation strategies and adaptive management practices aimed at preserving biodiversity and ecosystem services. This classification breaks down forested areas in Europe into a handful of ecologically homogeneous units, thus facilitating the analysis of data related to forest conditions and management practices across a wide range of climatic and edaphic conditions. The current lack of an EFTs map for Europe prompted its processing, using a shared rule-based expert system algorithm. Utilizing a dataset featuring 39 “relative probability of presence (RPP) maps” of tree species and various forest masks, the algorithm identified 14 EFT categories. This initiative filled a critical gap in spatial monitoring, providing the first consistent pan-European EFT maps gridded dataset. The availability of standardized and comprehensive spatial data on forest types enhances our capacity to understand, manage, and conserve forest ecosystems effectively. Such data support biodiversity conservation and ensure the sustained provision of essential ecosystem services, highlighting the critical role of forest types in maintaining ecological balance and supporting human well-being. The European Forest Types map gridded dataset is freely available in Zenodo at https://doi.org/10.5281/zenodo.18496150 (Giannetti et al., 2026).

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Publication Details

Journal
Earth system science data
Published
2026-09-04
DOI
https://doi.org/10.5194/essd-18-6435-2026
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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A gridded dataset of European Forest Types to support forest monitoring, modelling and reporting

Yamuna Giambastiani, Alessio Collalti, Elisa Grieco, Ilaria Zorzi et al.
Earth system science data
Remote Sensing and LiDAR Applications
article

A gridded dataset of European Forest Types to support forest monitoring, modelling and reporting

Yamuna Giambastiani, Alessio Collalti, Elisa Grieco, Ilaria Zorzi, Mauro Morichetti, G. Chirici, Mathias Neumann, Sorin Cheval, Anna Barbati, Elia Vangi, Alice Ludvig, Stefanie Linser, Livia Passarino, Giuliano Secchi, Nicu Constantin Tudose, Irene Fattoretto, Marco Marchetti, Giovanni D’Amico, Davide Travaglini, Jessica Scriva, Francesca Giannetti, Piermaria Corona
article en

Abstract

Abstract. A standardized system of nomenclature for forest types is essential for effectively monitoring and understanding the impacts of climate change on diverse ecosystems in Europe and beyond. A comprehensive classification system, such as the European Forest Types (EFTs) scheme, is essential for assessing baseline conditions, tracking changes, and guiding conservation decisions. A unified forest type nomenclature supports international collaboration, enables researchers and policymakers to accurately compare data across regions and time periods, and enhances the development of targeted conservation strategies and adaptive management practices aimed at preserving biodiversity and ecosystem services. This classification breaks down forested areas in Europe into a handful of ecologically homogeneous units, thus facilitating the analysis of data related to forest conditions and management practices across a wide range of climatic and edaphic conditions. The current lack of an EFTs map for Europe prompted its processing, using a shared rule-based expert system algorithm. Utilizing a dataset featuring 39 “relative probability of presence (RPP) maps” of tree species and various forest masks, the algorithm identified 14 EFT categories. This initiative filled a critical gap in spatial monitoring, providing the first consistent pan-European EFT maps gridded dataset. The availability of standardized and comprehensive spatial data on forest types enhances our capacity to understand, manage, and conserve forest ecosystems effectively. Such data support biodiversity conservation and ensure the sustained provision of essential ecosystem services, highlighting the critical role of forest types in maintaining ecological balance and supporting human well-being. The European Forest Types map gridded dataset is freely available in Zenodo at https://doi.org/10.5281/zenodo.18496150 (Giannetti et al., 2026).

Earth system science dataVol. 18(9)
Università degli Studi della Tuscia (IT), Chamber of Deputies (IT), Babeș-Bolyai University (RO), National Institute for Research and Development in Forestry "Marin Drăcea" (RO), Istituto per il Sistema Produzione Animale in Ambiente Mediterraneo (IT), Administraţia Naţională de Meteorologie (RO), University of Florence (IT), Sapienza University of Rome (IT), University of Palermo (IT), BOKU University (AT)
European Commission, Ministero dell’Istruzione, dell’Università e della Ricerca, Università degli Studi di Firenze, HORIZON EUROPE Framework Programme, HORIZON EUROPE Food, Bioeconomy, Natural Resources, Agriculture and Environment
Life in Land
Openalex Percentile: Top 82%
Remote Sensing and LiDAR Applications
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