The European Forest Disturbance Atlas: a forest disturbance monitoring system using the Landsat archive

Forests in Europe are undergoing complex changes that require a comprehensive monitoring of disturbance occurrence. Here, we present the European Forest Disturbance Atlas (EFDA), a Landsat-based approach for mapping annual forest disturbances across continental Europe from 1985 onwards. We built a consistent Landsat data cube of summer composites and compiled reference data on forest land use and forest disturbances. A classification-based approach was developed to detect forest disturbances annually, therefore accounting for multiple disturbance events per time series. The EFDA contains annual layers on disturbance occurrence, severity, and agent, as well as aggregated layers on the number of disturbances and the latest and greatest disturbance year. Based on the annual disturbance estimates (1985–2023), we quantified a total forest disturbed area of 439 000 km2, which increases to 610 000 km2 when accounting for multiple overlapping disturbance events. Map accuracies of the disturbance classification showed an overall F1 score of 0.89, with very low errors (<1 %) for the undisturbed class and with commission and omission errors for the disturbed class of 17.3 % and 22.5 %, respectively. Further, temporal validation revealed that errors decreased over time, with commission errors decreasing substantially to 10.6 % after the year 2000. We designed and implemented our workflow to create annual forest disturbance maps for easy updating when new data arrive and in an open-access framework to facilitate reproducibility, thus paving the road for an operational forest disturbance system in Europe. EFDA products are available at https://doi.org/10.5281/zenodo.13333034 (Viana-Soto and Senf, 2024).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-05
DOI
https://doi.org/10.5281/zenodo.17236096
Primary Topic
Diverse Scientific and Economic Studies
Type
article
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article

The European Forest Disturbance Atlas: a forest disturbance monitoring system using the Landsat archive

Zenodo (CERN European Organization for Nuclear Research)
Diverse Scientific and Economic Studies
article

The European Forest Disturbance Atlas: a forest disturbance monitoring system using the Landsat archive

article en

Abstract

Forests in Europe are undergoing complex changes that require a comprehensive monitoring of disturbance occurrence. Here, we present the European Forest Disturbance Atlas (EFDA), a Landsat-based approach for mapping annual forest disturbances across continental Europe from 1985 onwards. We built a consistent Landsat data cube of summer composites and compiled reference data on forest land use and forest disturbances. A classification-based approach was developed to detect forest disturbances annually, therefore accounting for multiple disturbance events per time series. The EFDA contains annual layers on disturbance occurrence, severity, and agent, as well as aggregated layers on the number of disturbances and the latest and greatest disturbance year. Based on the annual disturbance estimates (1985–2023), we quantified a total forest disturbed area of 439 000 km2, which increases to 610 000 km2 when accounting for multiple overlapping disturbance events. Map accuracies of the disturbance classification showed an overall F1 score of 0.89, with very low errors (<1 %) for the undisturbed class and with commission and omission errors for the disturbed class of 17.3 % and 22.5 %, respectively. Further, temporal validation revealed that errors decreased over time, with commission errors decreasing substantially to 10.6 % after the year 2000. We designed and implemented our workflow to create annual forest disturbance maps for easy updating when new data arrive and in an open-access framework to facilitate reproducibility, thus paving the road for an operational forest disturbance system in Europe. EFDA products are available at https://doi.org/10.5281/zenodo.13333034 (Viana-Soto and Senf, 2024).

Zenodo (CERN European Organization for Nuclear Research)
Technical University of Munich (DE)
Life in Land
Openalex Percentile: Top 34%
Diverse Scientific and Economic Studies
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