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• Developed robust and independently validated forest disturbance monitoring. • Monthly forest canopy cover loss at 10 m resolution for Germany (09/2017-09/2024) • Revealed 924,000 ha forest canopy cover loss corresponding to 8.4% of total forest. • Found five major hotspot regions in central Germany with distinct dynamics. • Observed 2/3 of losses during winter, supporting the value of off-season monitoring. From 2018 onwards, multiple droughts and heatwaves hit Central Europe including Germany. These triggered, together with other disturbance drivers, unprecedented damages to forests. While annual field-based crown defoliation surveys provide valuable insights into overall forest condition in Germany, continuous spatio-temporal dynamics are not explicitly addressed in current monitoring practices. Here, we present a forest canopy cover loss (FCCL) assessment in Germany at monthly resolution between September 2017 and September 2024 based on Sentinel-2 and Landsat satellite time series. This approach enables near-continuous monitoring of forest disturbance dynamics across spatial and temporal scales. Our results reveal that a strip in central Germany was most affected. Storm events in late 2017 and early 2018 caused the first large-scale canopy losses, while drought- and heat-related disturbances, including bark beetle outbreaks in spruce forests, dominated in 2019 and 2020. FCCL rates generally declined after 2020. We recorded a total of 924,000 ha FCCL over the seven-year period (8.4% of Germany’s forest area), 84.5% of which were found in coniferous forests. At district and municipality level, we detected FCCL of up to more than 50%. Two-thirds of FCCL were recorded during winter (November-April), underscoring the importance of off-season monitoring. This study demonstrates the value of dense, multi-sensor satellite time series for operational forest monitoring. It highlights regions with high future disturbance potential, particularly in southern and southeastern Germany due to their high share of spruce forests. Future monitoring should integrate seasonal data and early-warning systems to improve adaptive forest management at national scale.
Thonfeld et al. (Sun,) studied this question.