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Satellite remote sensing reveals widespread small-scale forest loss across France, indicating that conventional satellite monitoring systematically underestimates tree disturbance regimes.
Current large-scale satellite-based forest disturbance monitoring systems operate at 10–30 m resolution, which is too coarse to detect changes at the scale of individual trees resulting in a systematic underestimation of forest disturbances. Here, we introduce FORMSpoT (Forest Mapping with SPOT Time series), a decade-long (2014-2024), country-scale mapping of forest canopy height at 1.5 m resolution over France, together with FORMSpoT- Δ , annual disturbance polygons derived from height differences in the FORMSpoT time series. Canopy heights were derived from annual SPOT-6/7 composites using a hierarchical transformer model (PVTv2) trained on high-resolution airborne laser scanning (ALS) data. To enable robust change detection, we developed a post-processing pipeline combining co-registration and spatio-temporal total variation denoising. We find that (1) the French disturbance regime is dominated by small events. Sub-100 m 2 disturbances alone represent 72% of all events, and disturbances below 0.1 ha account for 97% of events and 39% of the disturbed area. These events are largely missed by Sentinel-1/2 and Landsat-based products. (2) Validated against successive ALS revisits across 19 sites and 5087 NFI plot revisits, FORMSpoT- Δ provides reliable detection (F1 > 0.8) above 100 m 2 while retaining sensitivity to finer events that coarser products do not capture. (3) At the national scale, FORMSpoT- Δ resolves contrasted disturbance regimes, from clear-cut-dominated dynamics in maritime pine plantations to diffuse, smaller disturbance events in mountain forests, and captures their temporal dynamics, including the salvage-logging signature of the 2017–2022 bark beetle crisis in northeastern France.
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Schwartz et al. (2026) studied this question.
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