Country-wide, high-resolution monitoring of forest browning with Sentinel-2
Natural and anthropogenic disturbances are impacting the health of forests worldwide. Monitoring forest disturbances at scale is important to inform conservation efforts. Here, we present a scalable approach for country-wide mapping of forest greenness anomalies at the 10 m resolution of Sentinel-2. Using relevant ecological and topographical context and an established representation of the vegetation cycle, we learn a predictive quantile model of the normalised difference vegetation index (NDVI) derived from Sentinel-2 data. The resulting expected seasonal cycles are used to detect NDVI anomalies across Switzerland between April 2017 and August 2025. Goodness-of-fit evaluations show that...
| Authors | Samantha Biegel, David Brüggemann, Francesco Grossi et al. |
|---|---|
| Primary category | stat.AP |
| Published | 2 April 2026 |
| Last updated at source | 2 April 2026 |
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