Deep learning interpretability for understanding forest disturbance driver classification from Sentinel-1 and -2 data

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Journal
International Journal of Remote Sensing
Published
2025-12-11
DOI
https://doi.org/10.1080/01431161.2025.2598147
Primary Topic
Tree Root and Stability Studies
Type
article
Field-Weighted Citation Impact
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article

Deep learning interpretability for understanding forest disturbance driver classification from Sentinel-1 and -2 data

Johannes Reiche, Bart Slagter, Laura Elena Cué La Rosa, Diego Marcos
International Journal of Remote Sensing
Tree Root and Stability Studies
article

Deep learning interpretability for understanding forest disturbance driver classification from Sentinel-1 and -2 data

Johannes Reiche, Bart Slagter, Laura Elena Cué La Rosa, Diego Marcos
article en

Abstract

No abstract available for this paper.
International Journal of Remote SensingVol. 47(3)
Institut national de recherche en sciences et technologies du numérique (FR), Université de Montpellier (FR), Wageningen University & Research (NL)
Openalex Percentile: Top 59%
Tree Root and Stability Studies
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