Landslide Detection and Mapping Using Deep Learning Across Multi-Source Satellite Data and Geographic Regions

arXiv:2507.01123v2 Announce Type: replace-cross Abstract: Landslides pose severe threats to infrastructure, economies, and human lives, necessitating accurate detection and predictive mapping across diverse geographic regions. With advancements in deep learning and remote sensing, automated landslide detection has become increasingly effective. This study presents a comprehensive approach integrating multi-source satellite imagery and deep learning models to enhance landslide identification and prediction. We leverage Sentinel-2 multispectral data and ALOS PALSAR-derived slope and Digital Elev

Source: arXiv cs.LG — read the full report at the original publisher.

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