Remote Sensing Monitoring of Geomorphological Hazards: From Observing to Anticipating Risk Across Scales

This Special Issue brings together six contributions showcasing how remote sensing technologies are transforming the monitoring and assessment of geomorphological hazards, with a particular focus on landslides. The papers collected in the Special Issue span diverse contexts: from hyperspectral mineral mapping in mud eruption systems to multi-temporal LiDAR and Unmanned Aerial Vehicle (UAV) photogrammetry for coastal cliff retreat, landslide evolution, and debris-flow dynamics. Advanced techniques such as Digital Image Correlation (DIC), Structure-from-Motion photogrammetry, and DEM differencing enable precise quantification of displacements, volumes, and kinematics across scales, while emergency UAV deployments highlight operational workflows for rapid hazard mapping under crisis conditions. Collectively, these studies emphasize multi-sensor integration, uncertainty evaluation, and reproducible methodologies that bridge scientific research, civil protection, and education. They demonstrate that Remote Sensing is not only improving observational capacity but also fostering proactive risk governance, early warning strategies, and resilience planning in line with the Sendai Framework for Disaster Risk Reduction 2015-2030, the global plan to reduce disaster losses. Despite the limited contributions collected, by coupling high-resolution spatial data with process-based interpretation, this Special Issue advances the state of the art in hazard monitoring and provides a roadmap for future applications in engineering geology, geomorphology, and geospatial technologies.