Unmanned Aerial Vehicles (UAVs) have become indispensable platforms for high-resolution monitoring of landslide processes, offering rapid deployment, flexible acquisition strategies, and integration of diverse sensors such as RGB, LiDAR, multispectral, thermal, and hyperspectral systems. Recent advances in data fusion and AI-driven analytics enable UAV-derived products to move beyond traditional photogrammetry toward comprehensive digital twins of landslide-prone environments. This session invites contributions exploring UAV applications for landslide detection, mapping, kinematic monitoring, hazard assessment, and post-event analysis. Topics include novel workflows for integrating multi-sensor datasets, automated feature extraction using computer vision and deep learning, and 3D point cloud fusion for terrain change detection that leverages UAV products. We welcome case studies from a range of geomorphological contexts as well as methodological innovations that address challenges such as vegetation cover, temporal repeatability, and scaling from local to regional assessments. The session aims to bring together researchers and practitioners to showcase cutting-edge UAV solutions that can enhance landslide science.