Landslides are a landscape modelling process inducing geomorphological changes on slopes in coastal, hilly, and mountainous areas. Their occurrence is generally controlled by predisposing (e.g., morphology, lithological and structural setting, vegetation cover, land use, climate, etc.) and triggering factors (e.g., heavy rainfall and snowfall events, wildfires, earthquakes, human activity, etc.). Therefore, paying attention to these factors in landslide analyses is essential to set an organic correlation between climate regime, geological, morphostructural and seismic setting, and slope instability phenomena. This type of analysis, together with the investigation and monitoring of existing landslides, is critical for mitigating their impact on human settlements and infrastructure. Field investigation, coupled with remote sensing technologies are essential tools in the analysis of landslides and predisposing factors, offering the ability to collect detailed and accurate data over large and inaccessible areas. This session aims to explore the use of these different types of techniques: field survey and remote sensing techniques, including LiDAR (Light Detection and Ranging), InSAR (Interferometric Synthetic Aperture Radar), and optical satellite and drone imagery, for the detection, mapping, and monitoring of landslides. These technologies provide valuable data that enable the analysis of terrain morphology, identification of landslide-prone areas, and monitoring of ground movements. The integration of remote sensing data with traditional geotechnical and geomorphological approaches can enhance the understanding of landslide dynamics and improve the development of predictive modelling and scenario reconstruction. This session gathers field survey and remote sensing studies, methodological and case studies, to highlight the advancements in innovative approaches and their vital role in landslide and geomorphological risk assessment, contributing to the development of effective mitigation strategies and early warning systems.