Monitoring and Modeling of Landslides

Landslides such as rock- and soil slides, rockfalls, and debris flows, are significant geological processes that pose risks to infrastructure, and human lives. Effective management of these hazards relies on a comprehensive methodological approach with monitoring, assessment, and multi-scale modeling, which enables a the understanding of the dynamics of landslides. Advances in sensor technologies, computational modeling, and data integration enhance predictive accuracy and early warning capabilities. Such interdisciplinary efforts are critical for mitigating the impacts of landslides. The monitoring involves the continuous or periodic collection of data to track slope stability, movement dynamics, and environmental conditions. Advanced techniques include, but are not limited to: – Ground-Based Methods, such as GNSS and Total Stations and inclinometer measurements to detect movement in slopes. – Remote Sensing, such as LiDAR, InSAR or UAVs, to detect surface changes over time. – Geotechnical Sensors, such as piezometers, strain gauges, and accelerometers to collect real-time data. The assessment focuses on understanding the triggering mechanisms, susceptibility, and potential impacts of landslides, which includes: – Hazard analysis according to inventory mapping and susceptibility models. – Triggering Factors, like climatic influences, changes in pore water pressure, seismic events and anthropogenic activities, as excavation or deforestation. The modeling of landslides across spatial and temporal scales bridges monitoring data with predictive capabilities. Approaches include for for example empirical models, physical models, numerical models or data driven models.