Abstract
This study addresses the modeling of deep-seated landslides, focusing
on the El Forn landslide in Andorra, using remote sensing and
data-driven approaches to create risk maps. A temperature-based model is
adjusted with data from an instrumented borehole to determine material
properties and conditions. The calibrated model is compared to
Interferometric Synthetic Aperture Radar (InSAR) data, using the
data for spatial analysis and creating a correlation map through
kriging. This map leads to a physics-informed risk map indicating
areas of instability. An uncertainty analysis of the model highlights
its limitations but underscores the utility of such maps for policy and
planning in areas prone to landslides. This approach provides a novel
tool for assessing landslide risks, combining in-situ and remote
sensing data for effective risk management.