Global Landslide Monitoring through Satellite Observations and Land Surface Modeling

Landslides affect nearly every country in the world, causing economic damage and human loss every year. Several factors have been identified as critical in predicting landslides, but the relationship between landslides and water storage at the global scale is not well understood. This challenge requires a multi-disciplinary and multi-scale approach in which insights in natural hazards are matched with recent remote sensing techniques and cutting-edge global land surface modelling and assimilation systems. The project aims at using reports of landslide occurrences in the global landslide catalog (GLC), along with satellite-based, model-based or data assimilation information about water budget components to improve probabilistic predictions of landslide occurrences. First, long-time integrated, coarsescale, summary statistics of soil moisture, terrestrial water storage, precipitation and evapotranspiration will be studied for their relative impact as landslide controlling variables on the quality of global landslide susceptibility maps. Second, time-variable, percentile values of these water budget components will be used to enhance daily probabilistic predictions of landslide occurrences. It will be verified to which extent satellite observations about water budget components add useful information to land surface model information for the estimation of global landslide occurrences.