Landslide databases as tools for integrated assessment of landslide risk: Fid-Bau Portal

Landslide databases as tools for integrated assessment of landslide risk

Klose, Martin

Abstract: Landslides are complex geomorphological phenomena with high destructive power and the potential to threaten human activity and infrastructures in many parts of the world. A major challenge in fundamental understanding of landslide risk relates to the many obstacles in developing methods that enable to bridge the gap between analysis of landslide processes and impacts. “From physical process to economic impact”, these words represent the basic principle of methodological research in this study, aiming at the development of analytical tools for assessing landslide risk in integrated perspective. The present study introduces new and optimized methods embedded in an innovative risk assessment framework that is tailored for use with data sets extracted from landslide databases. This new approach to risk assessment rests upon a variety of different methods, including knowledge discovery in landslide databases, landslide susceptibility models, and statistical analysis of landslide triggering mechanisms. Alternatively, a key role is played by a toolset for cost survey and modeling, whereby methods to analyze fiscal cost impacts occupy center stage as well. Much of this research refers to regional case studies in NW Germany, Central Europe. Method development makes use of a landslide database for the Federal Republic of Germany and tools such as Geographical Information Systems (GIS). The purpose of a regional landslide susceptibility model is to identify areas at risk of landslides and to assess potential infrastructure exposure. Temporal landslide hazard is derived from a soil water balance model that is coupled with historical landslide time series. These two methods are integrated into a new approach to cost modeling and GIS-based regionalization of direct damage costs. The application of the developed toolset in regional case studies proves its capacity to open a whole new window on the study of landslide risk.