Landslide Databases as Tools for Integrated Assessment of Landslide Risk

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Martin Klose
430 g
241x160x15 mm
Springer Theses

Martin Klose received his PhD in Physical Geography from the University of Vechta, Germany. His research interests lie in geohazard databases, landslide risk assessment, and urban planning. Before working on a national landslide database project for Germany, he had been affiliated with the University of Göttingen, Germany. Martin Klose was visiting scientist and student assistant at the U.S. Geological Survey, Potsdam Institute for Climate Impact Research, and Department of Remote Sensing at the University of Würzburg in cooperation with the German Aerospace Center (DLR). He holds a diploma degree in Geography from the University of Würzburg, Germany.
This doctoral thesis presents a novel approach to landslide risk assessment that explores the various dimensions of landslide risk in an integrated perspective. The research approach introduced here is tailored for use with landslide databases and Geographic Information Systems (GIS). A landslide susceptibility model is at the heart of this new approach, enabling to identify and delineate areas at risk of landslides and to assess infrastructure exposure. Landslide risk is a pressing societal issue that is still poorly understood. Temporal landslide hazard is derived from landslide frequency statistics and a hydrological simulation approach to estimate triggering thresholds. These methods are integrated into a powerful toolset for cost modeling that uses historical data to compile, model, and extrapolate damage costs on different spatial scales over time. The combination of this toolset with techniques to analyze fiscal cost impacts supports integrated risk assessment by quantifying the economic relevance of landslide losses.
Nominated as an outstanding Ph.D. thesis by the University of Vechta, Germany
Introduction.- Landslide DatabasesState of Research and the Case of Germany.- Study Area.- Methodology.- Results.- SynthesisTowards Integrated Assessment of Landslide Risk.