Abstract

In Germany and Europe infrastructure managers are already undertaking massive efforts to reduce the risks and effects of mass movements on railway infrastructure. Supporting these efforts and adding the future perspective, we present the results of ongoing project developing a nationwide landslide susceptibility map along the German railway network."br" Mechanisms and parameter-interactions that trigger mass movements are complex and related to local conditions regarding, e.g. geology, topography, land use, and climate. In a first step, open source geodata sets, e.g. digital elevation models, geological maps, and digital landscape models were combined within two parallel approaches (i) geotechnical knowledge based, and (ii) artificial neural network (ANN), compared to each other and verified with documented landslide events. To access the future landslide geo-hazard potential along railways under the influence of climate change, the most promising landslide susceptibility map will be enhanced by integrating climate scenario data. Additionally, the resolution of the input datasets will be improved, systematically."br" The results obtained within this project will be integrated into the risk assessment tool that will be developed parallel within the BMVI Network of Experts and finally provide decision support to users across the railway sector.