Landslide susceptibility maps are helpful tools to identify areas potentially prone to future landslide occurrence. As more and more national and provincial authorities demand for these maps to be computed and implemented in spatial planning strategies, several aspects of the quality of the landslide susceptibility model and the resulting classified map are of high interest. In this study of landslides in Lower Austria, we focus on the model form uncertainty to assess the quality of a flexible statistical modelling technique, the generalized additive model (GAM). The study area (15 850 km2 ) is divided into 16 modelling domains based on lithology classes. A model representing the entire study area is constructed by combining these models. The performances of the models are assessed using repeated k-fold cross-validation with spatial and random subsampling. This reflects the variability of performance estimates arising from sampling variation. Measures of spatial transferability and thematic consistency are applied to empirically assess model quality. We also analyse and visualize the implications of spatially varying prediction uncertainties regarding the susceptibility map classes by taking into account the confidence intervals of model predictions. The 95 % confidence limits fall within the same susceptibility class in 85 % of the study area. Overall, this study contributes to advancing open communication and assessment of model quality related to statistical landslide susceptibility models
Within lanslide early warning systems, a continuous challenge is the on-site implementation of a robust monitoring system, a reliable data collection and cross-checked analysis, and the presentation of respective results in a real-time mode. This paper will describe one concept of an integrated early warning system developed within the German BMBF-funded ILEWS project. This system is based on a variety of factors. The connection of geomorphological knowledge, geotechnical and geophysical information, sensor networks and web-based applications are examined. In the Swabian Albm one system has been installed and first results will be presented. These results give some indications of the potential of a real-time landslide early warning system ready to be used by various end-users and stakeholders.
Geoengineer.org uses third party cookies to improve our website and your experience when using it. To find out more about the cookies we use and how to delete them visit our Cookies page. Allow cookies