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Statistical approaches are routinely applied to analyze landslide processes from several perspectives. During the last decade, the growing accessibility of environmental data as well as an increasing availability of powerful open-source statistical software, such as R, has certainly enhanced the regional-scale analysis of landslide phenomena. For large areas, a considerable number of statistics-oriented research focuses on the mapping of landslide-prone zones use binary classification algorithms. The resulting landslide susceptibility maps are commonly regarded as a suitable information source for land management, civil protection, and further statistical analyses. The creation of a statistically based landslide susceptibility model demands for a multitude of crucial decisions. For instance, besides the selection of suitable explanatory variables or modeling algorithms, also aspects related to the spatial representation …