Modelling Landslide Susceptibility for a Large Geographical Area Using Weights of Evidence in Lower Austria, Austria

Abstract

Knowledge of the spatial distribution of landslide susceptibility supports and enhances decision-making involved in land-use planning for mitigating the impacts of landslide hazards. Our study focuses on the application of the weights of evidence (WOE) method to statistically model landslide susceptibility for a large area in the Austrian province of Lower Austria. Approximately 16,000 km² was modelled with a 10 m × 10 m spatial resolution. To complete this task, a new implementation of WOE in R was developed, a free open source software for statistical computing, to handle the computation of weights for large geospatial datasets. Furthermore, the challenge of modelling diverse landslide conditions for a large area was addressed by modelling WOE separately for each lithology unit. The final susceptibility map was compiled by mosaicking these models. The performances of the models were estimated with a repeated cross-validation approach that measured the area under the receiver operating characteristic curve (AUROC). The results showed good WOE model performances; the median AUROC values ranged from 73 to 93 %, with an average performance of 86 % for the entire study area. Also, this study demonstrated the successful application of WOE for a large geographic area with a high spatial resolution.