Landslide Susceptibility Mapping for Austria Using Geons and Optimization with the Dempster-Shafer Theory

• Published in: Applied sciences 2019-12, Vol.9 (24), p.5393
• Main Authors: Gudiyangada Nachappa, Thimmaiah, Tavakkoli Piralilou, Sepideh, Ghorbanzadeh, Omid, Shahabi, Hejar, Blaschke, Thomas
• Format: Article
• Language: English
• Subjects: Classification; Geographic information systems; Geomorphology; Infrastructure; Land cover; Land use; Landslides; Landslides & mudslides; Lithology; Mapping; Model accuracy; Optimization; Rainfall; Susceptibility
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app9245393

Landslide susceptibility mapping (LSM) can serve as a basis for analyzing and assessing the degree of landslide susceptibility in a region. This study uses the object-based geons aggregation model to map landslide susceptibility for all of Austria and evaluates whether an additional implementation of the Dempster–Shafer theory (DST) could improve the results. For the whole of Austria, we used nine conditioning factors: elevation, slope, aspect, land cover, rainfall, distance to drainage, distance to faults, distance to roads, and lithology, and assessed the performance and accuracy of the model using the area under the curve (AUC) for the receiver operating characteristics (ROC). We used three scale parameters for the geons model to evaluate the impact of the scale parameter on the performance of LSM. The results were similar for the three scale parameters. Applying the Dempster–Shafer theory could significantly improve the results of the object-based geons model. The accuracy of the DST-derived LSM for Austria improved and the respective AUC value increased from 0.84 to 0.93. The resulting LSMs from the geons model provide meaningful units independent of administrative boundaries, which can be beneficial to planners and policymakers.