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Open AccessArticle

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

1
Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria
2
Department of Remote Sensing and GIS, University of Tabriz, Tabriz 5166616471, Iran
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(24), 5393; https://doi.org/10.3390/app9245393
Received: 31 October 2019 / Revised: 26 November 2019 / Accepted: 6 December 2019 / Published: 10 December 2019
(This article belongs to the Special Issue Mapping and Monitoring of Geohazards)
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. View Full-Text
Keywords: landslide susceptibility mapping; geons; Dempster–Shafer theory; object-based; natural hazards landslide susceptibility mapping; geons; Dempster–Shafer theory; object-based; natural hazards
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MDPI and ACS Style

Gudiyangada Nachappa, T.; Tavakkoli Piralilou, S.; Ghorbanzadeh, O.; Shahabi, H.; Blaschke, T. Landslide Susceptibility Mapping for Austria Using Geons and Optimization with the Dempster-Shafer Theory. Appl. Sci. 2019, 9, 5393.

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