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Landslides

, Volume 13, Issue 2, pp 379–397 | Cite as

Applying weight of evidence method and sensitivity analysis to produce a landslide susceptibility map

  • Ioanna IliaEmail author
  • Paraskevas Tsangaratos
Original Paper

Abstract

The main purpose of this study is to define the main variables that contribute to the occurrence of landslides in Kimi, Euboea, Greece, and to produce a landslide susceptibility map using the weight of evidence method. For the developed model, a sensitivity analysis is carried out in order to understand the model’s behavior when small changes are introduced in the weight value of the landslide-related variables. Landslide locations were identified from field surveys and interpretation of aerial photographs which resulted in the construction of an inventory map with 132 landslide events, while eight contributing variables were identified and exploited. All landslide-related variables were converted into a 5 × 5-m float-type raster file. These input-raster layers included a lithological unit layer, an elevation layer, a slope angle layer, a slope aspect layer, a distance from tectonic features layer, a distance from hydrographic network layer, a topographic wetness index layer, and a curvature layer. The validation of the developed model was achieved by using a subset of unprocessed landslide data, showing a satisfactory agreement between the expected and existing landslide susceptibility level, with the area under the predictive rate curve estimated to be 0.808. The area under the success rate curve was estimated to be 0.828 indicating a very high classification rate for existing landslide areas. According to the results of the sensitivity analysis, the lithological unit “yellowish gray to white marls” was the most sensitive as it had the highest change in the relative frequency of observed landslides. The overall outcomes of the performed analysis provide crucial knowledge in successful land use planning and management practice and also in risk reduction projects.

Keywords

Weight of evidence Landslide susceptibility Sensitivity analysis GIS 

Notes

Acknowledgments

The authors would like to thank the Editorial Office of Landslides Journal for editorial handling and also two anonymous reviewers for their helpful comments and suggestions that improved in quality the previous version of the manuscript.

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© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of Geological Studies, School of Mining and Metallurgical EngineeringNational Technical University of AthensZografouGreece

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