The TOPSIS method: Figuring the landslide susceptibility using Excel and GIS

Abstract

The current study introduced Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to enhance landslide susceptibility. It determines the relative distance of each alternative from the ideal best and ideal worst value. The ArcGIS environment was used to prepare eleven landslide conditioning factors, while raster values were extracted for the decision matrix preparation. We utilized subjective expert judgment to create a weighted matrix that considers the roles of each conditioning component. In addition, a Euclidean distance was measured from each alternative to the ideal best and worst values. The relative closeness value (R_i) has been used to prepare the landslide susceptibility index by the inverse distance weighting (IDW) interpolation. Furthermore, the precision of the landslide susceptibility was justified by area under curve-receiver operating characteristic (AUC-ROC) which was 0.987. Hence, multi-criteria decision-making (MCDM) techniques like the TOPSIS method are very useful for natural hazard mapping.

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  The simplified TOPSIS approach described by Hwang and Yoon (1981) is applied in this study. The criteria have been categorized and assigned weights based on expert judgment and previously published material.
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  The TOPSIS approach and GIS integration has significantly enhanced the creation of a landslide susceptibility map for a sensitive area.
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  The method is easiest and suitable for short term operation research.