Raster-based landslide susceptibility mapping using compensatory MADM methods

Abstract

Landslide Susceptibility Maps (LSMs) are among the essential layers for landslide risk management in landslide-prone regions. This study proposes raster-based landslide susceptibility mapping using widely used compensatory Multi-Attribute Decision Making (MADM) methods, including AHP-SAW, AHP-TOPSIS, and AHP-VIKOR in the Razmian region, Iran. The results showed that the range of Area Under the Curve (AUC) values varied from 0.793 to 0.833. Therefore, all LSMs derived from the compensatory MADM methods are within the acceptable and excellent acceptance range, so the accuracy of MADM methods is acceptable for TOPSIS and VIKOR (V = 0.0) and excellent for other methods. Validation results also showed that VIKOR0.7 is the best method to produce the LSM based on the Quality Sum (Qs) index and AUC values. In general, pixel-based landslide susceptibility mapping using compensatory MADM methods in combination with the group decision-making approach in AHP is recommended for landslide risk management and land-use planning.