Identification of landslide-prone zones using a GIS-based multi-criteria decision analysis and region-growing algorithm in uncertain conditions

Landslides are considered to be one of the most significant natural hazards. Detection landslide-prone zones is an important phase in landslide hazard assessment and mitigation landslide-related losses. AHP as effective methods for GIS-based multi-criteria decision analysis increasingly being used susceptibility mapping. However, its weights have some degree uncertainty that interval comparison matrix (ICM) method can deal with this problem. The importance study propose number distance-based region-growing (IDRG) based on ICM identification Urmia lake basin, Iran. To assess capability proposed IDRG method, a map was produced using common AHP, too. generate maps, nine conditioning factors were determined both traditional pairwise matrices ICM. accuracy maps assessed through ROC (receiver operating curve) dataset known occurrences. results indicate improvement about 11% by identifying method. This achieved minimizing associated criteria ranking/weighting prone areas instead pixels. Finally, robustness demonstrated sensitivity analysis.