Geospatial Multi-criteria Assessment with Fuzzy-AHP for Landslide Susceptibility Mapping in Almora District, India

Landslides pose significant hazards to human lives, infrastructure, and the environment, necessitating accurate susceptibility mapping for effective risk mitigation strategies. The Almora district in the Uttarakhand state of India faces significant susceptibility to landslides due to a combination of geological, climatic, and anthropogenic factors. This research focuses on the development of a comprehensive landslide susceptibility map using a spatial multicriteria approach integrated with Geographic Information Systems (GIS). Ten factors influencing landslide occurrence, including lithology, geomorphology, land cover, proximity to roads, lineaments, and drainage, elevation, aspect, rainfall, and slope, were analyzed. The Fuzzy Analytical Hierarchy Process (Fuzzy-AHP) was employed to assign weights to these factors based on their impact on landslide occurrence. The results indicate that 9.72% of the study area is at very low risk, 47.66% at low risk, 34.29% at moderate risk, 7.81% at high risk, and 0.49% at very high risk. High susceptibility to landslides is primarily observed in elevated regions, particularly along steep river valleys. Additionally, the validity of the susceptibility map was assessed using the Area Under the Curve (AUC) in the Receiver Operating Characteristic (ROC) curve, yielding a satisfactory outcome of 84.9%. This study provides valuable insights for land-use planning and disaster mitigation efforts in landslide-prone areas of the Almora district.