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Evaluating the risk of landslides to implement preventative measures and aid in development planning is crucial, particularly in regions prone to such occurrences. Employing a landslide susceptibility map proves beneficial in managing land in landslide-prone zones. In this research, we introduce a GIS technology-based approach along with the multi-criteria analysis (MCA) method, incorporating the analytical hierarchy process (AHP) to determine optimal weight allocation for the criteria influencing landslide risk and compute landslide risk assessment indices. Eight criteria affecting landslide risk were chosen from publicly available data sources on the internet: elevation, slope, terrain moisture index (TWI), precipitation, land cover, normalized difference vegetation index (NDVI), soil type, and drainage density. Subsequently, overlaying simple maps facilitated the calculation of the Landslide Susceptibility Index (LSI), leading to the partitioning of the study area into five levels of landslide risk: very high, high, medium, average, low, and very low, covering approximately 8.6%, 24.3%, 32.0%, 23.9%, and 11.2% of the study area, respectively.
Van et al. (Mon,) studied this question.