Integrating AHP and Remote Sensing Method for Landslide Susceptibility Mapping of the Coastal Cliffs in Southeastern Bangladesh

Abstract

The study focused on the southeastern part of Bangladesh from Cox’s Bazar to Teknaf, integrating the Analytical Hierarchy Process (AHP) and Remote Sensing (RS) techniques to develop a landslide susceptibility map. Ten conditioning factors—elevation, slope, aspect, curvature, soil type, land use/land cover, rainfall, drainage density, distance from road, and normalized difference vegetation index were produced from satellite imagery and secondary datasets. Analytical Hierarchy Process (AHP) was used to derive factor weights through pairwise comparison to evaluate susceptibility zonation. The resulting susceptibility map classified the area into 3 zones: low risk (35.34%), moderate risk (62.25%), high risk (2.40%) susceptibility. The findings highlight critical hotspots at Teknaf Upazila and moderate hotspot at the rest of Teknaf and Ukhia including the marine drive of coastal cliffs where mitigation and land-use planning should be prioritized. This integrated RS-AHP framework offers a cost-effective and scalable approach for hazard assessment in data-scarce regions like Bangladesh.