Feature-based model for landslide susceptibility mapping using a multi-parametric decision-making technique and the analytic hierarchy process

Landslide events are responsible for substantial financial damages, human causality, and irreversible fluctuations in the natural landscape. This paper discusses and deals with landslide inventory mapping using a digital elevation model and a knowledge-based numerical rating scheme. In this study, we have used six different parameters affecting landslides such as a slope map, an aspect map, a curvature map, distance from the road and streamline, and elevation. The voids in the Digital Elevation Model (DEM) data were filled as a part of preprocessing. The Landslide Susceptible Maps (LSMs) and Landslide Hazards Zonation (LHZ) maps were developed by computing the correlation between the landslide-impacting factors with past landslide positions using the Analytic Hierarchy Process (AHP) technique. The AHP model is utilized to establish the weightage value for every parameter, and the summation of the product signifies the Landslide Susceptible Index (LSI) value for every pixel. Based on the derived LSI, the area under consideration was categorized into five susceptibility classes from very low to scars. The LSMs were confirmed and verified using prevailing landslide inventory records. The overall prediction accuracy of the AHP model is 90.91%. The susceptibility maps can be very helpful in the identification of the more troublesome areas, which is highly critical for studying landslide hazards, risk assessment and community, and regional planning.

Automated summary

This study focuses on the mapping of landslide inventory using a digital elevation model and an Analytic Hierarchy Process (AHP) technique, utilizing various parameters to develop Landslide Susceptible Maps and Landslide Hazards Zonation maps. The research demonstrates high prediction accuracy and highlights the importance of susceptibility maps in identifying troublesome areas for landslide hazards, risk assessment, and planning.