Application of Analytical Hierarchy Process (AHP) and Frequency Ratio (FR) Model in Assessing Landslide Susceptibility and Risk

Abstract

To prepare landslide susceptibility map of the Shivkhola watershed, one of the landslide prone part of Darjiling Himalaya, RS and GIS tools were being used to integrate 10 landslide triggering parameters like lithology, slope angle, slope aspect, slope curvature, drainage density, lineament, upslope contributing area (UCA), road contributing area (RCA) settlement density, and land use and land cover (LULC). Analytical Hierarchy Process (AHP) was applied to quantify all the factors by estimating factors weight on MATLAB Software with reasonable consistency ratio (CR). Frequency ratio model (FR) was used to derive class frequency ratio or class weight incorporating both pixels with and without landslides and to determine the relative importance of individual classes. All the required data layers were prepared in consultation with SOI Topo-sheet (78B/5), LIIS-III Satellite Image (2010) by using Erdas Imagine 8.5, PCI Geomatica, and ARC GIS Software. The weighted linear combination (WLC) method was followed to combine factors weight and class weight and to determine the landslide susceptibility coefficient value (LSCV or ‘M’) on GIS platform. Greater the value of ‘M’, higher is the susceptibility of landslide. The Shivkhola watershed was classified into five landslide susceptibility zones by averaging window lengths of 3, 5, 7, and 9 and taking into account the landslide threshold boundaries value of 7.05, 9.29, 11.5, and 13.8. The overall classification accuracy rate is 92.22 % and overall Kappa statistics is 0.894. The elements like weighted LULC map, RCA (road contributing area) map and settlement density map were developed and their weighted linear combination was performed to prepare landslide risk exposure map. Then by integrating landslide susceptibility map and landslide risk exposure map landslide hazard risk co-efficient values were derived and a classification was incorporated on ARC GIS Platform to prepare landslide hazard risk map of the Shivkhola watershed. To evaluate the validity of the landslide hazard risk map, probability/chance of landslide hazard risk event has been estimated by means of frequency ratio (FR) between landslide hazard risk area (%) and number of risk events (%) for each landslide hazard risk class. Finally, an accuracy assessment was made through a comparative study between true GPS derived data and a set of randomly selected pixels points from the classified image corresponding to the true data from 50 locations on ERDAS Imagine (8.5) which depicts that the classification accuracy of the landslide hazard risk map was 92.89 with overall Kappa statistics of 0.8929.