Fuzzy gamma operator model for preparing landslide susceptibility zonation mapping in parts of Kohima Town, Nagaland, India

Abstract

Growing population and expansion of settlements over hilly areas have largely increased the impact of landslide. This paper deals with the use of Geoinformatics technology and Fuzzy Gamma Operator model to map the landslide susceptibility zones in part of Kohima Town, Nagaland. For this study, eight landslide inducing parameters such as slope gradient, slope aspect, curvature, elevation, land use and land cover, drainage density, lineament density, and topographical wetness index were considered and prepared with the help of toposheet, high resolution satellite imagery such as World View II, LISS IV, DEM data and field data. Landslide inventory was the first step for the geospatial database generation which involves the mapping of past landslide details. Landslide susceptibility maps were generated by calculating relationship between the landslide inducing factors with past landslide locations using frequency ratio and fuzzy gamma operator model. The ratios were normalized between the range of 0 and 1 to obtain fuzzy membership values. The landslide susceptibility zonation (LSZ) map were prepared by integrating all the causative factors with fuzzy membership values and classified into five different susceptibility classes based on Jenks natural breaks classification viz. very high (37.51%), high (32.21%), moderate (20.97%), low (7.97%), and very low (1.34%). The LSZ map were compared with the landslide inventory map and validated with best prediction accuracy using area under curve (AUC) with the accuracy level and R-Index.