Hazard Vulnerability and Risk Analysis In Landslide Prone Areas Of Kohima Town Nagaland Using Geospatial Technology

Abstract

newlineLandslide risk is commonly defined as a function of landslide hazard and vulnerability newline indicators at risk such as physical and demography with attributed damage potentials with a newline defined magnitude. Vulnerability estimation is an important part of this assessment; a newline literature review demonstrates a lack of different vulnerability studies in landslides risk newline research with regard to physical and demography. These approaches determine the risk newline associated with landslides processes of a given magnitude and are applied in regional newline landslide risk analyses in Kohima Town of Nagaland. Landslide inventory was the first step newline which includes the mapping of landslide details of part of the study area. In order to assess newline the landslides susceptibility, a total of eight landslide inducing parameters; slope gradient, newline slope aspect, curvature, elevation, lithology, land use and land cover, drainage density, newline lineament density and topographic wetness index were considered and prepared with the help newline of toposheet, high resolution satellite imagery namely WorldView II, LISS IV data and newline extensive fieldwork. Landslide susceptibility maps were generated by calculating the newline relationship between all landslide inducing factors with the inventory and was classified into newline five susceptibility classes based on Jenks natural breaks classification namely very low, low, newline moderate, high and very high. There are four objectives in this research study; firstly to create newline the landslide inventory based on the available government data, published article, news newline reports, and extensive fieldwork; the second objective is to prepare a landslide susceptibility newline zonation using four different model Frequency Ratio (FR), Fuzzy Gamm Operators (FGO), newline Analytical Hierarchy Process (AHP) and Statistical Index (SI) and validation using Area newline under Curve (AUC) and R-Index method to check the accuracy and consistency of the newline models. The third objective is to create the physical and demographic vulnerability thematic newline maps with the help of populatio