Knowledge-driven method: a tool for landslide susceptibility zonation (LSZ)

Abstract

ABSTRACT Gangtok, situated at the south-eastern part of the Sikkim state in India is the centre of the state’s administrative operations. Precambrian rocks comprising of foliated schists and phyllites are the major share of this city; slopes are therefore prone to regular landslides. There is a paradigm shift in disaster management policy of the city to emphasize disaster preparedness in order to ensure that human life and property are not harmed to the best possible. Apart from natural slope failure, now-a-days Gangtok city is more prone to frequent landslides as a result of recent road and building construction. Present research work deals with the development of Landslide susceptibility mapping (LSM) within the Gangtok Municipal Corporation (GMC) region by means of geospatial analysis. The weighted overlay method (WOM) is adopted for this purpose where, weights are assigned to various triggering factors based on expert opinion. Twelve triggering factors i.e., geology/lithology, slope morphometry, lineament density, water regime, rainfall, elevation, soil type, soil liquefaction, soil thickness, building density, relative relief, and land use/land covers (LULC) are considered for this analysis. Outcomes of LSM reveal that about 19 and 31 percent of the study area fall within very high and high susceptible zone respectively whereas, 30 and 18 percent of the city are categorized as medium to low susceptible categories respectively. The model generated LSM is further confirmed by using previous landslide events, yielding an overall accuracy of 80%.