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

Abstract

The Sikkim state, including Gangtok, is dominated by Precambrian rocks which contain foliated schists and phyllites; slopes are therefore susceptible to frequent landslides. The recent development of roads and building structures make this region more vulnerable to landslide hazard. In this research work, landslide susceptibility zonation mapping within Gangtok Municipal Corporation (GMC) area have been carried out implementing remote sensing and GIS technique. To derive the landslide susceptibility map (LSM) of GMC, weighted overlay method (WOM) was implemented by assigning weights to various triggering factors via expert opinion. The twelve triggering factors used in the study were 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). The final LSM of GMC shows that about 19.14% of the study area falls under very high landslide hazard zone and 31.78% area falls under the high category. Medium and low landslide hazard zone encompasses about 30.95% and 18.11 % of the total area, respectively. The model-generated LSM is validated with past reported landslide event where an overall accuracy of above 80% is observed.

Keywords

• Landslide susceptibility zonation (LSZ)
• Gangtok city
• knowledge-driven method
• validation