Prediction of Landslide Susceptibility Using Bivariate Models

  • Sujit MandalEmail author
  • Subrata Mondal
Part of the Environmental Science and Engineering book series (ESE)


The present study is dealt with the application of Information value model (IVM), landslide nominal risk factor mode (LNRFM), fuzzy logic approach (FLA) and statistical index model (SIM) and the preparation of landslide susceptibility maps of the Balason river basin of Darjeeling Himalaya using various geomorphic, hydrologic, and tectonic attributes such as elevation, slope, aspect, curvature, geology, geomorphology, soil, distance to lineament, lineament density, drainage density, distance to drainage, stream power index (SPI), topographic wetness index (TWI), land use and land cover (LULC) and NDVU. All the landslide conditioning factors were being processed in GIS platform. The prepared landslide susceptibility maps were also validated using ROC curve which stated that fuzzy logic approach is best suited for developing landslide susceptibility zonation map of the Balason river basin of Darjeeling Himalaya.


Bivariate models Landslide susceptibility ROC curve Model validation Landslide susceptibility Balason river basin 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of GeographyDiamond Harbour Women’s UniversityDiamond HarbourIndia
  2. 2.Bajitpur High SchoolGangarampurIndia

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