Knowledge-Driven Statistical Approach for Landslide Susceptibility Assessment Using GIS and Fuzzy Logic (FL) Approach
The present study is dealt with the application of fuzzy logic and preparation of landslide susceptibility zonation map of Darjeeling Himalaya on GIS environment. To accomplish fuzzy logic, several data layers such as elevation, slope, aspect, curvature, drainage density, distance to drainage, lineament density, distance to lineament, lithology, land use and land cover, soil, stream power index (SPI), topographic wetness index (TWI), and rainfall were made in consultation with topographical map, Google earth images, satellite imageries, and some other authorized maps. For computing fuzzy membership value and developing the model frequency ratio and cosine amplitude, values were derived corresponding to each class of the landslide causative factor. Then, fuzzy gamma operator value of 0.975 was used to prepare landslide susceptibility zonation map of Darjeeling Himalaya considering frequency ratio and cosine amplitude membership value. The accuracy study based on ROC curve revealed that the FR membership value based fuzzy gamma operator and landslide susceptibility map having the accuracy result of 80.9% and cosine amplitude membership value based landslide susceptibility having the validation result of 67.9%.
KeywordsLandslide susceptibility Frequency ratio Cosine amplitude Fuzzy membership value Fuzzy gamma operator value
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