Application and verification of fuzzy algebraic operators to landslide susceptibility mapping

Abstract

The aim of this study was to apply and to verify the use of fuzzy logic to landslide susceptibility mapping in the Gangneung area, Korea, using a geographic information system (GIS). For this aim, in the study, a data-derived model (frequency ratio) and a knowledge-derived model (fuzzy operator) were combined. Landslide locations were identified by changing the detection technique of KOMPSAT-1 images and checked by field studies. For landslide susceptibility mapping, maps of the topography, lineaments, soil, forest, and land cover were extracted from the spatial data sets, and the eight factors influencing landslide occurrence were obtained from the database. Using the factors and the identified landslide, the fuzzy membership values were calculated. Then fuzzy algebraic operators were applied to the fuzzy membership values for landslide susceptibility mapping. Finally, the produced map was verified by comparing with existing landslide locations for calculating prediction accuracy. Among the fuzzy operators, in the case in which the gamma operator (λ = 0.975) showed the best accuracy (84.68%) while the case in which the fuzzy or operator was applied showed the worst accuracy (66.50%).