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http://dx.doi.org/10.9719/EEG.2017.50.3.239

Physically Based Landslide Susceptibility Analysis Using a Fuzzy Monte Carlo Simulation in Sangju Area, Gyeongsangbuk-Do  

Jang, Jung Yoon (Dept. of Geoinformation Engineering, Sejong University)
Park, Hyuck Jin (Dept. of Geoinformation Engineering, Sejong University)
Publication Information
Economic and Environmental Geology / v.50, no.3, 2017 , pp. 239-250 More about this Journal
Abstract
Physically based landslide susceptibility analysis has been recognized as an effective analysis method because it can consider the mechanism of landslide occurrence. The physically based analysis used the slope geometry and geotechnical properties of slope materials as input. However, when the physically based approach is adopted in regional scale area, the uncertainties were involved in the analysis procedure due to spatial variation and complex geological conditions, which causes inaccurate analysis results. Therefore, probabilistic method have been used to quantify these uncertainties. However, the uncertainties caused by lack of information are not dealt with the probabilistic analysis. Therefore, fuzzy set theory was adopted in this study because the fuzzy set theory is more effective to deal with uncertainties caused by lack of information. In addition, the vertex method and Monte Carlo simulation are coupled with the fuzzy approach. The proposed approach was used to evaluate the landslide susceptibility for a regional study area. In order to compare the analysis results of the proposed approach, Monte Carlo simulation as the probabilistic analysis and the deterministic analysis are used to analyze the landslide susceptibility for same study area. We found that Fuzzy Monte Carlo simulation showed the better prediction accuracy than the probabilistic analysis and the deterministic analysis.
Keywords
uncertainty; Monte Carlo simulation; Fuzzy Monte Carlo simulation; fuzzy set theory;
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