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A method for landslide susceptibility assessment integrating rough set and decision tree: A case study in Beichuan, China

Landslide susceptibility assessment is necessary for disaster management and safe planning in mountainous regions. In this paper, we have used rough set theory to select ten landslide-related factors (slope, aspect, elevation and so on) derived from maps of geology and remote sensing data, and produced landslide susceptibility map in Beichuan Country, Sichuan Province of China based on a model integrating C4.5 decision tree and m-branch smoothing. The performance of method was evaluated by receiver operation characteristic (ROC) curve and the area under the curve (AUC). The result shows that the above initial controlling factors are very important for landslide activity in study area. When the parameter value of m-branch smoothing was set as 14, the method can get the best prediction accuracy with AUC value of 87.16%. These results demonstrated the proposed method for landslide susceptibility assessment is quite effective and can be applied to more disaster assessment problems.