Application of a Hybrid Model in Landslide Susceptibility Evaluation of the Western Tibet Plateau

Abstract

The evaluation of landslide susceptibility plays a crucial role in preventing the risks associated with landslides and debris flows, providing valuable insights for the effective prevention and mitigation of geological hazards. However, there is limited research on high-altitude areas. Therefore, this study chose the western Tibetan Plateau as the study area, a representative area known for its susceptibility to landslides and high attitudes. In this study, seven factors were identified based on research objectives. Information value (IVM), weight of evidence (WOE), information value logistic regression (IVM-LR), weight of evidence logistic regression (WOE-LR), information value multi-layer perceptron (IVM-MLP) and weight of evidence multi-layer perceptron (WOE-MLP) were selected and compared for landslide susceptibility. The percentage of disaster area included in each risk level, the AUC value and the ROC curve were used to evaluate the accuracy of the results. The ROC curves of the results were close to the upper–left corner and the AUC values exceeded 0.85, an indication that all results were highly accurate. Moreover, the percentage of disaster area included for each risk showed an upward trend regarding susceptibility. The results indicated that the hybrid model exhibited superior performance in assessing landslide susceptibility at high altitudes. Overall, the results showed great significance regarding disaster prevention and mitigation measures of local governments.

Keywords

• information model
• weight of evidence
• logistic regression
• multi-layer perceptron
• landslide susceptibility