Evaluation of landslide susceptibility based on the fuzzy frequency ratio and entropy index: a case study of Chongyi county

To further optimize landslide susceptibility evaluation based on the frequency ratio model, a landslide susceptibility evaluation model based on the fuzzy frequency ratio-entropy index was constructed. The basic principle and method of fuzzy information distribution were applied to the calculation of the frequency ratio. This method optimized the statistics of landslide information based on the classification of landslide susceptibility influencing factors and put forward the calculation method of the fuzzy frequency ratio. On this basis, a landslide susceptibility evaluation model combining the fuzzy frequency ratio and entropy index was established. Taking Chongyi county as a case study, and based on the systematic analysis of the geological environment and spatial distribution characteristics of landslides, 11 landslide evaluation factors were extracted, and the landslide susceptibility evaluation index system was constructed. The application results showed that the prediction accuracy of this model was 7.5% higher than that of the single model and 3.6% higher than that of the frequency ratio-entropy index model. The proportion of landslide frequency in high and extremely high-prone areas could reach 85.98%. The AUC value of the predicted success curve reached 0.8637. All this implied that the evaluation model without fuzzy frequency ratio optimization was better, indicating that it was an effective and reliable landslide-prone evaluation model.