Landslide Susceptibility Assessment Analysis based on IV and IV-IOE Models: A Case Study of Mao County

Taking Mao County as the study area, and based on existing data combined with the characteristics of landslide development in the study area, six evaluation factors including elevation, slope gradient, aspect, land use, NDVI (Normalized Difference Vegetation Index), and rainfall were selected. An independence test was conducted using Pearson correlation analysis to establish an evaluation index system for landslide disaster susceptibility. The study on the susceptibility of landslide geological disasters was carried out using both the Information Quantity Model and the Information Quantity-Entropy Index Model. The evaluation results were divided into five levels—extremely low, low, medium, high, and very high—using the natural break method based on GIS. The susceptibility of landslide geological disasters in the study area was clarified, and the accuracy was tested using the ROC curve. The experimental results show that the AUC values of the two evaluation models are 0.847 and 0.865, respectively, indicating that the Information Quantity-Entropy Index Model is superior to the Information Quantity Model and has stronger robustness in predicting the accuracy of landslide susceptibility.