## 5 Results  
### Information Content Calculation  
Referring to the Technical Requirements for Geological Hazard Risk Survey and Evaluation of Townships (Streets) in Guangdong Province (1:10,000) (Trial), the classification criteria of evaluation factors in this study are based on a combination of multidisciplinary theories and empirical data. Terrain slope is classified using the natural breaks method and engineering experience thresholds, reflecting the nonlinear influence of slope gradient on landslide occurrence. Terrain aspect follows the standard geographic azimuth classification, incorporating the impact of water and heat differences between sunny and shady slopes on slope stability. Slope morphology is classified based on the theory of terrain curvature, quantifying the control of different curvatures on slope stress distribution. Terrain relief is related to structural activity intensity through elevation range and classified using the natural breaks method. Engineering geological rock groups are classified based on differences in lithological strength. The thickness of the cover layer is categorized according to geo-mechanical principles and borehole data, considering the threshold effects of thickness on slope stability. Vegetation coverage is quantified using NDVI remote sensing to reflect the slope protection effects of vegetation. Land use types are classified in relation to the intensity of human activity disturbance. Slope structure is categorized according to geological survey standards, based on the relationship between slope direction and stratum dip. The height of artificial cut slopes is evaluated using free-face failure models and validated by aerial survey data [37; 38]. The final quantified results are presented in Table 2.  
The evaluation factors are classified according to the aforementioned quantification standards of the evaluation indicators. Using the information value model method, the information value of each evaluation factor and its corresponding classification is calculated. The resulting information values are assigned to the classified indicator states, yielding the information value table for the slope-type geological disaster-susceptibility evaluation factors in Huangshi Town (Table 2). Based on the weights of the disaster-susceptibility evaluation factors mentioned above, these weights are assigned to the classified factor raster map. Using spatial overlay analysis tools, the total information value of the raster cells at each spatial location in Huangshi Town is calculated, generating the disaster-susceptibility evaluation-index map for Huangshi Town (Figure 5). The information value model is a spatial prediction model, and the landslide susceptibility zoning results it produces are also predictive. The quality of susceptibility evaluation directly determines the accuracy of subsequent hazard and risk assessments. Therefore, in order to ensure the reliability of risk assessment results, it is necessary to evaluate the accuracy of the susceptibility analysis. The Receiver Operating Characteristic (ROC) curve is employed to validate the model's predictive performance. The predicted susceptibility values are divided into several classes, and within each class, the cumulative area of susceptible zones and the actual landslide areas are calculated. In the context of landslide susceptibility assessment, the true positive rate (TPR) on the y-axis represents the proportion of actual landslide areas, while the false positive rate (FPR) on the x-axis indicates the proportion of predicted susceptible areas.