## 6 Conclusions  
1. A relatively perfect geological disaster evaluation index system was established, and the relationship between different geological factors and evaluation factors was analyzed on the basis of geological disaster environment analysis. Taking Tekes County as an example, nine evaluation factors such as elevation were selected, and the information quantity model was adopted to carry out the susceptibility evaluation. The landslide disaster susceptibility level of the county was classified into four levels: high susceptibility, medium susceptibility, low susceptibility and not susceptible. The area of high susceptibility area was 491.3276 km\({}^{2}\), the area of medium susceptibility area was 1181.5171 km\({}^{2}\), the area of low susceptibility area was 1674.7609 km\({}^{2}\), and the area of not susceptible area was 2295.2976 km\({}^{2}\), which accounted for 5.68%, 13.67%, 19.38%, and 13.67%, respectively, of the total area of Texaco County. The zoning has been well applied in the geological disaster zoning area, the deployment of prevention and control works, and the construction of disaster prevention and mitigation early warning systems in Tekes County. 2. In this study, the evaluation results were examined by ROC curve, and the results showed that the AUC of the evaluation results of the geological disaster susceptibility in Tekes County = 0.8736, that is, the evaluation accuracy is 87.36%, which indicates that the use of the information quantity model as the basis, the entropy method of calculating weights, and the final use of the weighted information quantity model for the evaluation of the susceptibility to landslides in Tekes County has good applicability. It can provide a certain reference value for the prevention and mitigation of geological disasters in the district. 3. Based on the method of combining the information quantity method and entropy value method with GIS technology, the evaluation of the susceptibility to geological disasters in Tekes County is more in line with the actual investigation, and the modeling methods have a certain degree of reliability and are able to accurately predict the occurrence of landslide geohazards, which greatly promotes the construction of quantitative spatial early warning of landslide hazards and provides scientific bases for the evaluation of the regional riskiness and for the prevention and mitigation of disasters and other work. At the same time, this research method provides a practical, simple, and highly accurate prediction method for evaluating the susceptibility of geological hazards in China and other countries. 4. The spatial prediction of landslide geological hazards is a complex nonlinear process, and improving the accuracy of the model is of great significance to the task of landslide prediction. Exploring the distribution characteristics of the evaluation factors helps to understand the mechanism of landslide occurrence and it is necessary to establish a better system of landslide evaluation factors to quantitatively express the importance of the evaluation factors while exploring a more reasonable and reliable landslide prediction model. **Author Contributions:** All authors contributed to the study's conception and design. Material preparation, data collection, and analysis were performed by [PERSON], B.W., Y.S., W.W., T.X., Q.L. and H.M. The first draft of the manuscript was written by [PERSON], and all authors commented on previous versions of the manuscript. All authors have read and agreed to the published version of the manuscript. **Funding:** This work was supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region (2022D01A239); Open Fund of Xinjiang Key Laboratory of Geological Hazard Prevention and Control. **Data Availability Statement:** The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.