The mountainous areas in the western part of Sichuan Province are mostly Alpine Gorge regions with high mountains, steep slopes, complex topography and geomorphology, special climatic conditions, infertile soils, and fragile ecological environments. In this study, a geohazard risk assessment was carried out in the Alpine Gorge region to prevent geohazards from hindering socio-economic development, affecting the lives and safety of residents, and undermining sustainable development in the region. With the help of a geographic information system (GIS), the analysis of geohazard influence factors was carried out; eight indicators, such as elevation and slope aspect, were selected to construct the evaluation index system. Additionally, the time and space distribution pattern of each influence factor and geohazard was analyzed. Geologic hazards in the region are influenced mainly by precipitation and human engineering activities. The prediction and evaluation of geohazard risk in Jiulong County are based on the Information Value model (IV), the Logistic Regression model (LR), and the Random Forest model (RF). Comparing the Receiver operating characteristic (ROC) curves of the three models for the accuracy test, the results show that all three models are suitable for the Alpine Gorge region, and the Logistic Regression model has the highest accuracy. Based on the evaluation results, measures and countermeasures for geologic disaster prevention and mitigation are proposed in light of the reality of geologic disaster prevention and mitigation work in Jiulong County. The research results can guide the government’s disaster prevention and mitigation work, provide a scientific basis for formulating regional geologic disaster prevention and control strategies, and ultimately promote the region’s sustainable development.

Primary fractures significantly impacted the stability of surrounding rock in underground projects. Therefore, it is vital to find a solution for the problem of performing a non-destructive detection of rocks and extracting the internal three-dimensional (3D) data field of rocks for visualization analysis. To address this problem, this paper proposed a method of 3D reconstruction for complex cracks in deteriorated sandstone and developed a program based on MATLAB. This work carried out image recognition on the CT scan images of deteriorated sandstone, then implemented a surface reconstruction technique based on object cross-section information, a contour reconstruction technique based on object contour information, a point cloud reconstruction technique for extracting point cloud data of internal cracks in deteriorated sandstone, and a Graphical User Interface (GUI) control system that combines these three reconstruction techniques. The results showed that the 3D reconstruction techniques and the GUI control system proposed in this paper were capable of precisely marking the location of the cracks on a 3D coordinate system and accurately describing their shape with a vector. With only 10 CT scan images, the point cloud reconstruction technique constructed the digital core, and the digital core can quantitatively characterize the influence of primary fractures on the stability of surrounding rock. Additionally, the calculated results of the proposed method were very close to that of Avizo. This method realized the visualization and quantitative characterization of the internal structure of rocks and offered a model for analyzing the stress-fracture-seepage field change during excavation.