Spatial Risk Assessment of the Effects of Obstacle Factors on Areas at High Risk of Geological Disasters in the Hengduan Mountains, China

The Hengduan Mountains in China are known for their complex geological environment, which leads to frequent geological disasters that pose significant threats to the safety and economic and social development of the local population. In this study, we developed develop a multi-dimensional evaluation index system from the aspects of economy, society, ecology, and infrastructure, and the resilience inference measurement (RIM) model was developed to assess resilience to regional disasters. The clustering evaluation of exposure, damage, and recovery variables in four states was conducted by way of K-means clustering. The results of K-means clustering are confirmed by discriminant analysis, and the disaster resilience index was empirically verified once. At the same time, the obstacle factor was further analyzed with the obstacle degree model. The results indicate that there are 8 susceptible areas, 23 recovering areas, 27 resistant areas, and 7 usurper areas. The classification accuracy of the model is 95.4%. The disaster resilience of high-risk areas was found to be low, with “extremely poor” differentiation, where the majority of the areas had low resilience and only a minority had high resilience. A “high in the southeast and low in the northwest” spatial distribution was observed. High-resilience areas were “dotted” and mainly concentrated in core areas with a high population density and strong economic activity, while low-resilience areas had a pattern of “edge extension” and were mainly distributed in the transition zone between the Qinghai–Tibet and Yunnan Plateaus. There were clear differences in the barriers of disaster resilience among the 65 counties (cities). The economic barrier degree was found to be the largest barrier to disaster resilience, followed by ecological, social, and infrastructure barrier degrees. The main factors affecting the distribution of disaster resilience in the high-risk areas were topographic relief, proportion of female population, cultivated land area, industrial structure, number of industrial enterprises above a designated size, and drainage pipeline density in the built-up area. Additionally, primary barrier factors classify the 65 counties (cities) into three types: economic constraint, natural environment constraint, and population structure constraint.