China is actively promoting the construction of clean energy to reach its objective of achieving carbon neutrality. However, engineering constructions in mountainous regions are susceptible to landslide disasters. Therefore, the assessment of landslide disaster susceptibility is indispensable for disaster prevention and risk management in construction projects. In this context, the present study involved conducting a field survey at 42 landslide points in the selected planned site region. According to the geological and geographical conditions of the study region, the existing regulation, and the influencing factors of landslides, the assessment in the field survey was performed based on 11 impact factors, namely, the slope, slope aspect, curvature, relative relief, NDVI, road, river, fault, lithology, the density of the landslide points, and the land-use type. Next, based on their respective influences, these impact factors were further divided into subfactors according to AHP, and the weights of each factor and subfactor were calculated. The GIS tools were employed for linear combination calculation and interval division, and accordingly, a landslide susceptibility zone map was constructed. The ROC curve was adopted to test the partition evaluation results, and the AUC value was determined to be 0.845, which indicated the high accuracy of the partition evaluation results.

The determination of the sustainable development of a region requires estimating its carrying capacity in terms of resources and environment. It is essential to investigate the carrying capacity of Kunming City to comprehend its rapid development and create a resource and environment-friendly society. This research involved the selection of a set of 35 evaluation indicators from three categories: resources, environment, and social economy. These indicators were chosen based on statistical data obtained from Kunming City between 2011 and 2020. An evaluation system was established using the entropy weight method to determine the weight of these indicators. Subsequently, the fuzzy matter–element analysis method was utilized to construct the European closeness model of Kunming’s resource and environmental carrying capacity. The correlation between the carrying capacity of resources and environment and sub-carrying capacities was analyzed using Pearson’s correlation coefficient to determine the degree of influence of different aspects on the carrying capacity of resources and environment in Kunming. The results show a consistent upward trend in the carrying capacity of resources and environment in Kunming City from 2011 to 2019. However, in 2020, due to national policy adjustments and the impact of COVID-19 on the social economy, the resource and environment carrying capacity index in Kunming City slightly decreased.