Evaluating the Sustainable Development of Red Cultural Tourism in Yunnan, China, Using GIS and Machine Learning Methods

Against the backdrop of the accelerated integration of culture and tourism in China, red cultural tourism, as an important component of China’s cultural tourism system, urgently requires a systematic assessment of its development status and synergistic impact mechanisms. This study takes the Long March tourism resources in Yunnan as the research object and constructs a comprehensive evaluation system integrating social influence and ecological carrying capacity. By applying GIS spatial analysis, as well as K-means and XGBoost machine learning models, the development level of red cultural tourism in Yunnan is quantitatively assessed. Furthermore, the interpretable SHAP model is employed to identify the contribution of each evaluation indicator and to analyze the relationships among development levels under three different indicator models. The results reveal that (1) the development level of red cultural tourism in Yunnan generally exhibits a spatial pattern of being lower in the northwest and higher in the southeast; (2) transportation accessibility (TA), average annual precipitation (AAP), and average annual temperature (AAT) are the dominant indicators influencing the development level; (3) there are significant disparities in development levels among cities, indicating that future development needs to comprehensively consider both the social influence and ecological carrying capacity of red cultural tourism resources and adhere to a “social–ecological” synergistic development mechanism. This study not only uncovers the synergistic impacts of social and ecological dimensions on the development of red cultural tourism in Yunnan but also provides theoretical and data support for the optimization and sustainable development of Yunnan’s red cultural tourism resources.