In 2018, the Chinese government unveiled a comprehensive set of policies outlining the blueprint for rural revitalization, promoting the idea of “boosting rural revitalization through green development”. Using provincial panel data from 2011 to 2021, this study explores the impact of green development on rural revitalization, and the spatiotemporal and network evolution characteristics of this influence. Each region’s green development and rural revitalization levels are measured using the composite weighting method. Next, it explores the spatial characteristics of green development’s influence on rural revitalization by using spatial Durbin model. It further explores the heterogeneity of the spatial spillover effect of green development on rural revitalization using a two-regime spatial Durbin model. Lastly, it combines the complex network correlation method to identify important provinces.

Urban-rural integration is a significant driving force in promoting regional balance, optimizing the allocation of social resources, and achieving high-quality economic development. The study investigates the spatial-temporal evolution and influencing factors of urban-rural integration in Zhejiang from 2003 to 2022 based on four dimensions of “economy-society-space-ecology”. The research has found that: Firstly, the overall level of urban-rural integration in Zhejiang is on the rise with certain disparities. Secondly, the integration of urban and rural areas in Zhejiang exhibits a clear clustering phenomenon, presenting a spatial characteristic of “higher in the northeast and lower in the southwest”. Subsequently, per capita GDP, the advancement of the digital economy, the adjustment of industrial structure as well as the proportion of financial support dedicated to agriculture and urban-rural community affairs have played positive roles in promoting the process of urban-rural integration by influencing the flow of resources and factors between urban and rural areas. Accordingly, to further promote urban-rural integration, it is imperative to fully utilize leading cities to drive regional development, bolster the revitalization of mountainous regions and islands, accelerate the adjustment and upgrading of industrial structures, promote the growth of the digital economy, as well as refine the structure of government financial expenditures. This integrated approach will ultimately create a new paradigm of urban-rural integration.

Studying residency satisfaction is essential for designing optimal social spaces in ethnic villages, with villagers as the primary focus. This study analyzed data from 941 villagers across 21 typical ethnic villages in the Xiangxi Region to identify key factors influencing their satisfaction with their living environment. Using eight machine learning techniques—Logistic Regression (OneVsOne), SVM, AdaBoost, Random Forest, XGBoost, CatBoost, LightGBM, and Stacking—we sequentially develop prediction models for three dimensions of socio-spatial satisfaction categorization (Material bears, Behavioral activities, Institutional beliefs) in multi-category villages (Agriculture-leading, Historical and cultural, Leisure tourism). These models are then combined with SHAP for global interpretation analysis. Among these techniques, the Stacking model proved to be the most effective in predicting villagers’ satisfaction with their living conditions. Additionally, the study revealed a strong correlation between residents’ contentment and the specific socio-spatial attributes of their homes. This study offers a theoretical framework for designing efficient social spaces in ethnic villages in western Hunan and similar regions.

We apply a modified data envelopment analysis (DEA) model, spatial autocorrelation method, and geographic detector model to evaluate the resource conversion efficiency and its interaction mechanism in 81 red tourist attractions in Hunan Province in 2021. The results show that: (1) The overall conversion efficiency is 0.335, exhibiting high values in the east and low values in the west. (2) Next, both production and conversion efficiencies exhibit local spatial correlation, gradually decreasing from east to west. Accordingly, the efficiency types of Hunan province's red tourism resources can be divided into five types. (3) The strongest influencing factor was product innovation capability, followed by the quality of human capital, tourism market scale, policy support, traffic network conditions, and economic development level. Product innovation ability, human capital quality, and tourism market scale were three endogenous factors. Finally, we identified three interaction types of internal and external factors interaction type drove the spatial differentiation in conversion efficiency.

The travel agency network is a spatial organization that connects tourist flow between cities and scenic spots. Taking Wuxi City as the research object, the kernel density and service network measurement model were used to quantitatively evaluate the spatial evolution of the travel agency service network in Wuxi in 2005, 2010, 2015, and 2020. The results reveal that the “centripetal” spatial distribution of travel agencies is still strengthening. Liangxi District has always been a hot spot for travel agencies, but the development of peripheral hot spots is also accelerating. The evolution of the trends in how travel agencies operate in the three major sectors differs markedly. The hotspot network of travel agencies in the urban and Jiangyin sectors has developed rapidly, but the hotspot network of travel agencies in the Yixing sector has begun to emerge, albeit relatively slowly. Moreover, the focus of Wuxi’s tourism service network is the connection between urban areas. Notably, the network connection between urban areas and Jiangyin continues to strengthen. The travel agency service network between Jiangyin and Yixing has not yet been established, and the integrated service network of regional tourism still needs to be strengthened. From the aspects of tourism service market construction, the results of this study can guide business support capacity improvement and travel agency service innovation, as well as corresponding countermeasures and recommendations for Wuxi travel agency service network development.

The conservation renewal of historic districts is currently not effective due to insufficient public participation. Therefore, this study takes Dongguan Street in Dalian as an example and constructs a spatial environmental evaluation model for the historical district based on user perception. The Analytic Hierarchy Analysis (AHP) was used to determine the indicator weights, and a satisfaction survey was combined with the quadrant chart model method to analyze the discrepancies between the expert weights and user satisfaction. The results show that the overall satisfaction of the district reached a score of 80.43, but the key indicators such as participation and cultural experience showed characteristics of high weighting and low satisfaction. Accordingly, strategies such as the implantation of experiential businesses and cultural revitalization were proposed, and their effectiveness was verified through return visits. This study aims to provide multi-dimensional decision-making support for the conservation and renewal of historic districts, and to enhance the universality and accuracy of historic district design.