The premium effect of public service facilities on the housing market is a critical determinant of housing prices, leading to the competition of different social groups in the housing market and fueling spatial inequality. Taking Xi’an, China as a case in point, this study uses Geographic Information System (GIS) to describe the spatial distribution pattern of housing prices and urban public service facilities. Using the mixed geographically weighted regression model (MGWR) and the geographical detector model (GD), this study reveals the spatial effects of these facilities’ accessibility on housing prices. The results show that commercial and leisure facilities are spatially stationary, whereas a non-stationary effect is observed among those providing educational, medical, cultural, sport, and financial services. From the urban spatial resource allocation perspective, facilities meeting people’s basic needs, such as medical care and education, constitute the basic elements of housing price differentiation. When any two of these interact, a bivariate-enhanced effect emerges. The decisive interactive elements of housing price differentiation involve the facilities meeting people’s higher-level needs, such as leisure, culture, sports, and finance. When these interactive elements interact with other facilities, a non-linear enhancement effect is induced. This research is of practical value for improving people’s living quality, optimizing the spatial distribution of public service facilities, and eliminating urban spatial inequality.

Urban agglomerations (UAs) have become the urbanized “growth poles”, especially against the background of increasing population flow to cities. The spatial structure of UAs has been deemed the essential factor affecting regional function and sustainable development. Although there have been many meaningful studies on spatial structure changes in China, a systematically comparative work of UAs is still absent. Under this context, this paper examines the changing process of spatial structure in 20 Chinese UAs from monocentric to polycentric during the years 1992–2012 by using the night-time light data—an alternative to census data—and explores the major driving forces underlying the evolution. Our empirical results suggest that there is an obvious polycentric tendency of UAs, the spatial distribution pattern of which is not apparent. Panel regression models reveal that the economic level, the population size, the foreign direct investment (FDI), the human capital, and the transport infrastructure play significant positive roles in shaping the polycentric changing process, while the growth of the government expenditure does the opposite. Moreover, transport infrastructure and FDI are positively associated with polycentric spatial structure in mature UAs; on the contrary, they are negatively associated with it in the emerging UAs. Our study results have important policy implications for rapid Chinese urbanization—the policy whereby “China’s future urbanization development model is to limit the agglomeration of large cities while focusing on developing small and medium-sized cities” may be more efficient in mature UAs.

Against the backdrop of consolidating the achievements of poverty alleviation and promoting rural revitalization, whether digital village construction can alleviate the risk of rural families returning to poverty and then help long-term poverty prevention needs systematic and scientific empirical investigation. Using data from the 2020 China Rural Revitalization Survey (CRRS), this paper analyzes the impact of digital village construction on rural household poverty vulnerability and explores its potential channels. The results show that (1) digital village construction can significantly alleviate the poverty vulnerability of rural households. (2) Improving entrepreneurial activity is an effective way for digital village construction to affect the risk of rural households returning to poverty. (3) Digital village construction has a greater effect on reducing the poverty vulnerability of households in the eastern and the plains regions, and it is necessary to be vigilant against the emergence of the “digital divide”. Based on these findings, this paper proposes policy recommendations to prevent the risk of rural areas returning to poverty through digital village construction, which achieves sustainable poverty reduction and rural revitalization goals.

The urban agglomerations in the Yellow River Basin are important carriers for China’s high-quality development. It is an inevitable trend to promote sustainable development and people’s well-being in the urban agglomerations of the Yellow River Basin. A case study of 70 cities of seven urban agglomerations in the Yellow River Basin from 2011 to 2017 is presented. The two-stage super-efficiency network slacks-based measure (Super-NSBM) model considering undesirable outputs is adopted to measure the ecological well-being performance (EWP), and the spatial correlation analysis method is used to analyze the spatio-temporal evolution characteristics of the EWP. The results show that the average EWP of the seven urban agglomerations in the Yellow River Basin was less than 1, showing a trend of firstly rising and then slowly decreasing. The average EWP presents the distribution pattern of the highest in the middle reaches, followed by the upper reaches, and the lowest in the lower reaches of the Yellow River Basin, respectively. The average ecological economic efficiency in the first stage of urban agglomerations of the Yellow River Basin was greater than the average economic well-being efficiency in the second stage. The average EWP in the Yellow River Basin shows local spatial heterogeneity during the study period. Policy measures are proposed to promote the improvement of the EWP of urban agglomerations in the Yellow River Basin. This study can provide reference for the policy formulation of high-quality green development and sustainable construction of urban agglomeration in the Yellow River Basin.

Extensive development leads to the decline of ecological well-being, and it is necessary to improve the urban ecological well-being performance (EWP). This paper adopted the Super-slack-based measure (Super-SBM) model to evaluate the EWP of 285 Chinese prefecture level cities from 2011 to 2017. The exploratory spatial data analysis method (ESDA) was used to explore the spatial and temporal evolution characteristics of the EWP, and then the spatial Durbin model (SDM) was adopted to analyze the driving factors of the EWP. The results show that the trend of the overall average EWP has experienced a stage evolution process of “upward → downward → upward”. The urban EWPs have significant spatial agglomeration and path dependence. The economic development level and technological progress had the positive impacts on the EWP, and the urbanization level, economic extroversion and industrial structure had the negative impacts on the EWP. The result reveals that there was a “U-shaped” relationship existing between urbanization level and the EWP. The negative spatial spillover effect of urbanization level on the EWP was significant. The corresponding policy implications were put forward. This study will provide strategic guidance for policy makers to optimize and enhance the urban EWP.