Exploring the correlation of the built environment with metro ridership is vital for fostering sustainable urban growth. Although the research conducted in the past has explored how ridership is nonlinearly influenced by the built environment, less research has focused on the spatiotemporal ramifications of these nonlinear effects. In this study, density, diversity, distance, destination, and design parameters are utilized to depict the “5D” traits of the built environment, while Shapley Additive Explanations with eXtreme Gradient Boosting (XGBoost-SHAP) are adopted to uncover the spatial and temporal features concerning the nonlinear relationship of the built environment with ridership for metro stations located in Xi’an. We conducted a K-means clustering analysis to detect different site clusters by utilizing local SHAP coefficients. The results show that (1) built environment variables significantly influence metro ridership in a nonlinear manner at different periods and thresholds, with the POI facility density being the most critical variable and the other variables demonstrating time-driven effects; (2) the variables of population density and parking lot density exhibit spatial impact heterogeneity, while the number of parks and squares do not present a clear pattern; and (3) based on the clustering results, the metro stations are divided into four categories, and differentiated guidance strategies and planning objectives are proposed. Moreover, the current work offers a more developed insight into the spatiotemporal influence of built environments on metro travel in Xi’an, China, using nonlinear modeling, which has vital implications for coordinated urban–metro development.

The production–living–ecological functions of rural settlements are closely tied to water resources, which are the primary influencing factors of the spatial characteristics of rural settlements. However, the specific relationship between water resources and the spatial characteristics of rural settlements remains unclear. Understanding the interrelationship between the two can better safeguard the ecological pattern of the basin and optimize the living environment of settlements. This study utilized multi-source data to calculate the water yield, water demand, and ecological surplus or deficit of water resources in the Yanhe watershed. We quantified the spatial characteristics of rural settlements and employed bivariate spatial autocorrelation methods to analyze the spatial correlation between water resources and the spatial distribution, scale, and boundary form of rural settlements in the Yanhe watershed. The results show the following: ➀ Seven sub-basins in the upper reaches exhibit a severe ecological deficit in water resources, with insufficient water resources to support the demands of regional socio-economic development. The middle and lower reaches have achieved a balance between water supply and demand. ➁ Rural settlements are most densely distributed in the middle reaches, with the smallest area scale, exhibiting a transitional spatial characteristic towards the upstream and downstream ends. ➂ The Moran’s I values of spatial aggregation and morphological index of rural settlements with respect to the ecological surplus or deficit of water resources are 0.36 and 0.50, respectively, indicating a strong positive correlation. The Moran’s I value of the area scale with respect to the ecological surplus or deficit of water resources is −0.60, indicating a significant negative correlation. This research has important practical significance for guiding the spatial layout of rural settlements in the Yanhe watershed and promoting their sustainable development.

The long-term impacts of climate change and human activities have resulted in the Yanhe watershed, a typical watershed in the Loess Plateau region, exhibiting a high degree of vulnerability and significant heterogeneity in ecological environmental quality. This has led to environmental degradation and complex socio-ecological challenges. Consequently, there is an urgent need to carry out research on the spatial and temporal differentiation patterns of ecological environment quality. By utilizing remote sensing data spanning 21 years, this study evaluated the evolutionary trends and consistency of ecological environment quality (EEQ) within the Yanhe watershed based on the remote-sensing-based ecological index (RSEI). Furthermore, it examined global and local spatial autocorrelation of the RSEI by constructing a hexagonal grid, thereby revealing the spatiotemporal characteristics of EEQ at different scales within the Yanhe watershed. The results were as follows: (1) The EEQ has exhibited an overall upward trend in the past two decades, while it has displayed significant fluctuations; (2) the Global Moran’s I values for the years 2000, 2010, and 2020 were 0.18, 0.32, and 0.21, respectively, indicating a presence of spatial autocorrelation within the RSEI; (3) the overall EEQ of the Yanhe watershed will continue to improve, although the ecological quality in certain areas remains unstable due to local natural conditions and human activities. This research not only contributes to the technical framework for analyzing the spatiotemporal heterogeneity of EEQ but also provides actionable insights for ecosystem restoration and sustainability within the Loess Plateau watershed. Our work advances the understanding of ecological dynamics in semi-arid regions and offers a model for assessing ecological quality in similar environmental contexts.

Suburban villages are strongly influenced by cities. Understanding the relationship between urban and rural as well as the hierarchy of villages contributes to optimizing the structure of village-town, allocating resources effectively as well as coordinating the relationship between urban and rural areas. Taking the rural area of Qin and Han New City as the research object, this paper obtained the number of contact flows between urban and rural areas from cellphone signaling data mining and constructed a network with hierarchical system. The influence scope and hierarchy of city and village nodes in the network could be measured by conducting the primary linkage analysis. The effect intensity and radius of the central villages as well as the relationship between villages could be calculated by the multiple linkage analysis. Furthermore, according to the urbanization potential and the characteristic regions of cites, the regional village-town system could be finally determined. This study has shown that 89.4% of the villages were influenced by the surrounding cities strongly, and the influence range of the cities was 6.2-28.3km. There were 13 “Centrality” villages in this region, which was lean to city, traffic convenience and divisional centralized. Totally, 19 groups of villages should be merged and 3 groups should be developed together. Besides, two kinds of village-town systems were formed in this region, and the villages were classified into five categories for guidance. Moreover, the research results could not only provide a helpful method to determine the village-town system structure under the strong influence of cities but also offer a better way for resources allocation between urban and rural smartly and equally.

There are frequent population flow and complex spatial structures in suburban villages. Understanding the spatial characteristics of population activities in suburban villages helps to coordinate the relationship between urban and rural areas and guide the development of suburban villages and the formulation of sound policies. Taking the rural area of Qin and Han New City as the research object, this paper constructs a population time-space analysis framework of “population attribute-activity characteristics-spatial analysis” based on cellphone signaling data. According to the characteristics of the population activity curve, K-means clustering algorithm was used to classify rural space and analyze their characteristics. This study has shown that migrants, who are showed as young and energetic, account for 49.8% of the local registered population per day. Bidirectional flow of residents and commuters is generally presented in urban and rural areas. The urban-rural relation curve was characterized by “double peaks”. The changes in the population in each village and the intensity of urban-rural relation were affected by location, industry and land use. The village population activity curve was classified into three categories, and nine characteristic villages are formed combined with the activity function. The research results can provide a scientific basis for urban and rural planning, spatial planning, industrial guidance and the facility layout.