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.

There have been many studies that have only focused on factors affecting the spatial distribution of rural settlements, without paying attention to their function and scale. China’s mountainous rural area has many problems, such as a fragile ecological environment, poor infrastructure and limited public service facilities. As a result, mountainous rural settlements demonstrate a disorderly and scattered layout. This research takes southern Shaanxi as its research area and uses quantitative and qualitative analysis to analyze the field survey data, revealing the spatial format of rural settlements and its influencing factors. The research results show that: (1) The spatial structure of mountainous settlements can be summarized as falling into three types—agglomeration type, belt type, and dispersion type. The individual settlements are discrete, and the spatial structure of the settlement groups exhibits small-scale clustering in a large area. (2) The influencing factors of spatial structure are ranked thus—geomorphological conditions > population quantity > land use scale. (3) The number of settlements in the study area is constantly decreasing, and their boundaries are gradually shrinking, showing randomly distributed characteristics. (4) A radius of 284.12 m can be used as a measure of the development scope of the village to control the scope of settlement construction. The objective of the research is to classify the spatial structure and propose the most optimal spatial mode in mountainous rural areas.

Slate dwellings are known as the “living fossil of primitive dwellings” in China. Energy-saving strategies are crucial to slate dwellings for sustainability as well as maintaining thermal comfort. In this research, a subjective satisfaction analysis on the indoor thermal environment in Daziliang village, China, was conducted. It was found that neutral temperature is 20.92 °C in summer, 8.92 °C in winter, and the actual operating temperature in winter is too low to meet the 80% acceptable range. Therefore, a series of improvement strategies in winter were proposed. The results showed that adding external thermal insulation material—expanded polystyrene board with a thickness of 80 mm on the roof and outside walls—and sunspace depth of 1.5 m are better in terms of energy-saving effects. In addition, the slate dwelling’s daily energy-saving rate of the heating day is 44.26% lower than the original state through these strategies. The air temperature of Bedroom D in winter non-heating days increases by 3.82 °C after improvement and the mean radiant temperature increased by 2.54 °C. Our approach puts forward specific energy-saving improvement measures and provides feasible suggestions for the protection and development of slate dwellings in this area.

In recent years, Xi'an metro construction has been progressing rapidly, becoming the primary mode of urban green public transportation. Since the ridership of the metro is closely linked to the characteristics of its surrounding built environment, a key problem in promoting the benign development between the two is to explore the spatiotemporal distributional difference in ridership and its influencing factors. In this study, the "5D" characteristics of built environment are described by density, diversity, design, destination and distance variables. The spatiotemporal distribution characteristics of ridership are analyzed via Arc GIS and Python, while the nonlinear relationships between ridership and built environment of 106 metro stations of downtown Xi'an, as well as relevant threshold effects are revealed via Shapley additive explanations with gradient boosted decision tree (GBDT-SHAP). The results show that: (1) Xi'an metro travel presents a medium-short spatiotemporal distribution, and the ridership network is characterized by strong center-spillover. (2) The nonlinear relationship between built environment and ridership is ubiquitous and presents a threshold effect. The impact threshold of bus stop density on ridership is 4-6 pcs/km², the impact threshold of road network density is roughly 4-5 km/km², and the effective threshold of building density does not exceed 20%. (3) The positive impact of POI facility density on peak ridership is stronger than that at flat hours. Variables like land use mixture, population density and distance from downtown have a time-driven effect on the ridership, whose importance and influence change with time. This study provides a better understanding of the spatiotemporal impact of Xi'an's built environment on metro travel, which is of profound significance for the coordinated development between the city and metro construction.

Landscapes in semiarid regions are highly sensitive to climate change and anthropogenic activities, and their evolution directly influences ecosystem services and regional ecological security. Although previous research has examined land use changes, systematic quantitative analyses of long-term evolutionary trends and driving mechanisms, particularly the comprehensive relationships between key hydrological elements and landscape pattern evolution in water-scarce, semiarid watersheds, remain limited. To address the research gap in long-term, multifactor, and hydro–landscape integrated analysis, China’s Tuwei River watershed was selected as the study area in this study, and methods such as landscape pattern indices and gray relational analysis were employed to quantitatively reveal the spatiotemporal evolution of watershed landscape fragmentation from 1980 to 2020 and identify its dominant driving forces. The results revealed that (1) over the 40-year period, the land use structure of the watershed underwent significant restructuring, with developed land expanding by 1282%, cropland and bare land areas decreasing by 14.2% and 32.01%, respectively, and grassland and forestland areas increasing by 24.5% and 14.9%, respectively; (2) land-scape fragmentation continued to intensify, with the landscape fragmentation composite index (FCI) increasing by 37.6%, patch density (PD) continuously increasing, edge density (ED) and landscape shape index (LSI) increasing significantly, and landscape connectivity weakening; (3) natural and socioeconomic factors jointly drove landscape evolution, with temperature and mean annual flow contributing the most among natural factors and the urbanization rate and secondary industry output value serving as the core drivers among socioeconomic factors; and (4) the trend of landscape fragmentation was synchronized with changes in annual rainfall and runoff and exhibited a significant negative correlation with the groundwater level. In summary, through long-term, multifactor comprehensive analysis, the evolution characteristics and driving mechanisms of landscape patterns in the Tuwei River watershed were systematically revealed in this study. These findings not only deepen the understanding of landscape fragmentation processes under the dual pressures of climate change and anthropogenic activities but also provide scientific evidence for the sustainable management of landscapes and associated ecosystems in semiarid watersheds.