Understanding how ecological quality and human activity co-evolve in densely populated watersheds is essential for sustainable land management, yet spatially explicit long-term evidence remains limited. This study investigated the spatiotemporal dynamics and coupling coordination between ecological quality and multi-dimensional human activity intensity in the Huai River Basin (approximately 269,000 km²) from 2012 to 2024. An Improved Remote Sensing Ecological Index (IRSEI) was constructed by integrating EVI, wetness, dryness, land surface temperature, and a salinity index through annual principal component analysis. A composite Human Activity Intensity (HAI) index combining nighttime light, built-up intensity, and population density was derived with objectively determined weights. The coupling coordination degree (CCD) model and a pixel-level four-quadrant classification were then applied to characterize the human–environment interaction. Results showed that the basin-wide mean IRSEI declined from 0.564 in 2012 to 0.516 in 2020, before recovering to 0.566 in 2024, while HAI increased moderately by 16.9%. CCD improved slightly from 0.451 to 0.480, indicating limited but positive coordination gains. Four-quadrant transitions revealed that high-ecology, low-activity areas expanded, low-ecology, low-activity areas contracted, whereas low-ecology, high-activity zones persisted as stable pressure cores. These findings demonstrate that ecological recovery and human activity intensification can coexist spatially, but persistent high-pressure areas require targeted management interventions.

Understanding how staple-crop geography aligns with climate resources is important for food-security planning under climate change. Focusing on rice, winter wheat and maize in China from 2001 to 2020, this study constructed 1 km crop-abundance grids from annual 30 m crop-distribution data and integrated weighted centres of gravity (COGs), Standard Deviational Ellipses (SDEs), effective accumulated temperature and a Climate Resource Matching Index (CRMI) to evaluate crop migration, spatial-form change and matching with thermal, pluvial and radiant resource centres. Results show that rice exhibited the strongest northeastward migration, with a cumulative COG path of 448.9 km, but its CRMI declined markedly, indicating that thermal relaxation did not translate into coordinated multi-resource improvement. Winter wheat remained anchored in the Huang-Huai-Hai Plain, with adjustment mainly occurring through internal concentration and persistent moisture constraints. Maize showed expansion before 2015 followed by partial correction, and its CRMI trough in 2015 was robust under alternative weighting schemes. Overall, China’s staple-crop change represents a differentiated spatial reconfiguration rather than a uniform northward shift. Because these metrics are national-scale, the findings should inform crop zoning as broad spatial signals rather than direct local yield responses.

Composite environmental risks accumulate unevenly along urban–rural gradients, yet the conditional and nonlinear interaction between built environment quality (BEQ) and urban–rural functional connectivity (URFC) remains poorly quantified at fine resolution. This study aims to determine whether, and under what conditions, BEQ moderates the relationship between URFC and a population-weighted composite risk index (CRI), and to translate the result into spatia targeted green-infrastructure priorities. We use 744,714 grid cells at 100 m resolution over Guangzhou, China. The framework couples entropy-weighted BEQ from satellite and street-view imagery, gravity-model URFC computed on the real road network, and a two-stage population-weighted CRI of heat and air hazards. We apply nested ordinary least squares with incremental F-tests, spatial-lag and spatial-error models, generalised additive models with B-spline bases, gradient-boosted trees with SHAP interaction values, and Baron–Kenny mediation analysis. The main BEQ × URFC estimates are negative across the parametric and machine-learning specifications. The interaction is, however, small: a spatial-lag model on a 10,000-cell subsample returns β = −5.4 × 10⁻⁴, but a scalable generalised-method-of-moments spatial regression on the full grid—where the spatial autoregressive coefficient reaches ρ ≈ 0.99—shows the coefficient to be negative yet not statistically significant, and a five-seed re-estimation confirms that the subsample-based significance is draw-dependent. We therefore interpret the buffering as directionally supported but small and not robustly significant once spatial autocorrelation is fully modelled. The buffering response is nonlinear in the GAM main effects, and BEQ buffers across the entire observed connectivity range rather than switching sign at an interior threshold; URFC functions predominantly as a moderator rather than a mediator. Population-stratified estimation shows that the buffering is exposure-conditional: it is strongest where population exposure is high and weakens or reverses in sparsely populated cells, consistent with the risk = hazard × exposure structure of CRI. Sensitivity tests across values of the distance-decay parameter, 100 entropy perturbations and spatial scales corroborate the buffering direction. The framework provides an evidentiary basis for prioritising green infrastructure in functionally connected, populated but environmentally degraded transition zones.

This study examines the spatiotemporal evolution and driving mechanisms of urban expansion in the Guangxi Zhuang Autonomous Region, China, from 2013 to 2023. Using Suomi-NPP VIIRS nighttime light (NTL) data, we combine Standard Deviational Ellipse (SDE) analysis, centroid migration, kernel density estimation (KDE), landscape metrics, Local Moran’s I (LISA), and system Generalised Method of Moments (system-GMM) estimation. The results show that the centroid of urban development remained within Binyang County while moving overall toward the southeast with recurrent north–south oscillations. The SDE results indicate a stable northeast–southwest orientation, with secondary expansion in other directions. The urban structure is dominated by a strong Nanning core, accompanied by secondary clusters in Liuzhou, Guilin, and other prefecture-level cities. Nanning recorded the largest absolute expansion, followed by secondary centres, including Liuzhou, Guilin, Yulin, Wuzhou, Fangchenggang, Qinzhou, and Beihai, whereas western and northern Guangxi expanded more slowly. The system-GMM results indicate that financial deepening has a marginally significant positive effect on built-up area expansion and fiscal pressure has a marginally significant constraining effect, both at the 10% level; land finance dependency does not emerge as an independent driver in this small panel. We interpret these findings through a Source–Channel–Valve framework, in which financial deepening provides the capital source, land finance represents a hypothesised institutional channel, and fiscal pressure acts as a regulatory constraint. The study provides empirical evidence for sustainable and regionally coordinated urban development in Guangxi and comparable geographically constrained regions.