Land subsidence has become an increasing global concern over the past few decades due to natural and anthropogenic factors. However, although several studies have examined factors affecting land subsidence in recent years, few have focused on the spatial heterogeneity of relationships between land subsidence and urbanization. In this paper, we adopted the small baseline subset-synthetic aperture radar interferometry (SBAS-InSAR) method using Sentinel-1 radar satellite images to map land subsidence from 2015 to 2018 and characterized its spatial pattern in Wuhan. The bivariate Moran’s I index was used to test and visualize the spatial correlations between land subsidence and urbanization. A geographically weighted regression (GWR) model was employed to explore the strengths and directions of impacts of urbanization on land subsidence. Our findings showed that land subsidence was obvious and unevenly distributed in the study area, the annual deformation rate varied from −42.85 mm/year to +29.98 mm/year, and its average value was −1.0 mm/year. A clear spatial pattern for land subsidence in Wuhan was mapped, and several apparent subsidence funnels were primarily located in central urban areas. All urbanization indicators were found to be significantly spatially correlated with land subsidence at different scales. In addition, the GWR model results showed that all urbanization indicators were significantly associated with land subsidence across the whole study area in Wuhan. The results of bivariate Moran’s I and GWR results confirmed that the relationships between land subsidence and urbanization spatially varied in Wuhan at multiple spatial scales. Although scale dependence existed in both the bivariate Moran’s I and GWR models for land subsidence and urbanization indicators, a “best” spatial scale could not be confirmed because the disturbance of factors varied over different sampling scales. The results can advance the understanding of the relationships between land subsidence and urbanization, and they will provide guidance for subsidence control and sustainable urban planning.

Land use intensity (LUI) reflects the utilization status of land use. However, traditional LUI assessments have been conducted for land space governance with a primary focus on surface land. Thus far, the explicit variation and spatiotemporal characteristics of land use of underground space (LUUS), particularly the quantization of LUUS-related intensity, are not well understood. Using the case of Wuhan in China, this study takes the main urban area of Wuhan as the research area, based on the time series data of the underground space information survey of analysis units from 2002 to 2018. This reflected the distribution pattern and evolution characteristics of underground space in terms of the intensity, the concentration and spatial hot-spots by using the spatiotemporal analysis framework. The results show that: (1) The LUUS exhibits spatial characteristics of global dispersion, and local aggregation increased and expanded along the northwest–southeast direction; (2) The global spatial dependency of LUUS is strong and the degree decreases with the expansion of the scope; (3) The LUUS is mainly developed in a relatively concentrated mode, and the concentration degree decreases with time; (4) The main development area of the LUUS is gradually expanding from within the inner ring line outside the second ring road in different periods, and the spatial difference is more obvious and increasing. Our study renews the indicators of quantitative LUI evaluation based on underground spatial data. The findings refreshed the knowledge base concerning the spatiotemporal heterogeneity in terms of underground space intensity and provided new insights into spatial governance.

Spatial mismatches between ecosystem services and human demands pose critical challenges for sustainable land use in ecologically fragile regions. Rapid urbanization intensifies land-use conflicts in ecologically fragile regions, threatening ecosystem services and habitat sustainability. This study addresses this challenge by quantifying spatial mismatches between landscape resource functions (LRFs: natural, traditional, and humanistic) and service demands (LSFs, e.g., catering and public facilities) in Xinxian County, in China’s Dabie Mountains, using multi-source data (DEM, POI big data, and remote sensing) and spatial analysis (nearest neighbor indices, kernel density, and multi-ring buffers). The results reveal that concentrated natural LRFs in high-elevation single-core clusters exhibit low dispersion, thus increasing vulnerability to land conversion, while agglomerated LSFs in urban cores exacerbate ecosystem service inequalities. Crucially, service deficits beyond 3 km buffers and the fragmentation of traditional agricultural zones indicate potential erosion of regulating services, as inferred from spatial mismatches (e.g., soil retention and water regulation), and cultural resilience. These spatial mismatches act as proxies for habitat risks, in which humanistic landscape expansion competes with ecological corridors, amplifying fragmentation. To mitigate risks, we propose (1) enhancing connectivity for natural resource corridors to stabilize regulating services, (2) reallocating LSFs to peri-urban buffers to reduce pressure on critical habitats, and (3) integrating ecosystem service trade-offs into landscape planning. This framework provides an actionable pathway for balancing development and habitat conservation in mountainous regions undergoing land-use transitions.