The survival and sustainability of regional species is constrained by habitat quality. In recent decades, the intensification of human activities on a global scale has had a profound impact on regional ecosystems and poses a serious threat to regional sustainable development. Scientific measurement of the drivers of habitat quality can provide important support for the development of effective biodiversity conservation and sustainable land-use policies. Taking the Hung River Valley as an example, the InVEST model was used to assess the habitat quality of the study area in 2000, 2005, 2010, 2015, and 2020 and to explore its spatial and temporal variation and distribution characteristics in combination with the spatial autocorrelation model, and the geographically weighted regression (GWR) model was used to explore the drivers of habitat quality change. The results show the following: (1) The overall habitat quality shows an increasing trend during 2000–2020, but the expansion of construction land in the central region plays a dominant role in the degradation of regional habitat quality. (2) The “Guide-Ledu” line is the dividing line of habitat quality in the Hung River Valley, with a general distribution of “south is good, north is bad” and “south is hot, north is cold”. (3) Natural factors such as slope and elevation basically shape the overall distribution pattern of habitat quality, while urbanisation factors such as population density, gross domestic product, and the night-time lighting index are generally negatively correlated with habitat quality. The results of the study can reveal the linkage between ecosystems and land-use change in the context of urbanisation.

Urban agglomerations have gradually formed in different Chinese cities, exerting great pressure on the ecological environment. Ecosystem health is an important index for the evaluation of the sustainable development of cities, but it has rarely been used for urban agglomerations. In this study, the ecosystem health in the middle reaches of the Yangtze River Urban Agglomeration was assessed using the ecosystem vigor, organization, resilience, and services framework at the county scale. A GeoDetector was used to determine the effects of seven factors on ecosystem health. The results show that: (1) The spatial distribution of ecosystem health differs significantly. The ecosystem health in the centers of Wuhan Metropolis, Changsha–Zhuzhou–Xiangtan City Group, and Poyang Lake City Group is significantly lower than in surrounding areas. (2) Temporally, well-level research units improve gradually; research units with relatively weak levels remain relatively stable. (3) The land use degree is the main factor affecting ecosystem health, with interactions between the different factors. The effects of these factors on ecosystem health are enhanced or nonlinear; (4) The effect of the proportion of construction land on ecosystem health increases over time. The layout used in urban land use planning significantly affects ecosystem health.

As a transitional zone between urban and rural areas, the peri-urban areas are the areas with the most intense urban expansion and the most frequent spatial reconfiguration, and in this context, it is particularly important to reveal the evolution pattern of rural settlements in the peri-urban areas to provide reference for the rearrangement of rural settlements. The study takes five townships in the urban suburbs, and explores the scale, shape, spatial layout, and spatial characteristics of the urban suburbs of Hefei from 1980 to 2030 under the influence of urban-lake symbiosis based on spatial mathematical analysis and geographical simulation software. The study shows that: (1) the overall layout of rural settlements in the study area is randomly distributed due to the hilly terrain, but in small areas there is a high and low clustering phenomenon, and the spatial density shows the distribution characteristics of “high in the east and low in the west”; (2) since the reform and opening up, there are large spatial differences in the scale of rural settlements in the study area. (3) Different development scenarios have a strong impact on the future spatial pattern of rural settlement land use within the study area, which is a strong reflection of policy.

Urban agglomerations (UAs), which play a significant role in socioeconomic development and urbanization, are confronted with mounting ecological stress and a profound global imbalance in ecosystem services (ES). Understanding the conflict and coordination of knowledge about ES supply and demand (ESSD) can facilitate more efficacious guidance on the ecological sustainable development of UAs. Nevertheless, the characteristics of the conflict and coordination relationship between ESSD in Chinese UAs remain unclear, and further investigation into the interactive coercive relationship between ESSD is warranted. Consequently, we employed spatial regression and coupled coordination models to elucidate the conflict and coordination relationship between ESSD, utilizing multi-source data on Chinese UAs from 2000 to 2020. We found that ES supply in the UAs decreased, while ES demand increased. Furthermore, the coupling coordination degree between ESSD demonstrated an increase trend. The overall coupling coordination degrees between ESSD in UAs were 0.260, 0.285, and 0.311 in 2000, 2010, and 2020, respectively. The central UAs were identified as stress areas, whereas the peripheral areas were classified as non-stress areas. This study offered valuable insights into the interactive relationship between ESSD in UAs and provided a basis for formulating differentiated policies for the sustainable development of ecosystems and human activities.

The unbalanced allocation of educational resources in kindergartens across China has attracted increasing attention from scholars and the public. However, few studies have examined their spatially imbalanced distribution and its influencing factors. Based on point-of-interest data, this study systematically analyzes the spatially imbalanced distribution characteristics of kindergartens in China from a multiscale perspective using the spatial analysis and spatial regression model to identify the factors influencing its formation pattern. The results reveal that the distribution pattern is “more in the southeast and fewer in the northwest,” with the Hu Huanyong Line serving as the boundary. Kernel density analysis revealed that areas with a density greater than 0.34 individual/km² were primarily concentrated in provincial capitals and major metropolitan areas, exhibiting a gradual decrease outward from these core zones. It also reveals a “large dispersion and small aggregation”, with a concentration around mega-cities, urban agglomerations, and provincial capitals. Significant spatial auto-correlations were found at all administrative levels, with hotspots distributed in northeast, north, and southeast China. The spatial determinants of kindergartens distribution in China exhibited significant spatial heterogeneity. The findings provide a reference in improving the spatial pattern and the state of unbalanced development of kindergarten education in China, as well as scientific suggestions to optimize resource allocation.

Research on the coupling coordination relationship between land–use carbon emissions (LUCE) and ecosystem service value (ESV) is vital for achieving China’s “dual carbon” goals and advancing ecological civilization. Applying the carbon emission coefficient method, equivalent factor method, coupling coordination degree model, and Geographically and Temporally Weighted Regression (GTWR) model, this study examined spatiotemporal patterns of land–use changes, carbon emissions per unit area (ACE), and ecosystem service value per unit area (AESV) across China (excluding Xizang, Hong Kong, Macao, and Taiwan) from 2000 to 2020, along with their coupling relationship and driving forces. Results showed that grassland, forest, and cropland accounted for more than 70% of China’s land area, with a total land–use conversion area of 1.42 × 106 km². ACE increased while AESV generally decreased, both displaying strong spatial heterogeneity and agglomeration. The average Dagum Gini coefficients were approximately 0.70 for ACE and 0.58 for AESV. Coupling coordination degree mostly fluctuated around 0.20, rising initially and then falling, with distinct spatial variations in coordinated development types. Population density, Normalized Difference Vegetation Index (NDVI), and average elevation were negatively correlated with the synergistic effect between LUCE and ESV, whereas GDP density, annual precipitation, and average slope showed positive correlations. These findings provided theoretical support for formulating scientific land–use policies, optimizing carbon emission management, and implementing effective ecological protection measures.