Urban green space, comprising parks, fields, woodlands, and other semi-natural areas, is a fundamental component of urban ecosystems. The determination of the relationship between urban green space and urban sprawl is necessary to understand urbanization and the provision of urban ecosystem services. It has been hypothesized that the center of urban (i.e., population and economic) areas in fast-growing cities would migrate toward urban green space over time. To test this hypothesis, urban expansion and urban green space expansion were examined in five cities in China and five cities in the U.S. that were experiencing high rates of growth. Landsat images of those cities from 2000 to 2017 were combined with annual population and economic data and used to quantify the extent and migration of the urban green space. These data were analyzed using the center of gravity method by Grether and Mathys and circular statistics were used to determine the relationship between urban green space and urban expansion. Eight out of the ten cities showed a divergent pattern, i.e., the population and economic centers moved in a different direction to that of the urban green space. The movement of the mean centers of the urban green spaces in the U.S. cities was more consistent than that of the Chinese cities. Over 18 years, the movement of urban green space and urban expansion in the 10 cities showed a synchronous growth trend; however, the proportion of urban green space in the cities decreased. The urban expansion rate exceeded the population growth rate, which led to problems with an unreasonable urban sprawl that is likely to deplete the provision of ecosystem services in the future. In conclusion, the centrifugal forces of urban green space that lead to the movement of population and economic centers away from green spaces play a larger role in urban change than the centripetal forces that pull these centers toward urban green space.

The study of spatial layout in China is changing from land use/land cover to territorial spatial layout and is mostly carried out at the administrative division scale. However, the driving factors affecting the evolution of territorial spatial layout are not all influenced by administrative boundaries. As cities are mostly centered on lakes and water systems, the evolution of territorial spatial layout in lake-type basins must have its own special characteristics. Taking the Dongting Lake Basin (DLB), a representative lake-type basin in China, as an example, this study identifies its territorial spatial layout elements and couples the system dynamics model with the patch-generating land-use simulation model based on multi-layer perceptron artificial neural networks. This study identified the best combination of driving factors and research step size affecting the evolution of territorial spatial layout. An improved quantitative spatial coupling model was used to simulate the territorial spatial layout of the DLB from 2000 to 2050 and identify its evolutionary characteristics and trends at both the elemental level and for three types of space. The simulation and prediction of territorial spatial layout from the lake-type basin hydrology scale can provide a reference for the formulation of regional territorial spatial planning policies.

Land use and land cover (LULC) changes play a crucial role in regional carbon dynamics and climate regulation. This study assesses the impact of LULC changes on carbon stocks in Hunan Province, China, from 2000 to 2035 using a MOP-PLUS–InVEST–OPGD integrated modeling framework. Results show that carbon stock declined by 45.96 million tons from 2000 to 2020 due to rapid urban expansion and conversion of forest and grassland to construction land. Scenario simulations reveal that by 2035, carbon stock will increase by 4.82% under the ecological protection scenario (EP) but decrease by 3.26% under the natural trend scenario (NT). Economic development scenario (ED) and sustainable development scenario (SD) produce intermediate outcomes. Spatially, high-carbon regions are concentrated in high-altitude forested areas, while urbanized lowlands exhibit the lowest carbon density. The optimal parameters-based geographical detector (OPGD) model identifies land use intensity, elevation, and net primary productivity as the dominant drivers of carbon stock variation, with significant interactions between natural and socioeconomic factors. These findings underscore the need for integrated land-use planning and ecological conservation policies that align with carbon neutrality goals. This study provides a replicable spatial framework and policy-oriented insights for managing carbon stocks in rapidly developing regions.

With the rapid advancement of industrialization and urbanization, the systematic assessment of water environment security in lake-type basins and the identification of key restoration zones have become critical scientific challenges for sustainable watershed management. This study focused on the Dongting Lake Basin, where a comprehensive evaluation system comprising 24 indicators was developed based on the Driving forces–Pressure–State–Impact–Response model. Indicator weights were determined using the entropy method. An obstacle degree model was applied to quantitatively identify the primary factors constraining water environment security. Additionally, spatial autocorrelation analysis was introduced to examine spatial dependency characteristics, enabling the delineation of priority restoration areas. The results demonstrated the following: (1) During 2000–2020, the Dongting Lake Basin exhibited significant spatial heterogeneity, with higher water environment security risks in the southeastern region, while the central-eastern region showed a continuous improvement trend. (2) Quantitative analysis identified the core obstacle factors affecting regional water environment security: wastewater treatment capacity (obstacle degree: 16.87%), ecological water use proportion (12.71%), effective irrigation area ratio (9.29%), environmental protection investment as a percentage of GDP (8.54%), and wastewater treatment rate (7.10%). (3) Based on these key constraints, targeted governance strategies are proposed, including enhancing wastewater treatment capacity, optimizing ecological water allocation, and increasing environmental protection investment. This study established an integrated “diagnosis–restoration–regulation” analytical framework for assessing water environment security and identifying priority restoration zones in lake-type basins, providing both theoretical foundations and practical references for global lake-type basin management.