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.

With the acceleration of urbanization, the disturbance to urban landscape patterns causes changes to urban surface runoff and increases the risk of urban waterlogging. We studied the response relationship between landscape pattern change and surface runoff in the Chang–Zhu–Tan metropolitan area for the period from 2000 to 2020, analyzing the driving factors that affected surface runoff. The influence of landscape pattern evolution on surface runoff was studied using the SCS-CN flow generation model, the moving window method, and Pearson’s analysis. The analysis showed that between 2000 and 2020, the forest area decreased, while the impermeable land area increased substantially. At the same time, the landscape spread degree (CONTAG) decreased, whereas the landscape fragmentation degree (DIVISION) increased, and the Shannon diversity index (SHDI) and landscape shape index (LSI) increased. The surface runoff in the main urban areas of Chang–Zhu–Tan increased substantially. The results showed that surface runoff is negatively correlated with SHDI, LSI, and DIVISION but displays a positive relationship to CONTAG. Soil texture and precipitation had the greatest impact on surface runoff. This study emphasizes the importance of landscape pattern evolution to surface runoff in rapidly developing metropolitan areas in terms of reducing surface runoff, alleviating urban waterlogging and preventing regional floods. Our research additionally seeks to optimize the landscape pattern of the Chang–Zhu–Tan metropolitan area.