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A series of negative effects of urban development have emerged owing to the imbalance of population, industry, and built-up land spatial agglomeration. This study proposes an integrated coupling coordination index system in sustainable urbanization evaluation based on population, industry, and built-up land, to evaluate the spatial-temporal evolution of coupling and coordination degree in Guangxi from 2005 to 2015. In addition, we adopted the exploratory spatial data analysis method to reveal the spatial pattern of coupling and coordination degree and its impact on sustainable urbanization. Finally, local indicator of spatial association (LISA) analysis was employed to identify the spatial heterogeneity of the coupling and coordination index values. The results, on the one hand, show that the coupling coordination degree of all counties increased yearly, but extremely slowly. The 88 counties in Guangxi are still in a low level of urbanization. On the other hand, a spatial agglomeration effect of urbanization levels is observed in this study. We found that the urbanization development is not independent. In other words, the urbanization level of each county will more or less be affected by its surrounding counties. In conclusion, in China, sustainable urbanization is closely related to the rational allocation of population, industry, and land resources. To promote the sustainable development of urbanization, it is necessary to strength the role of land use control and to rationally allocate these three elements in general.

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Water can carry or overturn a boat. Natural resources form the foundation of human survival and development. However, land use change caused by human urban civilization has damaged the natural environment and in turn threatened the continuation of human civilization. Accordingly, it is crucial to analyze the impacts of human activities on land use change and consequent dynamics of ecosystem service value (ESV). For the sustainable development of human beings, an investigation should be conducted to explore what type of land use behavior will be considerably beneficial to improve our relationship with the natural environment. This study analyzes the spatial–temporal dynamics of ESV of 148 counties in the Yangtze River Delta in China over three five-year periods (2000–2015) and examines the influence of socioeconomic forces and policy implications. Exploratory spatial data analysis and spatial regression were applied to facilitate the analysis. Results show that the averages of the ESV change ratios of the 148 counties in each of the aforementioned periods are −0.667%, −2.690%, and −4.668%, respectively. The number of counties that showed an ESV loss trend in the three periods are 72 (48.6%), 125 (84.4%), and 139 (93.9%), respectively. In terms of spatial pattern, ESV change demonstrates the spatial distribution characteristic of “high loss spreading from the northeast to the middle and west” with a tendency to strengthen spatial agglomeration. Results of the spatial regression analysis determine the overwhelming importance of population growth and economic advancement. The results also indicate that the development mode characterized by industrial structure, capital input, and technology upgrades can exert considerable influence on socioeconomic development, thereby affecting the change of ESV. Moreover, the constraints of policy substantially affect the changes of ESV from 2010 to 2015. Policy makers should consider the relationship between land use patterns and the ESV variation in different development stages to formulate appropriate measures, thereby reducing or preventing the loss of ecological service value and promoting sustainable development.

Urban land-use efficiency (ULUE) has been increasingly recognized as an issue of land-use management across the world in the last century as the globe experienced unprecedented rapid urban expansion. However, although a large body of studies was dedicated to analyzing the driving forces of ULUE, literature was rarely focused on the impacts of regional cooperation on ULUE. To bridge the knowledge gap, we used the Chinese trailblazer of regional cooperation–Yangtze River delta (YRD)—as a case to reveal the impacts of regional cooperation on ULUE. Social network analysis and a super efficiency SBM model with undesirable outputs were used to measure regional cooperation and ULUE, respectively. Furthermore, the impacts of regional cooperation on ULUE were examined by using the geographically and temporally weighted regression model. The results show that regional cooperation in the YRD strengthened from 2009 to 2016, among which Shanghai was the core node city in the YRD. Only seven cities maintained good ULUE with a stable trend during 2009–2016. The regression results indicated the positive impacts of regional cooperation on ULUE, which was more evident in the southern cities of the YRD. The potential mechanism to explain the impacts of regional cooperation on ULUE includes co-building transportation facilities and joint development zones. These findings provide insightful implications for improving ULUE by strengthening regional cooperation in Chinese cities.