With the fast pace of global urbanization, anthropogenic disturbances not only lead to frequent disasters, but also cause direct and indirect ecological and economic losses. To reduce the adverse effects of anthropogenic disturbances as part of sustainable ecosystem management, assessments of habitat quality and ecological risk are necessary. The objectives of this study are to analyze environmental conditions of the Beijing-Hangzhou Grand Canal (Suzhou section) for evaluating habitat quality and habitat degradation, and to conduct ecological-risk early warning assessment in this section. The Grand Canal is the longest and first canal in the world to be artificially excavated from natural rivers and lakes. By evaluating habitat quality using the InVEST suite of open-source software models for mapping and valuing the ecosystem, it was found that the natural lands with high habitat quality such as wetlands, forests and lakes along the Suzhou section of the Grand Canal have gradually decreased, while construction lands such as roads and buildings have gradually increased; there is a clear trend of decreasing areas with high habitat quality and increasing areas with low habitat quality, which is likely the result of urbanization. It was also found that the region has a high habitat degradation index, meaning that areas located at the junction of different land types are vulnerable to the surrounding environment due to narrow buffer zones that allow areas with high habitat quality to be easily affected by areas with low habitat quality. In terms of ecological risks, it was found that the natural land area with high habitat quality in the downstream locations was declining, thereby increasing the risks of pollution and flooding events while reducing the ecosystem’s resilience. The valuation model used in this study can be used as an effective decision-support tool to prioritize important ecological areas for conservation in the Grand Canal, and can also be adapted for use in the ecosystem management of other regions.

In developing countries like China, urbanization is still occurring at a rapid pace. During urbanization, the urban land expands drastically, which makes suburbs the most affected area facing urban expansion. The land transition has proven to threaten the function and security of ecosystems, and therefore the topics of suburban land transition and ecological security have raised much attention. However, the urban-suburban interaction, which is one of the basic characteristics of suburbs, has been insufficiently considered. The urban-suburban interaction is developed based on the flows of people, materials, and information between urban and suburban areas, and it essentially reveals the relationship between human activities and land-use optimization. To fill the research gap, this study adopts a case study of Wuhan city, and first quantifies the urban-suburban interactions from a symbiotic perspective, and investigates rural residents and public buses to verify the estimated interactions. The results show that there is obvious heterogeneity in urban-suburban interactions in different suburban towns. Correlation analysis and geographic weight regression are then applied to demonstrate the relationship between the urban-suburban interaction and urbanization in the suburbs. Additionally, urbanization potential in the suburbs is estimated. Then, a suburban ecological security assessment is conducted by a “pressure-status-response” (PSR) model, and the urbanization potential that is estimated based on urban-suburban interaction is integrated as a “pressure” indicator. The comparison between the suburban ecological security assessment results based on considering and not considering urban-suburban interaction demonstrates the importance of considering urban-suburban interaction. This study contributes to the understanding of the complicated relationships of urban-suburban socio-economic, spatial, and ecological environments, and offers suggestions for suburban planning and ecological protection.

As the transitional area between urban and rural areas, land-use change in suburbs is drastic, which generates negative effects on the ecological environment. However, the identification of the suburbs remains controversial. Usually, the density of the population and residential land is referenced, and the close spatial interactions between urban areas and suburbs are generally neglected. To fill this research gap, this study adopts a case study method to map the suburbs of Jiangsu based on estimating the spatial interactions. First, a regression model is built to estimate the population distribution. Second, a radiation model is utilized to evaluate the spatial interaction at a grid level. After the main urban area is identified based on the high density of the population and construction land, the interaction strength between the main urban grid and other grid areas is calculated, and the grids that share high values of interaction strength with urban grids are identified as suburban areas. Finally, the suburbs of Jiangsu in 1998 and 2018 are mapped, and the ecological landscape pattern metrics are used to verify the effects of suburban expansion. As a result, the suburban expansion of Jiangsu over the 20 years was significant, and the effects of suburban expansion on ecological land fragmentation were evident. On the basis of the results, the enlightenment of mapping suburbs on ecological landscape planning is discussed.

Despite the worldwide studies on urban agglomeration (UA), the effects of intra-UA interaction patterns have not been thoroughly elucidated to date. To fill the research gap, first, this study utilized the Baidu Internet search data to quantify the internal interaction patterns of 11 main UAs in China. Rail-way data were referenced for verification. Based on building intercity interaction network, the node symmetry index (NSI) was calculated. Considering the estimated interaction strength and mutuality, the intra-interaction patterns were classified into symmetrical and asymmetrical mutualism, where the former indicates that the interactions of cities are mutually beneficial and the latter means that the interactions are unbalanced. The socio-economic development levels of cities and UAs were estimated by the entropy-TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method. Finally, the impacts of intra-UA interaction were explored through ordinary least square regression. This study obtained two findings. Firstly, at the city scale, symmetrical mutualism had a greater impact than asymmetrical mutualism on the city’s socio-economic development level. Secondly, at the regional scale, both symmetrical and asymmetrical mutualism were related with regional socioeconomic development level; however, only symmetrical mutualism showed a correlation with regional coordinated development level. Respondent suggestions and implications to promote regional coordinated development were then offered based on the results of the analysis. Limitations of this study include that exogenous interactions between UAs and their backlands, and other relationships, such as competition, were not discussed. These issues can be considered in future researches. This study characterizes the interaction pattern of intra-urban agglomeration and offers advice and suggestion for implementing regional sustainable development.

In the context of rapid urbanization, inefficient, disorderly, and low-density urban sprawl often leads to resource waste and ecological damage. Over the decades, many studies on the measurement, analysis, and governance of urban sprawl have emerged. However, existing approaches lack in-depth research on distinguishing effective expansion from inefficient sprawl. Given the limit of land use resources and the demand for urban development, an accurate and reasonable method for urban sprawl measurement is needed. This study proposes an urban sprawl identification method based on a mechanical equilibrium model to analyze the spatial distribution and spatiotemporal evolution characteristics of inefficient sprawl, using the Yangtze River Delta’s (YRD) urban agglomeration as an example. The study found the following: (1) The inefficient sprawl in the YRD was 5219, 1189, and 980 km² in the three five-year periods between 2005 and 2020. (2) From 2005 to 2020, the inefficient sprawl in the YRD was, on the whole, a weakening trend, but Shanghai and Zhoushan showed an accelerating trend of inefficient sprawl. (3) The proposed method is applicable to most urban development patterns and provides implications for urban sprawl control in mega-urban agglomeration areas, such as the YRD.