Urban agglomeration has become a crucial topic in order for the Chinese government to promote new-type urbanization in China, and its urbanization will greatly affect China’s eco-environment. Existing literature on bidirectional influence between urbanization and eco-environment from the perspective of urban agglomeration is, however, limited. This study establishes a conceptual framework to identify bidirectional relationships between urbanization and eco-environment in urban agglomerations. After evaluating urbanization level and eco-environment quality for each city in an urban agglomeration, this framework determines key interaction factors, and employs a global regression approach to quantify the coercing effects of urbanization on eco-environment and constraining effects of eco-environment on urbanization. Spatial heterogeneity of bidirectional interactions is then examined using local regression, represented by geographically weighted regression. The case study in the urban agglomeration in the middle reaches of the Yangtze River from 2000 to 2015 indicated the existence of bidirectional interactions and coercing threat that was stronger than constraining pressure in this region. The coercion that urbanization posed on the eco-environment began to vary in space significantly from 2010, whereas the constraint of eco-environment on urbanization was spatially stationary. This study will help policy-makers to develop sustainable policies to balance urban development and eco-environment conservation.

The study of industrial spatial linkages of urban agglomerations is crucial to recognizing spatial structure and optimizing regional division and cooperation. The existing studies often focus on external spatial interaction at the inter-city level, but few have considered complex internal economic linkages at the inter-sector level. In this study, we established an integrated framework by combining the wave effect gradient field with the gravity model. The wave effect gradient field was used to analyze the inter-sector relation, while the gravity model was adopted to explore the spatial interactions of industry at the inter-city level. The Urban Agglomeration in the Middle Reaches of the Yangtze River (UAMRYR) was taken as a case study, which demonstrates the applicability of the proposed framework. The results indicate that there exists an imbalanced development in the network of industrial linkages in the study region. Each subgroup has presented a self-organized spatial linkage network, but the linkages between subgroups are immature. Compared with other sectors, the high-tech and internet industrial sectors contribute most to economic linkages among cities. Thus, policymakers should take actions to strengthen the inter-subgroup spatial linkages and give priority to the high-tech industries, which is necessary for the integrated and sustainable development of UAMRYR.

Urban agglomeration has become the predominant form of urbanization in China. In this process, spatial interaction evidently played a significant role in promoting the collaborative development of these correlated cities. The traditional urban model’s focus on individual cities should be transformed to an urban system model. In this study, a multi-scale simulation model has been proposed to simulate the agglomeration development process of the Wuhan urban agglomeration area by embedding the multi-scale spatial interaction into the transition rule system of cellular automata (CA). A system dynamic model was used to predict the demand for new urban land at an aggregated urban agglomeration area scale. A data field approach was adopted to measuring the interaction of intercity at city scale. Neighborhood interaction was interpreted with a logistic regression method at the land parcel scale. Land use data from 1995, 2005, and 2015 were used to calibrate and evaluate the model. The simulation results show that there has been continuing urban growth in the Wuhan urban agglomeration area from 1995 to 2020. Although extension-sprawl was the predominant pattern of urban spatial expansion, the trend of extensive growth to intensive growth is clear during the entire period. The spatial interaction among these cities has been reinforced, which guided the collaborative development and formed the regional urban system network.

Mixed-use development is theoretically considered to enhance the residential value of an area. However, limited empirical research has focused on European and North American cities. HOPSCA is a real estate project that integrates hotels, offices, parks, shopping malls, conference centers, and apartments. As an important mixed-use development project in Chinese cities, HOPSCA is designed to improve the quality of urban life and to enhance the residential value of an area. Few studies have explicitly examined the effect of HOPSCA on residential property values, let alone linked this question to particular types of HOPSCA. To bridge this research gap, we selected Wuhan City in China as a case study to explore the effects of HOPSCA on residential property values. Specifically, we used the potential model to quantify the effects of HOPSCA and used the geographically weighted regression (GWR) method to estimate the relationship between HOPSCA variables and residential property values. The results are as follows: (1) the effects of HOPSCA on residential property values are statistically significant with positive and negative effects. The balanced-development HOPSCA generated the greatest effects, with the highest premium of 10.76% placed on residential properties. Moderate price premiums of 3.57% and 1.83% were generated under the influence of the commerce-oriented HOPSCA and housing-oriented HOPSCA, respectively. By contrast, the business-oriented HOPSCA exerted a negative effect on residential property (−2.43%). (2) Significant spatial heterogeneity exists on the effect of HOPSCA on residential property values. The results showed that the influence of different types of HOPSCA, viz. the higher the compatibility between the HOPSCA type and the socioeconomic context of Wuhan, the higher the premium captured by residential properties within the city areas. HOPSCA benefits the improvement of the quality of urban life, which promotes urban development. For policy makers and real estate developers, our findings suggest that matching the development types and the spatial layouts of HOPSCA with the regional socioeconomic contexts is critical for enhancing the value performance of such projects.

Farmland protection in China is facing multiple pressures, including urbanization, population growth and ecological degradation. Primary farmland zoning was introduced as a basic state policy to ensure national food security. Previous studies about “primary farmland zoning” have always taken the factors as global linear variables, neglecting the spatial heterogeneity of the study areas. Based on the Development Priority Zoning (DPZ) strategy, we present a zoning approach using Bayesian networks (BNs) for considering regional differences. The networks were developed using quantitative biophysical and economic variables from multi-scale and historical change data of farmland. The simulated results substantiate that this method can ensure the agricultural quality, stability and connectivity of primary farmland. Furthermore, it can further optimize the spatial allocation of primary farmland to meet the development conditions and trends of different sub-regions, promoting the balance between the farmland protection, urban development and ecological protection of certain regions.

As a complex symbiosis, a reasonable industrial structure of each symbiotic unit within an urban agglomeration (UA) is crucial to the sustainable development of the regional economy. In an urban agglomeration (UA), a reasonable industrial structure is crucial to the sustainable development of the regional economy. This paper comprehensively considers the industrial total factor productivity (TFP) and the industrial spatial linkages between cities to adjust the industrial structure. Malmquist index (MI) is introduced to assess the industry performance in this paper to judge the development status of the industry. The calculation method for identifying industrial structure similarity is improved by combining it with industrial spatial linkages, to accurately reflect the degree of industrial structure convergence in the UA and to recognize which cities need industrial adjustment. The results from a case study on Wuhan UA showed that the method proposed in this paper can provide objective and specific suggestions for every industrial sector in each member city of the UA on a regional scale, so that the city can give priority to the developing industry with a certain foundation on the premise of avoiding the low resource allocation efficiency.