Analyzing industry ecological sustainability from the perspective of spatial association network: A case study of the urban agglomeration in the middle reaches of the Yangtze River
Weifeng Deng, Shuoshuo Li, Guoen Wei, Ling Bai, Yaobin Liu
Abstract
• The industrial ecological sustainability (IES) index was constructed based on three subsystems: industrial development, resource and environment, and ecological protection. • The fluctuating upward trend and spatial inequality characteristic of IES in Chinese urban agglomeration was investigated. • The spatial correlation network of IES in UAMRYR exhibits a “multi-polar and multi-thread” structure, driven mainly by intra-cluster linkages. • The evolution of spatial correlation network of IES is influenced by a combination of stability factors and stage-specific factors. As zones of intensive human activity overlap with ecologically sensitive areas, human-land conflict in urban agglomerations becomes more pronounced. This highlights the need to balance industrial development with ecological protection. This study constructs an industrial ecological sustainability (IES) index based on three subsystems: industrial development, resource-environment, and ecological protection. Using the Urban Agglomeration in the Middle Reaches of the Yangtze River (UAMRYR) as a case, we analyze the spatial–temporal patterns and spatial correlation network of IES, identifying the mechanisms driving these linkages. Firstly, from 2005 to 2020, the UAMRYR’s IES level showed a fluctuating upward trend, with spatial inequality manifesting as lower levels in the northwest and higher levels in the southeast. Leading areas of IES expanded from the southeast to the northwest, while lagging areas gradually decreased. Secondly, the spatial correlation network of IES in UAMRYR exhibits a “multi-polar and multi-thread” structure, driven mainly by intra-cluster linkages. The IES correlation intensity decreases as the distance from core cities increases. The network forms three types of blocks: bidirectional spillover, net beneficiary, and net spillover. The net beneficiary block is typically located in economically advanced areas that lead the network. Third, the spatial correlation network of IES is influenced by stable factors like geographical proximity and land use intensity differences and green innovation levels differences. It is also influenced by periodic factors such as economic development levels differences, urbanization rates differences, and energy consumption intensity differences.