Evolution and optimization of spatial structure of the Yangtze River Delta Urban Agglomeration from the perspective of coordination

Fan, Qingyu; Yang, Shengli

doi:10.31497/zrzyxb.20190802

Cited by 1 publication

(1 citation statement)

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“…However, most studies in the literature have focused on the development of the methods for ESN identification, reconstruction, and optimization (Hu et al, 2018;Kong et al, 2010;Shen, Wang, & Fu, 2014;Shi et al, 2020;Xie, Zhou, & Guan, 2014;Yin et al, 2011;Zhang, Yang, & Fath, 2010). A few studies have dealt with spatial and temporal evolution and systematic assessment of the constructed ESNs (Fan & Yang, 2019;Wang et al, 2020;Yu et al, 2018;Zhou, Lin, Ma, Qi, & Yan, 2020). In China, assessing the constructed ESNs is still at the exploratory stage by using landscape pattern index or traditional network structure index of graph theory (Liu et al, 2019;Pascual-Hortal & Saura, 2006), apparently lacking a systematic evaluation index system based on the complex network theory.…”

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confidence: 99%

Using complex network analysis to assess the ecological security network for a rapid urbanization region in China

Zhou

Lin

Yan

et al. 2021

Preprint

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A sound ecological security network (ESN) promotes the interconnection of ecological sources, improves the pattern of ecological security, and alleviates the degradation of an ecosystem. Rapid urbanization and land use changes may lead to serious fragmentation and islanding of landscape patches and further to deep disturbance of regional ESNs. However, most studies in the recent years focused on the methodological development of ESN identification, reconstruction, and optimization, but lacked the systematic assessment of the network after its construction. The purpose of this study is to use complex network analysis to systematically assess the constructed ESN for the urban agglomeration around Hangzhou (UAHB), a rapid urbanization region in China. By integrating landscape ecology theory, graph theory, and complex network analysis, we abstracted the ESN into a topological network and developed an index system to assess the abstracted network, which was based on the structural elements of the topological network (nodes, edges, and the overall network). Our results show that the connectivity and stability of the UAHB’s ESN have been improved in the last 20 years, although isolated nodes are still existing in the ESN. Our study also shows that the network’s robustness under human disturbance has been affected more than that under non-human disturbance. Finally, we proposed five optimization strategies from the perspective of topological structure and ecological function to maintain a sustainable and well-protected ecological system.

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