Urban resilience assessment and multi-scenario simulation: A case study of three major urban agglomerations in China

被引:1
|
作者
Xiao, Yi [1 ,2 ,3 ]
Yang, Haonan [2 ]
Chen, Liang [3 ,4 ]
Huang, Huan [2 ,3 ]
Chang, Ming [1 ]
机构
[1] Chengdu Univ Technol, State Key Lab Geohazard Prevent & Geoenvironm Prot, Chengdu 610059, Sichuan, Peoples R China
[2] Chengdu Univ Technol, Business Sch, Chengdu 610059, Sichuan, Peoples R China
[3] Chengdu Univ Technol, Digital Hu Line Res Inst, Chengdu 610059, Sichuan, Peoples R China
[4] Chengdu Univ Technol, Sch Environm & Civil Engn, Chengdu 610059, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Urban resilience; Critical influencing factor exploration; Scenario simulation and prediction; GTWR model; Three major urban agglomerations; GEOGRAPHICALLY WEIGHTED REGRESSION; DETERMINANTS;
D O I
10.1016/j.eiar.2024.107734
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Assessing and mitigating the adverse impacts of hazard shocks on urban is of paramount importance for cities to effectively enhance resilience and strive for sustainable development. This research employs an "EconomicEcological-Infrastructure-Social-Institutional" (EEISI) evaluation framework to assess urban resilience (UR) of three major urban agglomerations. It analyzes their coordinated development levels among subsystems, examines spatial and temporal variation characteristics of critical influencing factors, and predicts UR under various scenarios. The results show that the UR of most cities exhibits a rapid increase, and the UR of cities in the Pearl River Delta (PRD) is remarkably ahead of the rest of the urban agglomerations. The consumption level, industrial structure, emergency shelter area, and government investment in science and education play a pivotal role in UR enhancement, and there are significant dynamic fluctuations in spatial and temporal dimensions among them. Furthermore, the prediction results for UR show an overall upward trend, and the optimal growth rate for the critical influencing factors is around 2 %. In this scenario, when factors increase by 1 %, UR increases by approximately 0.1728 %. These findings will provide management with decision-making information and references for scientific planning and optimization of urban agglomerations' functional layouts.
引用
收藏
页数:23
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