Resilience Enhancement Paths Assessment Based on City Networks Synergistic Response Under Disaster Strike—A Case Study of Yangtze River Delta City Cluster

In the face of increasingly polarized disasters, interregional synergistic emergency responses have become a mainstream means of enhancing disaster response and recovery. Given the holistic and networked nature of city clusters under regional synergy, it is necessary to fully consider the balance between the overall region and individual cities when analyzing regional resilience enhancement. Taking the Yangtze River Delta (YRD) city cluster as the study area, this study proposes three resilience enhancement paths under the perspective of network synergy, including promoting the resource allocation of cities, strengthening the development of inter-city transportation systems, and improving the integration of sub-metropolitan areas. The dynamic resilience status of the whole city cluster system and each individual city under three enhancement paths are compared based on synergistic network simulation. Firstly, the optimal resilience model is for each city to allocate 60% of its resources for self-recovery and invest 40% of its resources for other recovery. Secondly, among the existing transportation planning policies, railway development will more significantly enhance YRD’s resilience. Thirdly, for the resilient impact of the integration of the six metropolitan areas, the Shanghai metropolitan area has the most significant influence.

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Publication Details

Journal
Land
Published
2025-04-01
DOI
https://doi.org/10.3390/land14040752
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
Field-Weighted Citation Impact
0.00

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Resilience Enhancement Paths Assessment Based on City Networks Synergistic Response Under Disaster Strike—A Case Study of Yangtze River Delta City Cluster

Longbin Kou, Xiao Zhang, Hanping Zhao, Ye Yang
Land
Infrastructure Resilience and Vulnerability Analysis
article

Resilience Enhancement Paths Assessment Based on City Networks Synergistic Response Under Disaster Strike—A Case Study of Yangtze River Delta City Cluster

Longbin Kou, Xiao Zhang, Hanping Zhao, Ye Yang
article en

Abstract

In the face of increasingly polarized disasters, interregional synergistic emergency responses have become a mainstream means of enhancing disaster response and recovery. Given the holistic and networked nature of city clusters under regional synergy, it is necessary to fully consider the balance between the overall region and individual cities when analyzing regional resilience enhancement. Taking the Yangtze River Delta (YRD) city cluster as the study area, this study proposes three resilience enhancement paths under the perspective of network synergy, including promoting the resource allocation of cities, strengthening the development of inter-city transportation systems, and improving the integration of sub-metropolitan areas. The dynamic resilience status of the whole city cluster system and each individual city under three enhancement paths are compared based on synergistic network simulation. Firstly, the optimal resilience model is for each city to allocate 60% of its resources for self-recovery and invest 40% of its resources for other recovery. Secondly, among the existing transportation planning policies, railway development will more significantly enhance YRD’s resilience. Thirdly, for the resilient impact of the integration of the six metropolitan areas, the Shanghai metropolitan area has the most significant influence.

LandVol. 14(4)
China Aerospace Science and Industry Corporation (China) (CN), Beijing Normal University (CN)
Chinese Academy of Sciences, Ministry of Science and Technology of the People's Republic of China, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences
Openalex Percentile: Top 93%
Infrastructure Resilience and Vulnerability Analysis
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Resilience Enhancement Paths Assessment Based on City Networks Synergistic Response Under Disaster Strike—A Case Study of Yangtze River Delta City Cluster — Longbin Kou, Xiao Zhang, et al. · Land (2025) | TGRS Research Map | TGRS