Differences in Resilience of Urban Communities under Disaster Disturbance: Case Study of Kunming, China

Qisheng Wang et al.

Journal of Urban Planning and Development2026https://doi.org/10.1061/jupddm.upeng-5740article
ABDC B
Weight
0.50

What the paper says

In the context of global climate change and rapid urban expansion, enhancing community resilience has become a key concern in urban disaster risk reduction. However, the contributing factors and their interaction mechanisms remain insufficiently understood. This study proposes the EISFS-BRIC framework, incorporating economic, institutional, social, facility, and spatial dimensions, to assess community resilience. Applying this framework to 15 communities in Jinbi Street, Kunming, China, resilience levels were quantified using GIS methods. A coupling coordination degree model evaluated the mutual influences among dimensions, while an obstacle degree model diagnosed key barriers. The results indicate that community resilience values range from 0.29 to 0.47, with modernization not necessarily leading to higher resilience. Public spaces, infrastructure, and building plot ratios were identified as major influencing factors. Moreover, the coordination among subsystems and community organizational structures significantly affects overall resilience. This study provides a scientific basis for disaster risk reduction strategies and resilience enhancement in urban communities.

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https://doi.org/https://doi.org/10.1061/jupddm.upeng-5740

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@article{qisheng2026,
  title        = {{Differences in Resilience of Urban Communities under Disaster Disturbance: Case Study of Kunming, China}},
  author       = {Qisheng Wang et al.},
  journal      = {Journal of Urban Planning and Development},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1061/jupddm.upeng-5740},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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