中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (10): 39-45.doi: 10.16265/j.cnki.issn1003-3033.2023.10.0042

• 安全社会科学与安全管理 • 上一篇    下一篇

城市综合韧性能力时空动态评估模型:以传染病为例

张雅宁1,2(), 司鹄1,2,**()   

  1. 1 煤矿灾害动力学与控制国家重点实验室,重庆 400044
    2 重庆大学 资源与安全学院,重庆 400044
  • 收稿日期:2023-04-08 修回日期:2023-07-17 出版日期:2023-10-28
  • 通讯作者:
    **司 鹄(1964—),女,重庆人,博士,教授,主要从事安全科学、工程力学以及流体力学方面的研究。E-mail:
  • 作者简介:

    张雅宁 (1998—),女,四川雅安人,硕士研究生,主要研究方向为城市公共安全风险评估。E-mail:

    司鹄 教授

  • 基金资助:
    国家自然科学基金资助(51874054)

Spatial-temporal dynamic evaluation model of urban comprehensive resilience: taking infectious diseases as an example

ZHANG Yaning1,2(), SI Hu1,2,**()   

  1. 1 State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing 400044, China
    2 School of Resources and Safety Engineering, Chongqing University, Chongqing 400044, China
  • Received:2023-04-08 Revised:2023-07-17 Published:2023-10-28

摘要:

为探究传染病背景下城市韧性因素作用机制和时空变化,从多尺度把握韧性短板,以街道为基本研究单元,采集空间数据和统计数据,构建时空动态评估模型。考虑城市韧性的承灾、抵御和恢复能力,集空间回归分析和地理探测器等方法,分阶段研究并得出显著驱动街道韧性的因素,进而量化市区与全市韧性,并以武汉市为例进行验证。结果表明:主城区的韧性能力整体低于远城区且波动程度大。全市韧性能力从较高升至高水平。从作用机制看,城市道路、高速和区域组织协调限制局域韧性能力;建成区绿化率在研究阶段与城市发展情况、区域组织协调的指标相互影响,驱动全局韧性提升。在时空角度,街道的恢复具有主导并协同其他影响因素驱动城市整体韧性回升的效果,且空间分布随时间推移趋于集中化。

关键词: 城市韧性, 综合韧性能力, 时空动态评估模型, 传染病, 地理探测器, 多尺度地理加权回归(MGWR)

Abstract:

In order to explore the action mechanism, spatial and temporal changes of urban resilience factors under the infectious diseases background, the resilience shortcomings were grasped from multiple scales. The street was taken as the basic research unit to collect spatial and statistical data to construct a spatiotemporal evaluation model. The disaster bearing, resistance and recovery ability of urban resilience were considered, and the spatial regression analysis was used to study factors that significantly drove street resilience in stages. The urban area resilience and whole city were then quantified. Wuhan was taken as an example to verify. The results show that the resilience of the main urban area is lower than that of the remote urban area, and the fluctuation range is large. The city resilience level has risen to a high level. According to the mechanism of action, local resilience is limited by urban roads, highways and regional coordination. The overall resilience is driven by the interaction of the built-up area's greening rate with the urban development and the coordination the regional organization. In terms of time and space, the overall city resilience can be dominated by street recovery and driven by other influencing factors, and the spatial distribution tends to be centralized over time.

Key words: urban resilience, comprehensive resilience capability, spatial-temporal dynamic evaluation model, infectious diseases, geographical detector, multiscale geographic weighted regression (MGWR)