自然资源学报 ›› 2021, Vol. 36 ›› Issue (9): 2368-2381.doi: 10.31497/zrzyxb.20210914

• 国土空间安全的规划方法创新 • 上一篇    下一篇

灾害风险视角下的城市安全评估及其驱动机制分析——以滁州市中心城区为例

杨海峰, 翟国方()   

  1. 南京大学建筑与城市规划学院,南京 210093
  • 收稿日期:2020-07-03 修回日期:2021-04-02 出版日期:2021-09-28 发布日期:2021-09-15
  • 通讯作者: 翟国方(1964- ),男,江苏江阴人,博士,教授,研究方向为城市与区域规划、城市灾害风险综合评估、空间规划与城市安全。E-mail: guofang_zhai@nju.edu.cn
  • 作者简介:杨海峰(1994- ),男,安徽安庆人,博士研究生,研究方向为城市灾害风险评估、生态安全。
  • 基金资助:
    日本学术振兴会项目(18K03022)

Spatial assessment and driving mechanism of urban safety from the perspective of disaster risk:A case study of Chuzhou central city

YANG Hai-feng, ZHAI Guo-fang()   

  1. School of Architecture and Planning, Nanjing University, Nanjing 210093, China
  • Received:2020-07-03 Revised:2021-04-02 Online:2021-09-28 Published:2021-09-15

摘要:

全球自然灾害以及城市化进程中的人为灾害频发,严重制约着城市的生存和安全发展。以典型的灾害多发地区滁州市中心城区为例,基于压力—状态—响应(Pressure-State-Response,PSR)概念框架,构建了各单灾种风险评价指标体系,利用耦合激励模型复合单灾种风险评估结果,定量测度了研究区的城市安全风险分布特征,并运用地理探测器对城市安全风险进行了驱动机制分析。结果表明:(1)研究区的城市安全风险等级占比从低到高分别为2.49%、8.71%、41.08%、30.47%和17.25%,以中风险占主导。在空间上,城市安全风险表现为中部高于周围边缘区域,呈现出由核心区往外逐步减弱的格局特征。(2)6个驱动因子对城市安全风险的解释力强度为人口密度(0.404)>地均GDP(0.402)>建筑承灾能力(0.095)>植被覆盖度(0.078)>路网密度(0.013)>用地类型风险(0.012),因子交互协同作用后对结果的解释力增强。研究结果为城市安全风险评估提供了新的理论视角与研究框架,能够服务于高风险区域的灾害风险管理。

关键词: 城市安全风险, PSR框架, 耦合激励模型, 地理探测器, 驱动机制, 滁州市中心城区

Abstract:

The frequent occurrence of natural and man-made disasters in the process of urbanization has seriously restricted the survival and safe development of cities. We used Chuzhou central city, one of the representative disaster prone areas, as a case study to measure safety risk. We constructed a safety risk index system, based on a typical Pressure-State-Response (PSR) conceptual framework. We then used coupling indication model to compound the risk assessment results of each single disaster, and quantitatively evaluated the distribution characteristic of urban safety risk. Finally, we used geographic detector to analyse the impact mechanism of the driving indicators of urban safety risk. We found that: (1) The proportions of urban safety risk grades from low to high were 2.49%, 8.71%, 41.08%, 30.47% and 17.25%, respectively, with medium risk dominating the study area. Spatially, the safety risk of central area was higher than that of the surrounding areas, that is to say, it showed a declining trend from the central city to the suburbs. (2) The order of the explanatory power intensity of the driving indicators on the safety risk was as follows: population density (0.404) > GDP density (0.402) > building disaster tolerance (0.095) > vegetation coverage (0.078) > road network density (0.013) > risk of land use type (0.012), and the explanatory power of the results was enhanced by interaction of factors. The research will provide a new theoretical perspective and framework for urban safety risk assessment, and help for disaster risk management in high risk areas.

Key words: urban safety risk, PSR framework, coupling indication model, geographic detector, driving mechanism, Chuzhou central city