广州市多维度韧性水平测度和空间格局研究

Research on Multi-Dimensional Resilience Levels and Spatial Patterns in Guangzhou City

摘要: 韧性城市将城市发展和城市公共安全结合起来，为城市转型和城市可持续发展研究提供了新的思路。以城市防灾减灾为视角，从经济韧性、社会韧性、基础设施韧性和生态韧性4个维度构建城市韧性评价体系，结合熵权法、TOPSIS模型和地理信息系统等方法，评估广州市城市多维韧性时空水平和格局。研究发现：1) 广州市各区韧性水平呈现显著空间分异，天河区综合得分最高，为高韧性区；黄埔区、越秀区、南沙区位列较高韧性层级；增城区、从化区、白云区为中等韧性；海珠区、花都区、荔湾区、番禺区属较低韧性区。2) 广州市呈现“中心强韧、周边薄弱”和灾害韧性随机分布的特征，中南部依托经济集聚与政策优势形成韧性高地，而北部及西部地区受产业结构单一、基础设施老化等因素制约。3) 韧性指标中人口密度、一般工业固体废物综合利用率和建成区绿化覆盖率影响显著。体现“人–资源–环境”是韧性提升的首要任务。

Abstract: Resilient cities integrate urban development with public safety, offering new insights for research on urban transformation and sustainable development. Against the backdrop of accelerating global climate change and urbanization, the risk of compound disasters in cities has become increasingly prominent, posing severe challenges to traditional disaster prevention models. From the perspective of disaster prevention, this study constructs an urban resilience evaluation system encompassing four dimensions: economic resilience, social resilience, infrastructure resilience, and ecological resilience. Utilizing methods such as the Entropy Weight Method, TOPSIS model, and Geographic Information System (GIS), it assesses the spatiotemporal resilience level of Guangzhou City. The research findings are as follows: 1) The resilience levels of Guangzhou’s districts exhibit significant spatial variation. Tianhe District has the highest comprehensive score, classified as a high-resilience area; Huangpu District, Yuexiu District, and Nansha District fall into the relatively high-resilience tier; Zengcheng District, Conghua District, and Baiyun District are of medium resilience; Haizhu District, Huadu District, Liwan District, and Panyu District belong to the relatively low-resilience tier. 2) Guangzhou displays a characteristic of “strong resilience in the center, weaker resilience in the periphery”, with disaster resilience showing a random distribution pattern. The central-southern region forms a resilience highland, leveraging economic agglomeration and policy advantages, while the northern and western areas are constrained by factors such as a single industrial structure and aging infrastructure. 3) Among the resilience indicators, population density, comprehensive utilization rate of general industrial solid waste, and green coverage rate of built-up areas have significant impacts. This highlights that the “people-resources-environment” nexus is the primary task for enhancing resilience.