摘要
武汉是国内遭受新型冠状病毒肺炎疫情冲击最为严重的城市,本文基于武汉中心城区的确诊病例数据,对确诊小区地理位置信息进行空间化处理,利用核密度分析对COVID-19感染人群的空间分布进行估计,分析武汉中心城区的疫情分布及扩散程度。在此基础上,对研究区域进行网格化处理,运用多尺度地理加权回归模型分析了疫情与社会人口、城市形态、城市设施、城市功能等空间风险因素的关联性,揭示了这些因素的效应、影响范围和空间异质性。通过对这些空间风险因素的分析和验证,有利于在未来采取有效的城市规划和建筑设计应对手段,制定更加科学合理的防治措施。
Wuhan is the city that was hit hardest by the COVID-19 epidemic.Based mainly on the data of confirmed cases in the central urban area of Wuhan,this paper comprehensively analyzes the distribution and spread of the epidemic in the central urban area of Wuhan by spatially processing the geographic location information of confirmed communities and using kernel density analysis to estimate the spatial distribution of the infected people.On this basis,the paper explores the correlation between the epidemic and spatial risk factors,such as population,urban morphology,urban facilities,and urban functions through subdividing the study area into uniform grids and based on the multi-scale geographically weighted regression model.It reveals the effects,scope of influence,and spatial heterogeneity of these factors,and proposes corresponding urban planning suggestions for future response to such public health emergencies.Through the analysis and verification of these spatial risk factors,it contributes to adopting effective urban planning and architectural design countermeasures in the future,and helps formulate more scientific and reasonable prevention measures.
作者
李欣
周林
贾涛
刘斐旸
邹宇量
LI Xin;ZHOU Lin;JIA Tao;LIU Feiyang;ZOU Yuliang
出处
《城市规划》
CSSCI
CSCD
北大核心
2021年第8期78-86,共9页
City Planning Review
基金
国家自然科学基金面上项目:“基于集成信息技术的老旧社区复合环境宜居效能机制研究”(52078388)
“轨迹数据驱动的人类移动模式与多层网络社区结构研究”(41971332)。
关键词
公共卫生突发事件
新冠肺炎
空间分析
城市空间因素
地理加权模型
public health emergency
COVID-19
spatial analysis
urban space factors
geographically weighted regression
