解除封锁:从伦敦公共交通需求复苏中衡量空间弹性

Chen Zhong, Divya Sharma, H. Wong
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引用次数: 1

摘要

新冠肺炎大流行的破坏性影响迅速改变了个人在城市中的出行方式。各国政府担心,未来出行行为将转向汽车驾驶和在家办公,从而将需求从公共交通的使用转移。这些担忧将公共交通的复苏置于可能的危机之中。从恢复力的角度来看,可能有助于围绕复苏展开讨论,尤其是偏离疫情前行为的讨论。本文对伦敦的公共交通需求进行了实证研究,并在现有的疫情后公共交通需求研究中引入了空间弹性的观点。这项研究将空间弹性定义为封锁限制解除后一段时间内人口普查范围内公共交通需求的恢复率。通过全球空间回归模型和地理加权回归(GWR)模型的局部视角,研究了空间弹性与城市社会经济因素之间的关系。在这项针对伦敦的案例研究中,分析的重点是第一次新冠肺炎封锁限制措施解除后(2020年6月)到2020年9月中旬新限制措施之前的时间段。分析表明,伦敦外围地区的复苏速度普遍快于伦敦内部地区。研究发现,收入、汽车保有量和公共交通基础设施密度等因素对弹性的空间模式影响最大。此外,有影响力的关系在当地各不相同,这就需要未来的研究来检验这种空间异质性的驱动因素。因此,这项研究建议交通政策制定者了解在家工作的影响,确保为最低水平的服务提供资金,并倡导疫情后的多中心复苏。
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Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery
The disruptive effects of the COVID-19 pandemic has rapidly shifted how individuals navigate in cities. Governments are concerned that travel behavior will shift toward a car-driven and homeworking future, shifting demand away from public transport use. These concerns place the recovery of public transport in a possible crisis. A resilience perspective may aid the discussion around recovery – particularly one that deviates from pre-pandemic behavior. This paper presents an empirical study of London’s public transport demand and introduces a perspective of spatial resilience to the existing body of research on post-pandemic public transport demand. This study defines spatial resilience as the rate of recovery in public transport demand within census boundaries over a period after lockdown restrictions were lifted. The relationship between spatial resilience and urban socioeconomic factors was investigated by a global spatial regression model and a localized perspective through Geographically Weighted Regression (GWR) model. In this case study of London, the analysis focuses on the period after the first COVID-19 lockdown restrictions were lifted (June 2020) and before the new restrictions in mid-September 2020. The analysis shows that outer London generally recovered faster than inner London. Factors of income, car ownership and density of public transport infrastructure were found to have the greatest influence on spatial patterns in resilience. Furthermore, influential relationships vary locally, inviting future research to examine the drivers of this spatial heterogeneity. Thus, this research recommends transport policy-makers capture the influences of homeworking, ensure funding for a minimum level of service, and advocate for a polycentric recovery post-pandemic.
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