Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery

ABSTRACT 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...

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Main Authors: Divya Sharma, Chen Zhong, Howard Wong
Format: Article
Language:English
Published: Taylor & Francis Group 2023-10-01
Series:Geo-spatial Information Science
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/10095020.2022.2156300
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author Divya Sharma
Chen Zhong
Howard Wong
author_facet Divya Sharma
Chen Zhong
Howard Wong
author_sort Divya Sharma
collection DOAJ
description ABSTRACT 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 policymakers 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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spelling doaj.art-9db73283d9c248faaa05c1ab7bd70e382024-02-14T12:14:19ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532023-10-0126468570210.1080/10095020.2022.2156300Lockdown lifted: measuring spatial resilience from London’s public transport demand recoveryDivya Sharma0Chen Zhong1Howard Wong2Centre for Advanced Spatial Analysis, University College London, London, UKCentre for Advanced Spatial Analysis, University College London, London, UKCentre for Advanced Spatial Analysis, University College London, London, UKABSTRACT 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 policymakers capture the influences of homeworking, ensure funding for a minimum level of service, and advocate for a polycentric recovery post-pandemic.https://www.tandfonline.com/doi/10.1080/10095020.2022.2156300Spatial resiliencedemand recoverypublic transportCOVID-19pandemicLondon
spellingShingle Divya Sharma
Chen Zhong
Howard Wong
Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery
Geo-spatial Information Science
Spatial resilience
demand recovery
public transport
COVID-19
pandemic
London
title Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery
title_full Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery
title_fullStr Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery
title_full_unstemmed Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery
title_short Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery
title_sort lockdown lifted measuring spatial resilience from london s public transport demand recovery
topic Spatial resilience
demand recovery
public transport
COVID-19
pandemic
London
url https://www.tandfonline.com/doi/10.1080/10095020.2022.2156300
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AT chenzhong lockdownliftedmeasuringspatialresiliencefromlondonspublictransportdemandrecovery
AT howardwong lockdownliftedmeasuringspatialresiliencefromlondonspublictransportdemandrecovery