Urban commuting dynamics in response to public transit upgrades: A big data approach

Autoři: Qi-Li Gao aff001;  Qing-Quan Li aff001;  Yan Zhuang aff001;  Yang Yue aff002;  Zhen-Zhen Liu aff004;  Shui-Quan Li aff004;  Daniel Sui aff005
Působiště autorů: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, P.R. China aff001;  Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Department of Urban Informatics, School of Architecture and Urban Planning, Shenzhen University, Shenzhen, P.R. China aff002;  Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen, P.R. China aff003;  College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, P.R. China aff004;  Department of Geosciences, University of Arkansas, Fayetteville, AR, United States of America aff005
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0223650


Public transit, especially urban rail systems, plays a vital role in shaping commuting patterns. Compared with census data and survey data, large-scale and real-time big data can track the impacts of urban policy implementations at finer spatial and temporal scales. Therefore, this study proposed a multi-level analytical framework using transit smartcard data to examine urban commuting dynamics in response to rail transit upgrades. The study area was Shenzhen, one of the most highly urbanized and densely populated cities in China, which provides the opportunity to examine the effects of rail transit upgrades on commuting patterns in a rapidly developing urban context. Changes in commuting patterns were examined at three levels: city, region, and individual. At the city level, we considered the average commuting time, commuting speed, and commuting distance across the whole city. At the region level, we analyzed changes in the job accessibility of residential zones. Finally, this study evaluated the potential effects of rail transit upgrades on the jobs-housing relationship at the individual level. Difference-in-difference models were used for causal inference between rail transit upgrades and commuting patterns. In the very short term, the opening of new rail transit lines resulted in no significant changes in overall commuting patterns across the whole city; however, two effects of rail transit upgrades on commuting patterns were identified. First, rail transit upgrades enhanced regional connectivity between residential zones and employment centers, thus improving job accessibility. Second, rail transit improvement increased the commuting distances of individuals and contributed to the separation of workplaces and residences. This study provides meaningful insights into the effects of rail transit upgrades on commuting patterns.

Klíčová slova:

Census – Employment – Housing – Human mobility – Jobs – Transportation infrastructure – Urban areas – Dynamic response


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2019 Číslo 10
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