Association between built environment characteristics and metro usage at station level with a big data approach
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 38-49 |
Journal / Publication | Travel Behaviour and Society |
Volume | 28 |
Online published | 1 Mar 2022 |
Publication status | Published - Jul 2022 |
Link(s)
Abstract
Transit-oriented development (TOD) planning strategy has been widely implemented worldwide to formulate dense, mixed-use built environment in the past three decades. The primary goal of TOD is to promote public transit usage including both transit mode share and ridership. Research supports that built environment characteristics around metro stations affect residents' travel behaviors and metro usage. However, the evidence remains inconsistent in different urban contexts. Furthermore, research focusing on mode share such as commuting trips at station level is still scarce. In this study, a rule-based model was used to identify commuting trips using metro service with smart card data (SCD), covering more than 90 percent of all metro passengers in Wuhan, China. Built environment characteristics around metro stations were measured with a 3Ds framework (density, diversity, and design). Results suggest that population density is negatively associated with metro commuting mode share, while street intersection shows a positive relationship. Office-oriented urban function and street intersection are positively correlated with metro ridership. Hence, exploring the fine-grained relationship of metro usage and built environment factors around transit stations in different urban and social contexts warrants further research attention.
Research Area(s)
- Built environment, Commuting, Mode share, Smart card data, TOD outcomes, Transit-oriented development
Citation Format(s)
Association between built environment characteristics and metro usage at station level with a big data approach. / Chen, Long; Lu, Yi; Liu, Yanfang; Yang, Linchuan; Peng, Mingjun; Liu, Yaolin.
In: Travel Behaviour and Society, Vol. 28, 07.2022, p. 38-49.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review