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Article: Monitoring Transit-served Areas with Smartcard Data: A Brisbane Case Study

TitleMonitoring Transit-served Areas with Smartcard Data: A Brisbane Case Study
Authors
Issue Date2019
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/jtrangeo
Citation
Journal of Transport Geography, 2019, v. 76, p. 265-275 How to Cite?
AbstractA city can be divided into areas that are served by transit and those that are not. In this study, the former is referred to as “transit-served areas (TSAs)”. To quantify, monitor and visualise the TSAs of the Southeast Queensland (SEQ), this study analyses half-year smartcard data between 2012 and 2013 from TransLink, the transit agency for SEQ. Four scenarios are prescribed and four corresponding metrics (the minimum, actual, random and maximum travels) are calculated, which reflect transit riders' different levels of elasticity of distance travelled (EDT) relative to the cost of travel within or between TSAs and how transit riders could possibly travel as EDT varies. The total trips generated by or attracted to TSA and the temporal and spatial variations of these metrics across days are used to monitor TSAs, especially transit trips within or between them. The results indicate that transit trips attracted to, and generated by TSA and transit trips between TSAs vary significantly over time and across space. Across the scenarios, the temporal variance tends to be larger as EDT becomes more inelastic. The above results provide useful references for decision-makers to understand better the ranges of transit demand (by TSA) across the space and time when EDT is a variable.
Persistent Identifierhttp://hdl.handle.net/10722/246384
ISSN
2017 Impact Factor: 2.699
2015 SCImago Journal Rankings: 1.734

 

DC FieldValueLanguage
dc.contributor.authorZhou, J-
dc.contributor.authorSipe, N-
dc.contributor.authorMa, Z-
dc.contributor.authorMateo-Babiano, I-
dc.contributor.authorDarchen, S-
dc.date.accessioned2017-09-18T02:27:34Z-
dc.date.available2017-09-18T02:27:34Z-
dc.date.issued2019-
dc.identifier.citationJournal of Transport Geography, 2019, v. 76, p. 265-275-
dc.identifier.issn0966-6923-
dc.identifier.urihttp://hdl.handle.net/10722/246384-
dc.description.abstractA city can be divided into areas that are served by transit and those that are not. In this study, the former is referred to as “transit-served areas (TSAs)”. To quantify, monitor and visualise the TSAs of the Southeast Queensland (SEQ), this study analyses half-year smartcard data between 2012 and 2013 from TransLink, the transit agency for SEQ. Four scenarios are prescribed and four corresponding metrics (the minimum, actual, random and maximum travels) are calculated, which reflect transit riders' different levels of elasticity of distance travelled (EDT) relative to the cost of travel within or between TSAs and how transit riders could possibly travel as EDT varies. The total trips generated by or attracted to TSA and the temporal and spatial variations of these metrics across days are used to monitor TSAs, especially transit trips within or between them. The results indicate that transit trips attracted to, and generated by TSA and transit trips between TSAs vary significantly over time and across space. Across the scenarios, the temporal variance tends to be larger as EDT becomes more inelastic. The above results provide useful references for decision-makers to understand better the ranges of transit demand (by TSA) across the space and time when EDT is a variable.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/jtrangeo-
dc.relation.ispartofJournal of Transport Geography-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleMonitoring Transit-served Areas with Smartcard Data: A Brisbane Case Study-
dc.typeArticle-
dc.identifier.emailZhou, J: zhoujp@hku.hk-
dc.identifier.authorityZhou, J=rp02236-
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.jtrangeo.2017.07.005-
dc.identifier.hkuros278133-
dc.identifier.volume76-
dc.identifier.spage265-
dc.identifier.epage275-
dc.publisher.placeUnited Kingdom-

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