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Article: Built environment determinants of bicycle volume: A longitudinal analysis

TitleBuilt environment determinants of bicycle volume: A longitudinal analysis
Authors
Issue Date2017
PublisherUniversity of Minnesota, Department of Civil, Environmental, and Geo-Engineering. The Journal's web site is located at https://www.jtlu.org/index.php/jtlu
Citation
Journal of Transport and Land Use, 2017, v. 10 n. 1, p. 655-674 How to Cite?
AbstractThis study examines determinants of bicycle volume in the built environment with a five-year bicycle count dataset from Seattle, Washington. A generalized linear mixed model (GLMM) is used to capture the bicycle volume change over time while controlling for temporal autocorrelations. The GLMM assumes that bicycle count follows a Poisson distribution. The model results show that (1) the variables of non-winter seasons, peak hours, and weekends are positively associated with the increase of bicycle counts over time; (2) bicycle counts are fewer in steep areas; (3) bicycle counts are greater in zones with more mixed land use, a higher percentage of water bodies, or a greater percentage of workplaces; (4) the increment of bicycle infrastructure is positively associated with the increase of bicycle volume; and (5) bicycling is more popular in neighborhoods with a greater percentage of whites and younger adults. It concludes that areas with a smaller slope variation, a higher employment density, and a shorter distance to water bodies encourage bicycling. This conclusion suggests that to best boost bicycling, decision-makers should consider building more bicycle facilities in flat areas and integrating the facilities with employment densification and open-space creation and planning.
Persistent Identifierhttp://hdl.handle.net/10722/245905
ISSN
2017 Impact Factor: 2.058
2015 SCImago Journal Rankings: 0.651
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChen, P-
dc.contributor.authorZhou, J-
dc.contributor.authorSun, F-
dc.date.accessioned2017-09-18T02:18:57Z-
dc.date.available2017-09-18T02:18:57Z-
dc.date.issued2017-
dc.identifier.citationJournal of Transport and Land Use, 2017, v. 10 n. 1, p. 655-674-
dc.identifier.issn1938-7849-
dc.identifier.urihttp://hdl.handle.net/10722/245905-
dc.description.abstractThis study examines determinants of bicycle volume in the built environment with a five-year bicycle count dataset from Seattle, Washington. A generalized linear mixed model (GLMM) is used to capture the bicycle volume change over time while controlling for temporal autocorrelations. The GLMM assumes that bicycle count follows a Poisson distribution. The model results show that (1) the variables of non-winter seasons, peak hours, and weekends are positively associated with the increase of bicycle counts over time; (2) bicycle counts are fewer in steep areas; (3) bicycle counts are greater in zones with more mixed land use, a higher percentage of water bodies, or a greater percentage of workplaces; (4) the increment of bicycle infrastructure is positively associated with the increase of bicycle volume; and (5) bicycling is more popular in neighborhoods with a greater percentage of whites and younger adults. It concludes that areas with a smaller slope variation, a higher employment density, and a shorter distance to water bodies encourage bicycling. This conclusion suggests that to best boost bicycling, decision-makers should consider building more bicycle facilities in flat areas and integrating the facilities with employment densification and open-space creation and planning.-
dc.languageeng-
dc.publisherUniversity of Minnesota, Department of Civil, Environmental, and Geo-Engineering. The Journal's web site is located at https://www.jtlu.org/index.php/jtlu-
dc.relation.ispartofJournal of Transport and Land Use-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleBuilt environment determinants of bicycle volume: A longitudinal analysis-
dc.typeArticle-
dc.identifier.emailZhou, J: zhoujp@hku.hk-
dc.identifier.authorityZhou, J=rp02236-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.5198/jtlu.2017.892-
dc.identifier.hkuros278136-
dc.identifier.volume10-
dc.identifier.issue1-
dc.identifier.spage655-
dc.identifier.epage674-
dc.identifier.isiWOS:000404406500036-
dc.publisher.placeUnited States-

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