IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v126y2025ics0966692325001097.html
   My bibliography  Save this article

COVID-era built environment and travel: Insights from location-based services data

Author

Listed:
  • Kane, Kevin
  • Zheng, Huixin

Abstract

This study revisits the linkage between land use interventions and travel behavior in the COVID era using increasingly available cell phone-based individual mobility data. Reducing the carbon emissions associated with personal vehicle travel is crucial to achieving climate targets; policies such as California's Senate Bill 375 require that land use planning achieve climate targets at the regional level. The implementation relies heavily on local placemaking efforts such as higher density infill development and walkable streets which have long been considered potential reducers of automobile travel. However, the rise of telework, decline of transit, and increase in pedestrian deaths following the pandemic have cast doubts on the efficacy and cost-effectiveness of strategies seeking to foster low-Vehicle Miles Traveled (VMT) location patterns. This study uses StreetLight Insight data on vehicle trip origination at the census tract-level before and after the emergence of COVID-19 (2019 and 2021) to assess the contribution of several built environment measures to VMT and to the share of short trips in the 6-county Southern California region. Despite concerns over COVID-induced changes, we find that several built environment measures remain solidly associated with travel efficiency in multivariate models investigating VMT levels, VMT rebound, and the share of trips that are shorter than two miles. While the prevalence of neighborhood-scale destinations is an activity generator, it also fosters shorter trips, and a region-level measure of job accessibility provides some evidence that more populated areas nearer the region's core did indeed struggle to return to pre-COVID activity levels. After the first year of the pandemic, VMT rebound was most pronounced in tracts with a high share of residents under the age of 18, suggesting that while many adults did not return to prior activity patters (e.g. due to telecommuting), children mostly did. Findings suggest that local policies and placemaking efforts, including 15-minute communities, may still be promising trip reducers, while near real-time data provides a mechanism for far faster performance evaluation.

Suggested Citation

  • Kane, Kevin & Zheng, Huixin, 2025. "COVID-era built environment and travel: Insights from location-based services data," Journal of Transport Geography, Elsevier, vol. 126(C).
    • Handle: RePEc:eee:jotrge:v:126:y:2025:i:c:s0966692325001097
    DOI: 10.1016/j.jtrangeo.2025.104218
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692325001097
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2025.104218?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Duco Vos & Evert Meijers & Maarten Ham, 2018. "Working from home and the willingness to accept a longer commute," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 61(2), pages 375-398, September.
    2. Mark R. Stevens, 2017. "Does Compact Development Make People Drive Less?," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(1), pages 7-18, January.
    3. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    4. LEE, Sungwon & LEE, Bumsoo, 2020. "Comparing the impacts of local land use and urban spatial structure on household VMT and GHG emissions," Journal of Transport Geography, Elsevier, vol. 84(C).
    5. Arjun Ramani & Nicholas Bloom, 2021. "The Donut Effect of Covid-19 on Cities," NBER Working Papers 28876, National Bureau of Economic Research, Inc.
    6. Allen J. Scott, 1997. "The Cultural Economy of Cities," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 21(2), pages 323-339, June.
    7. van Wee, Bert, 2011. "Evaluating the impact of land use on travel behaviour: the environment versus accessibility," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1530-1533.
    8. Georgia Pozoukidou & Zoi Chatziyiannaki, 2021. "15-Minute City: Decomposing the New Urban Planning Eutopia," Sustainability, MDPI, vol. 13(2), pages 1-25, January.
    9. Patrícia C. Melo, 2022. "Will COVID‐19 hinder or aid the transition to sustainable urban mobility? Spotlight on Portugal's largest urban agglomeration," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S1), pages 80-106, November.
    10. Reid Ewing & Robert Cervero, 2017. "“Does Compact Development Make People Drive Less?” The Answer Is Yes," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(1), pages 19-25, January.
    11. Fujie Rao & Yijun Kong & Ka Heng Ng & Qiyang Xie & Youyu Zhu, 2024. "Unravelling the Spatial Arrangement of the 15-Minute City: A Comparative Study of Shanghai, Melbourne, and Portland," Planning Theory & Practice, Taylor & Francis Journals, vol. 25(2), pages 184-206, March.
    12. Reid Ewing & Guang Tian & JP Goates & Ming Zhang & Michael J Greenwald & Alex Joyce & John Kircher & William Greene, 2015. "Varying influences of the built environment on household travel in 15 diverse regions of the United States," Urban Studies, Urban Studies Journal Limited, vol. 52(13), pages 2330-2348, October.
    13. Kevin Kane, 2024. "How Have American Migration Patterns Changed in the COVID Era?," Growth and Change, Wiley Blackwell, vol. 55(4), December.
    14. repec:cdl:itsdav:qt3np3p2t0 is not listed on IDEAS
    15. Choi, Kwangyul & Zhang, Ming, 2017. "The impact of metropolitan, county, and local land use on driving emissions in US metropolitan areas: Mediator effects of vehicle travel characteristics," Journal of Transport Geography, Elsevier, vol. 64(C), pages 195-202.
    16. Mark R. Stevens, 2017. "Response to Commentaries on “Does Compact Development Make People Drive Less?”," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(2), pages 151-158, April.
    17. Manville, Michael & Pinski, Miriam, 2020. "Parking behaviour: Bundled parking and travel behavior in American cities," Land Use Policy, Elsevier, vol. 91(C).
    18. Kevin Kane & Young-An Kim, 2020. "Parcels, points, and proximity: Can exhaustive sources of big data improve measurement in cities?," Environment and Planning B, , vol. 47(4), pages 695-715, May.
    19. Gehrke, Steven R. & Wang, Liming, 2020. "Operationalizing the neighborhood effects of the built environment on travel behavior," Journal of Transport Geography, Elsevier, vol. 82(C).
    20. Armita Kar & Huyen T. K. Le & Harvey J. Miller, 2022. "What Is Essential Travel? Socioeconomic Differences in Travel Demand in Columbus, Ohio, during the COVID-19 Lockdown," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 112(4), pages 1023-1046, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:cdl:itsdav:qt3h62q04h is not listed on IDEAS
    2. Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.
    3. Faizeh Hatami & Jean-Claude Thill, 2022. "Spatiotemporal Evaluation of the Built Environment’s Impact on Commuting Duration," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    4. Ding, Chuan & Cao, Xinyu (Jason) & Næss, Petter, 2018. "Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 107-117.
    5. Laviolette, Jérôme & Morency, Catherine & Waygood, E.O.D., 2022. "A kilometer or a mile? Does buffer size matter when it comes to car ownership?," Journal of Transport Geography, Elsevier, vol. 104(C).
    6. Guan, Xiaodong & Wang, Donggen, 2019. "Influences of the built environment on travel: A household-based perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 710-724.
    7. Tao, Tao & Cao, Jason, 2024. "Ineffective built environment interventions: How to reduce driving in American suburbs?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    8. Blaudin de Thé, Camille & Carantino, Benjamin & Lafourcade, Miren, 2021. "The carbon ‘carprint’ of urbanization: New evidence from French cities," Regional Science and Urban Economics, Elsevier, vol. 89(C).
    9. Aston, Laura & Currie, Graham & Kamruzzaman, Md. & Delbosc, Alexa & Teller, David, 2020. "Study design impacts on built environment and transit use research," Journal of Transport Geography, Elsevier, vol. 82(C).
    10. LEE, Sungwon & LEE, Bumsoo, 2020. "Comparing the impacts of local land use and urban spatial structure on household VMT and GHG emissions," Journal of Transport Geography, Elsevier, vol. 84(C).
    11. Tian, Guang & Ewing, Reid & Li, Han, 2023. "Exploring the influences of ride-hailing services on VMT and transit usage – Evidence from California," Journal of Transport Geography, Elsevier, vol. 110(C).
    12. Tomás Cox & Ricardo Hurtubia, 2022. "Compact development and preferences for social mixing in location choices: Results from revealed preferences in Santiago, Chile," Journal of Regional Science, Wiley Blackwell, vol. 62(1), pages 246-269, January.
    13. Liang Guo & Shuo Yang & Qinghao Zhang & Leyu Zhou & Hui He, 2023. "Examining the Nonlinear and Synergistic Effects of Multidimensional Elements on Commuting Carbon Emissions: A Case Study in Wuhan, China," IJERPH, MDPI, vol. 20(2), pages 1-28, January.
    14. repec:cdl:itsdav:qt1pf307sp is not listed on IDEAS
    15. Chetan Doddamani & M. Manoj, 2023. "Analysis of the influences of built environment measures on household car and motorcycle ownership decisions in Hubli-Dharwad cities," Transportation, Springer, vol. 50(1), pages 205-243, February.
    16. Mouratidis, Kostas & Ettema, Dick & Næss, Petter, 2019. "Urban form, travel behavior, and travel satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 306-320.
    17. Miotti, Marco & Needell, Zachary A. & Jain, Rishee K., 2023. "The impact of urban form on daily mobility demand and energy use: Evidence from the United States," Applied Energy, Elsevier, vol. 339(C).
    18. Næss, Petter & Peters, Sebastian & Stefansdottir, Harpa & Strand, Arvid, 2018. "Causality, not just correlation: Residential location, transport rationales and travel behavior across metropolitan contexts," Journal of Transport Geography, Elsevier, vol. 69(C), pages 181-195.
    19. Lin, Tao & Wang, Donggen & Guan, Xiaodong, 2017. "The built environment, travel attitude, and travel behavior: Residential self-selection or residential determination?," Journal of Transport Geography, Elsevier, vol. 65(C), pages 111-122.
    20. Bindong Sun & Rui Guo & Chun Yin, 2023. "Inequity on suburban campuses: University students disadvantaged in self‐improvement travel," Growth and Change, Wiley Blackwell, vol. 54(2), pages 404-420, June.
    21. Zhao, Juanjuan & Ren, Huan & Gu, Yan & Pan, Haojie, 2023. "Relationships between the residential environment, travel attitude and behaviour among knowledge workers: The role of job types," Journal of Transport Geography, Elsevier, vol. 106(C).
    22. Gao, Jiong & Ma, Shoufeng & Zou, Hongyang & Du, Huibin, 2023. "How does population agglomeration influence the adoption of new energy vehicles? Evidence from 290 cities in China," Technological Forecasting and Social Change, Elsevier, vol. 196(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jotrge:v:126:y:2025:i:c:s0966692325001097. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.