IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/kwbdz.html
   My bibliography  Save this paper

Understanding Urban Traffic Flows in Response to COVID-19 Pandemic with Emerging Urban Big Data in Glasgow

Author

Listed:
  • Li, Yue
  • Wang, Mingshu
  • Zhao, Qunshan

Abstract

With the global pandemic significantly changing people’s travel behaviours, urban traffic analysis has played an even more important role in urban (re)development, providing insights for urban planning, traffic management, and resource allocation. This research uses the spatial Durbin model to understand the relationship between traffic flows, urban infrastructure, and socio-demographic indicators before, during, and after pandemic periods. We analyze factors including road characteristics, socio-demographics, surrounding built environments, and Google Street View images to understand their influences on traffic flows. In Glasgow, we have found that areas with more young and white dwellers are associated with higher traffic flows, while green spaces are associated with fewer traffic flows. The application of Google Street View images has revealed the heterogeneous effects of the built environment on urban traffic flows, as the magnitudes of their effects vary by distance. With the influence of COVID-19, residents prefer to spend their daily life in their local areas rather than having long-distance travel in the pre-pandemic time. With this noticeable travel behaviour change, the promotion and development of the 15 or 20-minute neighbourhood concept can play an important role in encouraging active travel and achieving a net-zero carbon target in the near future.

Suggested Citation

  • Li, Yue & Wang, Mingshu & Zhao, Qunshan, 2023. "Understanding Urban Traffic Flows in Response to COVID-19 Pandemic with Emerging Urban Big Data in Glasgow," OSF Preprints kwbdz, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:kwbdz
    DOI: 10.31219/osf.io/kwbdz
    as

    Download full text from publisher

    File URL: https://osf.io/download/64c279ce684bcc009020482c/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/kwbdz?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. J. Paul Elhorst, 2014. "Spatial Panel Data Models," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 37-93, Springer.
    2. Bai, Jushan & Li, Kunpeng, 2013. "Spatial panel data models with common shocks," MPRA Paper 52786, University Library of Munich, Germany, revised 09 Mar 2014.
    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. Gallaher, Adam & Graziano, Marcello & Fiaschetti, Maurizio, 2021. "Legacy and shockwaves: A spatial analysis of strengthening resilience of the power grid in Connecticut," Energy Policy, Elsevier, vol. 159(C).
    2. Shuai Shi & Kathy Pain, 2020. "Investigating China’s Mid-Yangtze River economic growth region using a spatial network growth model," Urban Studies, Urban Studies Journal Limited, vol. 57(14), pages 2973-2993, November.
    3. Valente, Thomas W. & Pitts, Stephanie & Wipfli, Heather & Vega Yon, George G., 2019. "Network influences on policy implementation: Evidence from a global health treaty," Social Science & Medicine, Elsevier, vol. 222(C), pages 188-197.
    4. Muriuki, James & Hudson, Darren & Fuad, Syed & March, Raymond J. & Lacombe, Donald J., 2023. "Spillover effect of violent conflicts on food insecurity in sub-Saharan Africa," Food Policy, Elsevier, vol. 115(C).
    5. Wang, Chao & Lim, Ming K. & Zhang, Xinyi & Zhao, Longfeng & Lee, Paul Tae-Woo, 2020. "Railway and road infrastructure in the Belt and Road Initiative countries: Estimating the impact of transport infrastructure on economic growth," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 288-307.
    6. Ul-Durar, Shajara & De Sisto, Marco & Arshed, Noman & Naveed, Shabana & Farooqi, Madiha Rehman, 2024. "FinTech adoption in achieving ecologically sustainable mineral management in Asian OBOR countries – A cross-section and time autoregressive robust analysis," Resources Policy, Elsevier, vol. 91(C).
    7. Wang, Chao & Zhang, Xinyi & Ghadimi, Pezhman & Liu, Qian & Lim, Ming K. & Stanley, H. Eugene, 2019. "The impact of regional financial development on economic growth in Beijing–Tianjin–Hebei region: A spatial econometric analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 635-648.
    8. Yanyang Yan & Zhichao Wu, 2020. "Regional innovation distribution and its dynamic evolution: Policy impact and spillover effect—Based on the perspective of innovation motivation," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-29, July.
    9. Jingjing Gao & Gabriela A. Gallegos & Joe F. West, 2023. "Public Health Policy, Political Ideology, and Public Emotion Related to COVID-19 in the U.S," IJERPH, MDPI, vol. 20(21), pages 1-14, October.
    10. Cebula, Richard J., 2022. "Coal Mining, Health, and Morbidity: A Brief Overview of the Empirical Scholarly Literature from a Regional Science Perspective," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 52(01), October.
    11. Cynthia Fan Yang, 2021. "Common factors and spatial dependence: an application to US house prices," Econometric Reviews, Taylor & Francis Journals, vol. 40(1), pages 14-50, January.
    12. Rendao Ye & Yue Qi & Wenyan Zhu, 2023. "Impact of Agricultural Industrial Agglomeration on Agricultural Environmental Efficiency in China: A Spatial Econometric Analysis," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    13. Skevas, Ioannis, 2020. "Inference in the spatial autoregressive efficiency model with an application to Dutch dairy farms," European Journal of Operational Research, Elsevier, vol. 283(1), pages 356-364.
    14. Iacopo Odoardi & Donatella Furia & Piera Cascioli, 2021. "Can social support compensate for missing family support? An examination of dropout rates in Italy," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 121-139, February.
    15. Cheng, Muxi & McCarl, Bruce A. & Fei, Chengcheng, 2021. "Climate Change Effects on the U.S. Hog production," 2021 Annual Meeting, August 1-3, Austin, Texas 313966, Agricultural and Applied Economics Association.
    16. Liang, Cong & Hui, Eddie C.M. & Yip, Tsz Leung, 2018. "Time on market (TOM): The impact of new residential stamp duty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1117-1130.
    17. Mewes, Lars & Broekel, Tom, 2022. "Technological complexity and economic growth of regions," Research Policy, Elsevier, vol. 51(8).
    18. Mauricio Sarrias, 2020. "Random Parameters and Spatial Heterogeneity using Rchoice in R," REGION, European Regional Science Association, vol. 7, pages 1-19.
    19. Zhichun Yu & Yanjiao Wan, 2023. "Can the Growth of the Digital Economy Be Beneficial for Urban Decarbonization? A Study from Chinese Cities," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    20. Maurizio Malpede & Soheil Shayegh, 2022. "Staying home saves lives, really!," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 637-651, December.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:osfxxx:kwbdz. 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.