IDEAS home Printed from https://ideas.repec.org/a/spr/pubtra/v14y2022i2d10.1007_s12469-022-00296-2.html
   My bibliography  Save this article

Understanding the temporal and spatial interactions between transit ridership and urban land-use patterns: an exploratory study

Author

Listed:
  • Merkebe Getachew Demissie

    (University of Calgary)

  • Lina Kattan

    (University of Calgary)

Abstract

The land-use characteristics of urban areas continually change, and thus the activity patterns of the significant trip generators evolve. Efficient public transit planning needs to perform frequent estimates of the spatio-temporal distribution and dynamics of different activities in urban areas and measure the likely consequences of changes. Automated data collection systems usually collect transit ridership data (e.g., automated passenger count (APC)). Many transit agencies also generate General Transit Feed Specification (GTFS) data and make them publicly available. This study explores the use of APC, GTFS, and land-use data to examine various land-use and transit ridership interactions at the stop, route, and zonal levels using visualization, data mining, and statistical analysis techniques. Results show that transit ridership at the bus stop level gives a better understanding of each bus stop's unique land use. Zonal-level transit ridership patterns reveal the different trip generations and attraction roles of the neighboring land usage. This study could provide additional insights on the interaction between the temporal changes in population from the perspective of transit use and the associated land uses.

Suggested Citation

  • Merkebe Getachew Demissie & Lina Kattan, 2022. "Understanding the temporal and spatial interactions between transit ridership and urban land-use patterns: an exploratory study," Public Transport, Springer, vol. 14(2), pages 385-417, June.
    • Handle: RePEc:spr:pubtra:v:14:y:2022:i:2:d:10.1007_s12469-022-00296-2
    DOI: 10.1007/s12469-022-00296-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12469-022-00296-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12469-022-00296-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gutiérrez, Javier & Cardozo, Osvaldo Daniel & García-Palomares, Juan Carlos, 2011. "Transit ridership forecasting at station level: an approach based on distance-decay weighted regression," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1081-1092.
    2. Chakour, Vincent & Eluru, Naveen, 2016. "Examining the influence of stop level infrastructure and built environment on bus ridership in Montreal," Journal of Transport Geography, Elsevier, vol. 51(C), pages 205-217.
    3. Padeiro, Miguel, 2014. "The influence of transport infrastructures on land-use conversion decisions within municipal plans," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 7(1), pages 79-93.
    4. Yu, Chang & He, Zhao-Cheng, 2017. "Analysing the spatial-temporal characteristics of bus travel demand using the heat map," Journal of Transport Geography, Elsevier, vol. 58(C), pages 247-255.
    5. Lee, Sanggu & Hickman, Mark & Tong, Daoqin, 2013. "Development of a temporal and spatial linkage between transit demand and land-use patterns," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 6(2), pages 33-46.
    6. Xianyuan Zhan & Satish Ukkusuri & Feng Zhu, 2014. "Inferring Urban Land Use Using Large-Scale Social Media Check-in Data," Networks and Spatial Economics, Springer, vol. 14(3), pages 647-667, December.
    7. Aiman Soliman & Kiumars Soltani & Junjun Yin & Anand Padmanabhan & Shaowen Wang, 2017. "Social sensing of urban land use based on analysis of Twitter users’ mobility patterns," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-16, July.
    8. James Decraene & Christopher Monterola & Gary Kee Khoon Lee & Terence Gih Guang Hung, 2013. "A Quantitative Procedure For The Spatial Characterization Of Urban Land Use," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(01), pages 1-15.
    9. Boarnet, Marlon & Crane, Randall, 2001. "The influence of land use on travel behavior: specification and estimation strategies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(9), pages 823-845, November.
    10. Deal, Brian & Schunk, Daniel, 2004. "Spatial dynamic modeling and urban land use transformation: a simulation approach to assessing the costs of urban sprawl," Ecological Economics, Elsevier, vol. 51(1-2), pages 79-95, November.
    11. Du, Hongbo & Mulley, Corinne, 2012. "Understanding spatial variations in the impact of accessibility on land value using geographically weighted regression," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(2), pages 46-59.
    12. Demissie, Merkebe Getachew & Kattan, Lina, 2022. "Estimation of truck origin-destination flows using GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    13. Liping Ge & Malek Sarhani & Stefan Voß & Lin Xie, 2021. "Review of Transit Data Sources: Potentials, Challenges and Complementarity," Sustainability, MDPI, vol. 13(20), pages 1-37, October.
    14. Koragot Kaeoruean & Santi Phithakkitnukoon & Merkebe Getachew Demissie & Lina Kattan & Carlo Ratti, 2020. "Analysis of demand–supply gaps in public transit systems based on census and GTFS data: a case study of Calgary, Canada," Public Transport, Springer, vol. 12(3), pages 483-516, October.
    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. 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).
    2. Ingvardson, Jesper Bláfoss & Nielsen, Otto Anker, 2018. "How urban density, network topology and socio-economy influence public transport ridership: Empirical evidence from 48 European metropolitan areas," Journal of Transport Geography, Elsevier, vol. 72(C), pages 50-63.
    3. Tu, Wei & Cao, Rui & Yue, Yang & Zhou, Baoding & Li, Qiuping & Li, Qingquan, 2018. "Spatial variations in urban public ridership derived from GPS trajectories and smart card data," Journal of Transport Geography, Elsevier, vol. 69(C), pages 45-57.
    4. Gao, Fan & Yang, Linchuan & Han, Chunyang & Tang, Jinjun & Li, Zhitao, 2022. "A network-distance-based geographically weighted regression model to examine spatiotemporal effects of station-level built environments on metro ridership," Journal of Transport Geography, Elsevier, vol. 105(C).
    5. Simon Berrebi & Sanskruti Joshi & Kari E Watkins, 2020. "On Ridership and Frequency," Papers 2002.02493, arXiv.org, revised Apr 2021.
    6. Karnberger, Stephan & Antoniou, Constantinos, 2020. "Network–wide prediction of public transportation ridership using spatio–temporal link–level information," Journal of Transport Geography, Elsevier, vol. 82(C).
    7. Jun, Myung-Jin & Choi, Keechoo & Jeong, Ji-Eun & Kwon, Ki-Hyun & Kim, Hee-Jae, 2015. "Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul," Journal of Transport Geography, Elsevier, vol. 48(C), pages 30-40.
    8. Zack Aemmer & Andisheh Ranjbari & Don MacKenzie, 2022. "Measurement and classification of transit delays using GTFS-RT data," Public Transport, Springer, vol. 14(2), pages 263-285, June.
    9. Diab, Ehab & Kasraian, Dena & Miller, Eric J. & Shalaby, Amer, 2020. "The rise and fall of transit ridership across Canada: Understanding the determinants," Transport Policy, Elsevier, vol. 96(C), pages 101-112.
    10. Ding, Chuan & Cao, Xinyu & Liu, Chao, 2019. "How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds," Journal of Transport Geography, Elsevier, vol. 77(C), pages 70-78.
    11. Jiaoe Wang & Yanan Li & Jingjuan Jiao & Haitao Jin & Fangye Du, 2023. "Bus ridership and its determinants in Beijing: A spatial econometric perspective," Transportation, Springer, vol. 50(2), pages 383-406, April.
    12. Su, Shiliang & Zhao, Chong & Zhou, Hao & Li, Bozhao & Kang, Mengjun, 2022. "Unraveling the relative contribution of TOD structural factors to metro ridership: A novel localized modeling approach with implications on spatial planning," Journal of Transport Geography, Elsevier, vol. 100(C).
    13. Berrebi, Simon J. & Joshi, Sanskruti & Watkins, Kari E., 2021. "On bus ridership and frequency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 140-154.
    14. Tianxing Dai & Brian D. Taylor, 2023. "Three’s a crowd? Examining evolving public transit crowding standards amidst the COVID-19 pandemic," Public Transport, Springer, vol. 15(2), pages 321-341, June.
    15. Li, Jingjing & Kim, Changjoo & Sang, Sunhee, 2018. "Exploring impacts of land use characteristics in residential neighborhood and activity space on non-work travel behaviors," Journal of Transport Geography, Elsevier, vol. 70(C), pages 141-147.
    16. Huo, Jinbiao & Liu, Chengqi & Chen, Jingxu & Meng, Qiang & Wang, Jian & Liu, Zhiyuan, 2023. "Simulation-based dynamic origin–destination matrix estimation on freeways: A Bayesian optimization approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    17. 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.
    18. Singh, Abhilash C. & Faghih Imani, Ahmadreza & Sivakumar, Aruna & Luna Xi, Yang & Miller, Eric J., 2024. "A joint analysis of accessibility and household trip frequencies by travel mode," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    19. Weiss, Adam & Habib, Khandker Nurul, 2017. "Examining the difference between park and ride and kiss and ride station choices using a spatially weighted error correlation (SWEC) discrete choice model," Journal of Transport Geography, Elsevier, vol. 59(C), pages 111-119.
    20. Pasha, Obed & Wyczalkowski, Chris & Sohrabian, Dro & Lendel, Iryna, 2020. "Transit effects on poverty, employment, and rent in Cuyahoga County, Ohio," Transport Policy, Elsevier, vol. 88(C), pages 33-41.

    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:spr:pubtra:v:14:y:2022:i:2:d:10.1007_s12469-022-00296-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.