IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v125y2019icp294-307.html
   My bibliography  Save this article

Exploring the potential of mobile phone records and online route planners for dynamic accessibility analysis

Author

Listed:
  • García-Albertos, Pedro
  • Picornell, Miguel
  • Salas-Olmedo, María Henar
  • Gutiérrez, Javier

Abstract

Big Data sources offer new possibilities for urban mobility and accessibility studies. As people carry out their activities in a city, they leave behind a digital fingerprint that can be used to analyze the population’s daily mobility patterns and determine the exact times of travel between points of origin and destination at different times of the day. These data present high spatial and temporal resolution, and enable accurate and dynamic analysis of accessibility. The objective of this study was to conduct a dynamic analysis of urban accessibility considering its two main components: travel times and the attractiveness of destinations. To this end, we calculated travel times between transport zones using the Google Maps API and constructed origin and destination (OD) travel matrices from mobile phone records. Several scenarios were generated to analyze dynamic accessibility and the separate influence of its two components. We also conducted a cluster analysis to characterize transport zones according to their accessibility in each of the scenarios and times of day considered. Our results indicate that these new sources of geolocated data show considerable potential for use in time-sensitive accessibility studies, since they yield more accurate and realistic information than static or partially dynamic analyses. Such information could help politicians take better decisions concerning transport and land use.

Suggested Citation

  • García-Albertos, Pedro & Picornell, Miguel & Salas-Olmedo, María Henar & Gutiérrez, Javier, 2019. "Exploring the potential of mobile phone records and online route planners for dynamic accessibility analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 294-307.
    • Handle: RePEc:eee:transa:v:125:y:2019:i:c:p:294-307
    DOI: 10.1016/j.tra.2018.02.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856417307292
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2018.02.008?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. Li, Qingquan & Zhang, Tong & Wang, Handong & Zeng, Zhe, 2011. "Dynamic accessibility mapping using floating car data: a network-constrained density estimation approach," Journal of Transport Geography, Elsevier, vol. 19(3), pages 379-393.
    2. Owen, Andrew & Levinson, David M., 2015. "Modeling the commute mode share of transit using continuous accessibility to jobs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 110-122.
    3. Foth, Nicole & Manaugh, Kevin & El-Geneidy, Ahmed M., 2013. "Towards equitable transit: examining transit accessibility and social need in Toronto, Canada, 1996–2006," Journal of Transport Geography, Elsevier, vol. 29(C), pages 1-10.
    4. Boisjoly, Geneviève & El-Geneidy, Ahmed, 2016. "Daily fluctuations in transit and job availability: A comparative assessment of time-sensitive accessibility measures," Journal of Transport Geography, Elsevier, vol. 52(C), pages 73-81.
    5. Miguel Picornell & Tomás Ruiz & Maxime Lenormand & José Ramasco & Thibaut Dubernet & Enrique Frías-Martínez, 2015. "Exploring the potential of phone call data to characterize the relationship between social network and travel behavior," Transportation, Springer, vol. 42(4), pages 647-668, July.
    6. Maxime Lenormand & Miguel Picornell & Oliva G Cantú-Ros & Antònia Tugores & Thomas Louail & Ricardo Herranz & Marc Barthelemy & Enrique Frías-Martínez & José J Ramasco, 2014. "Cross-Checking Different Sources of Mobility Information," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
    7. Páez, Antonio & Scott, Darren M. & Morency, Catherine, 2012. "Measuring accessibility: positive and normative implementations of various accessibility indicators," Journal of Transport Geography, Elsevier, vol. 25(C), pages 141-153.
    8. Fransen, Koos & Neutens, Tijs & Farber, Steven & De Maeyer, Philippe & Deruyter, Greet & Witlox, Frank, 2015. "Identifying public transport gaps using time-dependent accessibility levels," Journal of Transport Geography, Elsevier, vol. 48(C), pages 176-187.
    9. S L Handy & D A Niemeier, 1997. "Measuring Accessibility: An Exploration of Issues and Alternatives," Environment and Planning A, , vol. 29(7), pages 1175-1194, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andreas Dypvik Landmark & Petter Arnesen & Carl-Johan Södersten & Odd André Hjelkrem, 2021. "Mobile phone data in transportation research: methods for benchmarking against other data sources," Transportation, Springer, vol. 48(5), pages 2883-2905, October.
    2. Chen, Siyuan & Liu, Xin & Lyu, Cheng & Vlacic, Ljubo & Tang, Tianli & Liu, Zhiyuan, 2023. "A holistic data-driven framework for developing a complete profile of bus passengers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    3. Sławomir Goliszek, 2021. "GIS tools and programming languages for creating models of public and private transport potential accessibility in Szczecin, Poland," Journal of Geographical Systems, Springer, vol. 23(1), pages 115-137, January.
    4. Antonello Ignazio Croce & Giuseppe Musolino & Corrado Rindone & Antonino Vitetta, 2021. "Estimation of Travel Demand Models with Limited Information: Floating Car Data for Parameters’ Calibration," Sustainability, MDPI, vol. 13(16), pages 1-23, August.
    5. Yadan Yan & Tianzhao Guo & Dongwei Wang, 2021. "Dynamic Accessibility Analysis of Urban Road-to-Freeway Interchanges Based on Navigation Map Paths," Sustainability, MDPI, vol. 13(1), pages 1-17, January.
    6. Alina Viorica Dumitrașcu & Camelia Teodorescu & Alexandra Cioclu, 2023. "Accessibility and Tourist Satisfaction—Influencing Factors for Tourism in Dobrogea, Romania," Sustainability, MDPI, vol. 15(9), pages 1-17, May.
    7. Fielbaum, Andrés & Jara-Diaz, Sergio, 2021. "Assessment of the socio-spatial effects of urban transport investment using Google Maps API," Journal of Transport Geography, Elsevier, vol. 91(C).
    8. Helai Huang & Jialing Wu & Fang Liu & Yiwei Wang, 2020. "Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data," Sustainability, MDPI, vol. 13(1), pages 1-23, December.
    9. Shi, Yuji & Blainey, Simon & Sun, Chao & Jing, Peng, 2020. "A literature review on accessibility using bibliometric analysis techniques," Journal of Transport Geography, Elsevier, vol. 87(C).
    10. Amparo Moyano & Marcin Stępniak & Borja Moya-Gómez & Juan Carlos García-Palomares, 2021. "Traffic congestion and economic context: changes of spatiotemporal patterns of traffic travel times during crisis and post-crisis periods," Transportation, Springer, vol. 48(6), pages 3301-3324, December.
    11. Jairo Ortega & János Tóth & Tamás Péter, 2021. "A Comprehensive Model to Study the Dynamic Accessibility of the Park & Ride System," Sustainability, MDPI, vol. 13(7), pages 1-17, April.
    12. Siqi Lai & Brian Deal, 2022. "Parks, Green Space, and Happiness: A Spatially Specific Sentiment Analysis Using Microblogs in Shanghai, China," Sustainability, MDPI, vol. 15(1), pages 1-18, December.

    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. Stępniak, Marcin & Pritchard, John P. & Geurs, Karst T. & Goliszek, Sławomir, 2019. "The impact of temporal resolution on public transport accessibility measurement: Review and case study in Poland," Journal of Transport Geography, Elsevier, vol. 75(C), pages 8-24.
    2. Shixiong Jiang & Wei Guan & Zhengbing He & Liu Yang, 2018. "Measuring Taxi Accessibility Using Grid-Based Method with Trajectory Data," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    3. Helai Huang & Jialing Wu & Fang Liu & Yiwei Wang, 2020. "Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data," Sustainability, MDPI, vol. 13(1), pages 1-23, December.
    4. Moyano, Amparo & Martínez, Héctor S. & Coronado, José M., 2018. "From network to services: A comparative accessibility analysis of the Spanish high-speed rail system," Transport Policy, Elsevier, vol. 63(C), pages 51-60.
    5. Nazari Adli, Saeid & Donovan, Stuart, 2018. "Right to the city: Applying justice tests to public transport investments," Transport Policy, Elsevier, vol. 66(C), pages 56-65.
    6. Shi, Yuji & Blainey, Simon & Sun, Chao & Jing, Peng, 2020. "A literature review on accessibility using bibliometric analysis techniques," Journal of Transport Geography, Elsevier, vol. 87(C).
    7. Ryan, Jean & Pereira, Rafael H.M. & Andersson, Magnus, 2023. "Accessibility and space-time differences in when and how different groups (choose to) travel," Journal of Transport Geography, Elsevier, vol. 111(C).
    8. Boisjoly, Geneviève & El-Geneidy, Ahmed, 2016. "Daily fluctuations in transit and job availability: A comparative assessment of time-sensitive accessibility measures," Journal of Transport Geography, Elsevier, vol. 52(C), pages 73-81.
    9. Xu, Wangtu (Ato) & Li, Yongling & Wang, Hui, 2016. "Transit accessibility for commuters considering the demand elasticities of distance and transfer," Journal of Transport Geography, Elsevier, vol. 56(C), pages 138-156.
    10. Boisjoly, Geneviève & El-Geneidy, Ahmed M., 2017. "How to get there? A critical assessment of accessibility objectives and indicators in metropolitan transportation plans," Transport Policy, Elsevier, vol. 55(C), pages 38-50.
    11. Boisjoly, Geneviève & El-Geneidy, Ahmed M., 2017. "The insider: A planners' perspective on accessibility," Journal of Transport Geography, Elsevier, vol. 64(C), pages 33-43.
    12. Deboosere, Robbin & El-Geneidy, Ahmed M. & Levinson, David, 2018. "Accessibility-oriented development," Journal of Transport Geography, Elsevier, vol. 70(C), pages 11-20.
    13. Kim, Junghwan & Lee, Bumsoo, 2019. "More than travel time: New accessibility index capturing the connectivity of transit services," Journal of Transport Geography, Elsevier, vol. 78(C), pages 8-18.
    14. Allen, Jeff & Farber, Steven, 2019. "Sizing up transport poverty: A national scale accounting of low-income households suffering from inaccessibility in Canada, and what to do about it," Transport Policy, Elsevier, vol. 74(C), pages 214-223.
    15. Sharma, Gajanand & Patil, Gopal R., 2021. "Public transit accessibility approach to understand the equity for public healthcare services: A case study of Greater Mumbai," Journal of Transport Geography, Elsevier, vol. 94(C).
    16. Allen, Jeff & Farber, Steven, 2020. "Planning transport for social inclusion: An accessibility-activity participation approach," SocArXiv ap7wh, Center for Open Science.
    17. Fayyaz, S. Kiavash & Liu, Xiaoyue Cathy & Porter, Richard J., 2017. "Dynamic transit accessibility and transit gap causality analysis," Journal of Transport Geography, Elsevier, vol. 59(C), pages 27-39.
    18. Merlin, Louis A. & Hu, Lingqian, 2017. "Does competition matter in measures of job accessibility? Explaining employment in Los Angeles," Journal of Transport Geography, Elsevier, vol. 64(C), pages 77-88.
    19. Wang, Chih-Hao & Chen, Na, 2015. "A GIS-based spatial statistical approach to modeling job accessibility by transportation mode: case study of Columbus, Ohio," Journal of Transport Geography, Elsevier, vol. 45(C), pages 1-11.
    20. Beria, Paolo & Debernardi, Andrea & Ferrara, Emanuele, 2017. "Measuring the long-distance accessibility of Italian cities," Journal of Transport Geography, Elsevier, vol. 62(C), pages 66-79.

    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:transa:v:125:y:2019:i:c:p:294-307. 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: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.