IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v70y2018icp78-90.html
   My bibliography  Save this article

Do different datasets tell the same story about urban mobility — A comparative study of public transit and taxi usage

Author

Listed:
  • Zhang, Xiaohu
  • Xu, Yang
  • Tu, Wei
  • Ratti, Carlo

Abstract

Understanding human movements and their interactions with the built environment has long been a research interest in transport geography. In recent years, two important types of urban mobility datasets — smart card transactions and taxi GPS trajectories — have been used extensively but often separately to quantify travel patterns as well as urban spatial structures. Despite the fruitful research outcomes, the relationships between different types of transport flows in the same geographic area remain poorly understood. In this research, we propose an analytical framework to compare urban mobility patterns extracted from these two data sources. Using Singapore as a case study, this research introduces a three-fold comparative analysis to understand: (1) the spatial distributions of public transit and taxi usages and their relative balance; (2) the distance decay of travel distance, and (3) the spatial interaction communities extracted from the two transport modes. The research findings reveal that the spatial distributions of travel demand extracted from the two transport modes exhibit high correlations. However, more in-depth analysis (based on rank-size distribution and log odds ratio) reveals a higher degree of spatial heterogeneity in public transit usage. The travel distance of trips from public transit decays faster than that of taxi trips, highlighting the importance of taxis in facilitating long-distance travels. Both types of trips decay much faster when travel distance is beyond 20 km, which corresponds to the average distance from the urban periphery to the center. The spatial interaction communities derived from public transit are different on weekdays and weekends, while those of taxis show similar patterns. Both transport modes yield communities that reveal the city's polycentric structure, but their differences indicate that each of the transport modes plays a specific role in connecting certain places in the city. The study demonstrates the importance of comparative data analytics to urban and transportation research.

Suggested Citation

  • Zhang, Xiaohu & Xu, Yang & Tu, Wei & Ratti, Carlo, 2018. "Do different datasets tell the same story about urban mobility — A comparative study of public transit and taxi usage," Journal of Transport Geography, Elsevier, vol. 70(C), pages 78-90.
  • Handle: RePEc:eee:jotrge:v:70:y:2018:i:c:p:78-90
    DOI: 10.1016/j.jtrangeo.2018.05.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692317307093
    Download Restriction: no

    File URL: https://libkey.io/10.1016/j.jtrangeo.2018.05.002?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. Schönfelder, Stefan & Axhausen, Kay W., 2003. "Activity spaces: measures of social exclusion?," Transport Policy, Elsevier, vol. 10(4), pages 273-286, October.
    2. Miaoyi Li & Lei Dong & Zhenjiang Shen & Wei Lang & Xinyue Ye, 2017. "Examining the Interaction of Taxi and Subway Ridership for Sustainable Urbanization," Sustainability, MDPI, vol. 9(2), pages 1-12, February.
    3. Yu Liu & Chaogui Kang & Song Gao & Yu Xiao & Yuan Tian, 2012. "Understanding intra-urban trip patterns from taxi trajectory data," Journal of Geographical Systems, Springer, vol. 14(4), pages 463-483, October.
    4. Martijn Burger & Evert Meijers, 2012. "Form Follows Function? Linking Morphological and Functional Polycentricity," Urban Studies, Urban Studies Journal Limited, vol. 49(5), pages 1127-1149, April.
    5. 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.
    6. Sun Sheng Han, 2005. "Polycentric Urban Development and Spatial Clustering of Condominium Property Values: Singapore in the 1990s," Environment and Planning A, , vol. 37(3), pages 463-481, March.
    7. Wang, Wenjun & Pan, Lin & Yuan, Ning & Zhang, Sen & Liu, Dong, 2015. "A comparative analysis of intra-city human mobility by taxi," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 134-147.
    8. Yang Xu & Shih-Lung Shaw & Ziliang Zhao & Ling Yin & Zhixiang Fang & Qingquan Li, 2015. "Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach," Transportation, Springer, vol. 42(4), pages 625-646, July.
    9. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    10. Mei-Po Kwan, 1999. "Gender, the Home-Work Link, and Space-Time Patterns of Nonemployment Activities," Economic Geography, Taylor & Francis Journals, vol. 75(4), pages 370-394, October.
    11. Yang Xu & Shih-Lung Shaw & Ziliang Zhao & Ling Yin & Feng Lu & Jie Chen & Zhixiang Fang & Qingquan Li, 2016. "Another Tale of Two Cities: Understanding Human Activity Space Using Actively Tracked Cellphone Location Data," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 106(2), pages 489-502, March.
    12. Kitamura, Ryuichi, 1984. "Incorporating trip chaining into analysis of destination choice," Transportation Research Part B: Methodological, Elsevier, vol. 18(1), pages 67-81, February.
    13. Liu, Xi & Gong, Li & Gong, Yongxi & Liu, Yu, 2015. "Revealing travel patterns and city structure with taxi trip data," Journal of Transport Geography, Elsevier, vol. 43(C), pages 78-90.
    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. Chen, Wendong & Chen, Xuewu & Cheng, Long & Liu, Xize & Chen, Jingxu, 2022. "Delineating borders of urban activity zones with free-floating bike sharing spatial interaction network," Journal of Transport Geography, Elsevier, vol. 104(C).
    2. Priscila Santin & Fernanda R. Gubert & Mauro Fonseca & Anelise Munaretto & Thiago Henrique Silva, 2020. "Characterization of Public Transit Mobility Patterns of Different Economic Classes," Sustainability, MDPI, vol. 12(22), pages 1-24, November.
    3. Zhao, Zhiyuan & Yao, Wei & Wu, Sheng & Yang, Xiping & Wu, Qunyong & Fang, Zhixiang, 2023. "Identifying the collaborative scheduling areas between ride-hailing and traditional taxi services based on vehicle trajectory data," Journal of Transport Geography, Elsevier, vol. 107(C).
    4. Song Li & Fei Xue & Chuyu Xia & Jian Zhang & Ao Bian & Yuexi Lang & Jun Zhou, 2022. "A Big Data-Based Commuting Carbon Emissions Accounting Method—A Case of Hangzhou," Land, MDPI, vol. 11(6), pages 1-18, June.
    5. Liao, Yuan, 2021. "Ride-sourcing compared to its public-transit alternative using big trip data," Journal of Transport Geography, Elsevier, vol. 95(C).
    6. Toger, Marina & Türk, Umut & Östh, John & Kourtit, Karima & Nijkamp, Peter, 2023. "Inequality in leisure mobility: An analysis of activity space segregation spectra in the Stockholm conurbation," Journal of Transport Geography, Elsevier, vol. 111(C).
    7. Zhang, Xiaohu, 2021. "Beyond expected regularity of aggregate urban mobility: A case study of ridesourcing service," Journal of Transport Geography, Elsevier, vol. 95(C).
    8. Zhang, Bin & Chen, Shuyan & Ma, Yongfeng & Li, Tiezhu & Tang, Kun, 2020. "Analysis on spatiotemporal urban mobility based on online car-hailing data," Journal of Transport Geography, Elsevier, vol. 82(C).
    9. Chen Xie & Dexin Yu & Ciyun Lin & Xiaoyu Zheng & Bo Peng, 2022. "Exploring the Spatiotemporal Impacts of the Built Environment on Taxi Ridership Using Multisource Data," Sustainability, MDPI, vol. 14(10), pages 1-24, May.
    10. Fangye Du & Jiaoe Wang & Yu Liu & Zihao Zhou & Haitao Jin, 2022. "Equity in Health-Seeking Behavior of Groups Using Different Transportations," IJERPH, MDPI, vol. 19(5), pages 1-16, February.
    11. Zhang, Shanqi & Yang, Yu & Zhen, Feng & Lobsang, Tashi & Li, Zhixuan, 2021. "Understanding the travel behaviors and activity patterns of the vulnerable population using smart card data: An activity space-based approach," Journal of Transport Geography, Elsevier, vol. 90(C).
    12. Kirtonia, Sajeeb & Sun, Yanshuo, 2022. "Evaluating rail transit's comparative advantages in travel cost and time over taxi with open data in two U.S. cities," Transport Policy, Elsevier, vol. 115(C), pages 75-87.

    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. Yang, Xiping & Fang, Zhixiang & Xu, Yang & Yin, Ling & Li, Junyi & Lu, Shiwei, 2019. "Spatial heterogeneity in spatial interaction of human movements—Insights from large-scale mobile positioning data," Journal of Transport Geography, Elsevier, vol. 78(C), pages 29-40.
    2. Fangye Du & Jiaoe Wang & Yu Liu & Zihao Zhou & Haitao Jin, 2022. "Equity in Health-Seeking Behavior of Groups Using Different Transportations," IJERPH, MDPI, vol. 19(5), pages 1-16, February.
    3. He, Zhengbing, 2020. "Spatial-temporal fractal of urban agglomeration travel demand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    4. Yang, Xiong & Zhuge, Chengxiang & Shao, Chunfu & Huang, Yuantan & Hayse Chiwing G. Tang, Justin & Sun, Mingdong & Wang, Pinxi & Wang, Shiqi, 2022. "Characterizing mobility patterns of private electric vehicle users with trajectory data," Applied Energy, Elsevier, vol. 321(C).
    5. Li, Ze-Tao & Nie, Wei-Peng & Cai, Shi-Min & Zhao, Zhi-Dan & Zhou, Tao, 2023. "Exploring the topological characteristics of urban trip networks based on taxi trajectory data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    6. Nie, Wei-Peng & Cai, Shi-Min & Zhao, Zhi-Dan & Zhou, Tao, 2022. "Revealing mobility pattern of taxi movements with its travel trajectory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    7. Zhao, Pengxiang & Kwan, Mei-Po & Qin, Kun, 2017. "Uncovering the spatiotemporal patterns of CO2 emissions by taxis based on Individuals' daily travel," Journal of Transport Geography, Elsevier, vol. 62(C), pages 122-135.
    8. Mepparambath, Rakhi Manohar & Soh, Yong Sheng & Jayaraman, Vasundhara & Tan, Hong En & Ramli, Muhamad Azfar, 2023. "A novel modelling approach of integrated taxi and transit mode and route choice using city-scale emerging mobility data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    9. Yong Gao & Jiajun Liu & Yan Xu & Lan Mu & Yu Liu, 2019. "A Spatiotemporal Constraint Non-Negative Matrix Factorization Model to Discover Intra-Urban Mobility Patterns from Taxi Trips," Sustainability, MDPI, vol. 11(15), pages 1-22, August.
    10. F. Crawford & D. P. Watling & R. D. Connors, 2023. "Analysing Spatial Intrapersonal Variability of Road Users Using Point-to-Point Sensor Data," Networks and Spatial Economics, Springer, vol. 23(2), pages 373-406, June.
    11. Rongxiang Su & Zhixiang Fang & Ningxin Luo & Jingwei Zhu, 2018. "Understanding the Dynamics of the Pick-Up and Drop-Off Locations of Taxicabs in the Context of a Subsidy War among E-Hailing Apps," Sustainability, MDPI, vol. 10(4), pages 1-24, April.
    12. Duan, Zhengyu & Zhao, Haoran & Li, Zhenming, 2023. "Non-linear effects of built environment and socio-demographics on activity space," Journal of Transport Geography, Elsevier, vol. 111(C).
    13. Kirtonia, Sajeeb & Sun, Yanshuo, 2022. "Evaluating rail transit's comparative advantages in travel cost and time over taxi with open data in two U.S. cities," Transport Policy, Elsevier, vol. 115(C), pages 75-87.
    14. Xingang Zhou & Anthony G. O. Yeh, 2021. "Understanding the modifiable areal unit problem and identifying appropriate spatial unit in jobs–housing balance and employment self-containment using big data," Transportation, Springer, vol. 48(3), pages 1267-1283, June.
    15. Chaogui Kang & Yu Liu & Diansheng Guo & Kun Qin, 2015. "A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-11, November.
    16. Lo, A. W.-T. & Houston, D., 2018. "How do compact, accessible, and walkable communities promote gender equality in spatial behavior?," Journal of Transport Geography, Elsevier, vol. 68(C), pages 42-54.
    17. Ying Ni & Jiaqi Chen, 2020. "Exploring the Effects of the Built Environment on Two Transfer Modes for Metros: Dockless Bike Sharing and Taxis," Sustainability, MDPI, vol. 12(5), pages 1-20, March.
    18. 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.
    19. Claudio Gariazzo & Armando Pelliccioni & Maria Paola Bogliolo, 2019. "Spatiotemporal Analysis of Urban Mobility Using Aggregate Mobile Phone Derived Presence and Demographic Data: A Case Study in the City of Rome, Italy," Data, MDPI, vol. 4(1), pages 1-25, January.
    20. Yue, Wenze & Wang, Tianyu & Liu, Yong & Zhang, Qun & Ye, Xinyue, 2019. "Mismatch of morphological and functional polycentricity in Chinese cities: An evidence from land development and functional linkage," Land Use Policy, Elsevier, vol. 88(C).

    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:70:y:2018:i:c:p:78-90. 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.