• DocumentCode
    2990375
  • Title

    Exploring spatiotemporal characteristics of intra-urban trips using metro smartcard records

  • Author

    Yongxi Gong ; Yu Liu ; Yaoyu Lin ; Jian Yang ; Zhongyuan Duan ; Guicai Li

  • Author_Institution
    Shenzhen Grad. Sch., Sch. of Urban Planning & Manage., Harbin Inst. of Technol., Shenzhen, China
  • fYear
    2012
  • fDate
    15-17 June 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Understanding the characteristics of intra-urban trips is essential to get a deep insight of the dynamic aspects of urban system and to make urban planning. We explore the spatiotemporal patterns of human intra-urban trips using metro smartcard records of Shenzhen city. Through statistics of millions of smartcard records, we found that the intra-urban trips: (a) have two significant peak hours over day; (b) are different between weekday and weekend; and (c) have significant periodicity. The temporal patterns owe to the living and working habit of the inhabitants. The result also shows that passengers´ volumes, as well as the spatiotemporal patterns, are various for different stations, due to the land uses around stations. The method shows that metro smartcard records provide a powerful approach to understanding the dynamic of urban system.
  • Keywords
    data acquisition; data mining; geographic information systems; geophysical techniques; geophysics computing; smart cards; spatiotemporal phenomena; town and country planning; transportation; China; Shenzhen city; intraurban trips; living habit; metro smartcard records; passenger volumes; public transport; spatiotemporal characteristics; spatiotemporal patterns; urban planning; urban system; working habit; Argon; Irrigation; Sun; Transportation; intra-urban trip; public transport; smartcard record; spatiotemporal pattern;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics (GEOINFORMATICS), 2012 20th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-4673-1103-8
  • Type

    conf

  • DOI
    10.1109/Geoinformatics.2012.6270316
  • Filename
    6270316