IDEAS home Printed from https://ideas.repec.org/a/kap/jgeosy/v22y2020i4d10.1007_s10109-020-00330-6.html
   My bibliography  Save this article

A spatial data model for urban spatial–temporal accessibility analysis

Author

Listed:
  • Zhangcai Yin

    (Wuhan University of Technology)

  • Zhanghaonan Jin

    (Wuhan University of Technology)

  • Shen Ying

    (Wuhan University)

  • Sanjuan Li

    (Wuhan University of Technology)

  • Qingquan Liu

    (Wuhan University)

Abstract

Time geography represents the uncertainty of the space–time position of moving objects through two basic structures, the space–time path and space–time prism, which are subject to the speed allowed in the travel environment. Thus, any attempt at a quantitative time-geographic analysis must consider the actual velocity with respect to space. In a trip, individuals tend to pass through structurally varying spaces, such as linear traffic networks and planar walking surfaces, which are not suitable for use in a single GIS spatial data model (i.e., network, raster) that is only applicable to a single spatial structure (i.e., point, line, polygon). In this study, a velocity model is developed for a traffic network and walking surface-constrained travel environment through the divide-and-conquer principle. The construction of this model can be divided into three basic steps: the spatial layering of the dual-constrained travel environment; independent modelling of each layer using different spatial data models; and generation of layer-based time-geographic framework by merging models of each layer. We demonstrate the usefulness of the model for studying the space–time accessibility of a moving object over a study area with varying spatial structures. Finally, an example is given to analyse the effectiveness of the proposed model.

Suggested Citation

  • Zhangcai Yin & Zhanghaonan Jin & Shen Ying & Sanjuan Li & Qingquan Liu, 2020. "A spatial data model for urban spatial–temporal accessibility analysis," Journal of Geographical Systems, Springer, vol. 22(4), pages 447-468, October.
  • Handle: RePEc:kap:jgeosy:v:22:y:2020:i:4:d:10.1007_s10109-020-00330-6
    DOI: 10.1007/s10109-020-00330-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10109-020-00330-6
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10109-020-00330-6?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. 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.
    2. Tetsuo Kobayashi & Harvey Miller & Walied Othman, 2011. "Analytical methods for error propagation in planar space–time prisms," Journal of Geographical Systems, Springer, vol. 13(4), pages 327-354, December.
    3. Shelat, Sanmay & Huisman, Raymond & van Oort, Niels, 2018. "Analysing the trip and user characteristics of the combined bicycle and transit mode," Research in Transportation Economics, Elsevier, vol. 69(C), pages 68-76.
    4. Dykes, J. A. & Mountain, D. M., 2003. "Seeking structure in records of spatio-temporal behaviour: visualization issues, efforts and applications," Computational Statistics & Data Analysis, Elsevier, vol. 43(4), pages 581-603, August.
    5. Shaw, Shih-Lung & Yu, Hongbo, 2009. "A GIS-based time-geographic approach of studying individual activities and interactions in a hybrid physical–virtual space," Journal of Transport Geography, Elsevier, vol. 17(2), pages 141-149.
    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. 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.
    2. Fu, Xiao & Zuo, Yufan & Zhang, Shanqi & Liu, Zhiyuan, 2022. "Measuring joint space-time accessibility in transit network under travel time uncertainty," Transport Policy, Elsevier, vol. 116(C), pages 355-368.

    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. Shih-Lung Shaw, 2023. "Time geography in a hybrid physical–virtual world," Journal of Geographical Systems, Springer, vol. 25(3), pages 339-356, July.
    2. Chen, Jie & Shaw, Shih-Lung & Yu, Hongbo & Lu, Feng & Chai, Yanwei & Jia, Qinglei, 2011. "Exploratory data analysis of activity diary data: a space–time GIS approach," Journal of Transport Geography, Elsevier, vol. 19(3), pages 394-404.
    3. Aguiléra, Anne & Guillot, Caroline & Rallet, Alain, 2012. "Mobile ICTs and physical mobility: Review and research agenda," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 664-672.
    4. Joni A Downs & Mark W Horner, 2014. "Adaptive-Velocity Time-Geographic Density Estimation for Mapping the Potential and Probable Locations of Mobile Objects," Environment and Planning B, , vol. 41(6), pages 1006-1021, December.
    5. Gao, Jie & Kamphuis, Carlijn B.M. & Helbich, Marco & Ettema, Dick, 2020. "What is ‘neighborhood walkability’? How the built environment differently correlates with walking for different purposes and with walking on weekdays and weekends," Journal of Transport Geography, Elsevier, vol. 88(C).
    6. Ma, Xinwei & Ji, Yanjie & Yuan, Yufei & Van Oort, Niels & Jin, Yuchuan & Hoogendoorn, Serge, 2020. "A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 148-173.
    7. Yang Liu & Yanjie Ji & Tao Feng & Zhuangbin Shi, 2020. "Use Frequency of Metro–Bikeshare Integration: Evidence from Nanjing, China," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    8. Karimpour, Abolfazl & Hosseinzadeh, Aryan & Kluger, Robert, 2023. "A data-driven approach to estimating dockless electric scooter service areas," Journal of Transport Geography, Elsevier, vol. 109(C).
    9. David Wong & Shih-Lung Shaw, 2011. "Measuring segregation: an activity space approach," Journal of Geographical Systems, Springer, vol. 13(2), pages 127-145, June.
    10. Cheng, Shaowu & Xie, Bing & Bie, Yiming & Zhang, Yaping & Zhang, Shen, 2018. "Measure dynamic individual spatial-temporal accessibility by public transit: Integrating time-table and passenger departure time," Journal of Transport Geography, Elsevier, vol. 66(C), pages 235-247.
    11. Nigro, Marialisa & Castiglione, Marisdea & Maria Colasanti, Fabio & De Vincentis, Rosita & Valenti, Gaetano & Liberto, Carlo & Comi, Antonio, 2022. "Exploiting floating car data to derive the shifting potential to electric micromobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 78-93.
    12. Chi, Guangqing & Porter, Jeremy R. & Cosby, Arthur G. & Levinson, David, 2013. "The impact of gasoline price changes on traffic safety: a time geography explanation," Journal of Transport Geography, Elsevier, vol. 28(C), pages 1-11.
    13. Fang, Zhixiang & Shaw, Shih-Lung & Tu, Wei & Li, Qingquan & Li, Yuguang, 2012. "Spatiotemporal analysis of critical transportation links based on time geographic concepts: a case study of critical bridges in Wuhan, China," Journal of Transport Geography, Elsevier, vol. 23(C), pages 44-59.
    14. Bert van Wee & Caspar Chorus & Karst T. Geurs, 2012. "ICT and accessibility: research synthesis and future perspectives," Chapters, in: Karst T. Geurs & Kevin J. Krizek & Aura Reggiani (ed.), Accessibility Analysis and Transport Planning, chapter 3, pages 37-53, Edward Elgar Publishing.
    15. Gao, Deng & Li, Shicheng, 2022. "Spatiotemporal impact of railway network in the Qinghai-Tibet Plateau on accessibility and economic linkages during 1984–2030," Journal of Transport Geography, Elsevier, vol. 100(C).
    16. 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.
    17. Meijie Chen & Yumin Chen & Xiaoguang Wang & Huangyuan Tan & Fenglan Luo, 2019. "Spatial Difference of Transit-Based Accessibility to Hospitals by Regions Using Spatially Adjusted ANOVA," IJERPH, MDPI, vol. 16(11), pages 1-20, May.
    18. Barajas, Jesus M. & Brown, Anne, 2021. "Not minding the gap: Does ride-hailing serve transit deserts?," Journal of Transport Geography, Elsevier, vol. 90(C).
    19. Aksel Ersoy, 2016. "Impact of Accessibility and Knowledge Creation on Local and Regional Development in Turkey," Growth and Change, Wiley Blackwell, vol. 47(4), pages 648-663, December.
    20. N. Nima Haghighi & Xiaoyue Cathy Liu & Ran Wei & Wenwen Li & Hu Shao, 2018. "Using Twitter data for transit performance assessment: a framework for evaluating transit riders’ opinions about quality of service," Public Transport, Springer, vol. 10(2), pages 363-377, August.

    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:kap:jgeosy:v:22:y:2020:i:4:d:10.1007_s10109-020-00330-6. 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.