IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v17y2021i8p15501477211034069.html
   My bibliography  Save this article

Perceptions of spatial patterns of visitors in urban green spaces for the sustainability of smart city

Author

Listed:
  • Qi Liu
  • Li Hou
  • Sana Shaukat
  • Usman Tariq
  • Rabia Riaz
  • Sanam Shahla Rizvi

Abstract

Urban green spaces are really vital for the well-being of human in urban areas. In urban planning for green space site selection, the study of the bond among the usage of green spaces and their categories that really influence their use can provide useful references. A spatial and temporal research on the allocation of visitors in 157 green areas was carried out in Shanghai to know which green spaces are denser or crowdsourced by utilizing social media big data. We evaluated the association with statistical testing and Kernel Density Estimation among the spatial pattern of the visitor spread in urban green areas. We used check-in data from social media to test this study comparing the number of humans who visit various green parks. We have classified green areas into various categories and our main findings are focused on their characteristics: (1) famous category of green parks according to visitors’ preferences, (2) Differences in the number of visitors by daytime, and (3) crowdsourced area based upon number of check-ins. The main aim of this article is to remind policy makers of the value of providing local people access to green areas and to empower cities with a framework for contacting green parks with the purpose of increasing the comfort of urban people with the architecture of smart city.

Suggested Citation

  • Qi Liu & Li Hou & Sana Shaukat & Usman Tariq & Rabia Riaz & Sanam Shahla Rizvi, 2021. "Perceptions of spatial patterns of visitors in urban green spaces for the sustainability of smart city," International Journal of Distributed Sensor Networks, , vol. 17(8), pages 15501477211, August.
  • Handle: RePEc:sae:intdis:v:17:y:2021:i:8:p:15501477211034069
    DOI: 10.1177/15501477211034069
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/15501477211034069
    Download Restriction: no

    File URL: https://libkey.io/10.1177/15501477211034069?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
    ---><---

    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:sae:intdis:v:17:y:2021:i:8:p:15501477211034069. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: SAGE Publications (email available below). General contact details of provider: .

    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.