IDEAS home Printed from https://ideas.repec.org/a/hin/complx/3798183.html
   My bibliography  Save this article

Exploring Residential Heterogeneity through Multiscalar Lens: A Case Study of Hangzhou, China

Author

Listed:
  • Qinshi Huang
  • Weixuan Song
  • Liyan Liu
  • Chunhui Liu
  • Xinyi Zhang
  • Ge He
  • Jun Yang

Abstract

The pattern, process, and mechanism of residential heterogeneity vary significantly with different geographical scales. However, most traditional methods ignore the checkboard and modifiable areal unit problem (MAUP), which may cover up the complexity and hierarchy of social space. Taking Hangzhou city as an example, a multiscalar method was proposed based on the information entropy theory to estimate residential heterogeneity and its scale sensitivity. Based on the sixth population census of Hangzhou and the housing price database of 6,536 residential districts from 2008 to 2018, we explore the scale effect and dynamic characteristics of residential heterogeneity. The results of spatial simulation and geostatistical analysis based on Python Spatial Analysis Library (PySAL) module show that the multiscalar algorithm better presents the real segregation pattern than traditional method, which is one of the new models and technologies in urban geography complex system. Exploring residential heterogeneity through multiscalar lens provides an important basis for the gradual and refined urban renewal.

Suggested Citation

  • Qinshi Huang & Weixuan Song & Liyan Liu & Chunhui Liu & Xinyi Zhang & Ge He & Jun Yang, 2021. "Exploring Residential Heterogeneity through Multiscalar Lens: A Case Study of Hangzhou, China," Complexity, Hindawi, vol. 2021, pages 1-12, February.
    • Handle: RePEc:hin:complx:3798183
    DOI: 10.1155/2021/3798183
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/complexity/2021/3798183.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/complexity/2021/3798183.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/3798183?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
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:hin:complx:3798183. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.