IDEAS home Printed from https://ideas.repec.org/h/spr/lnopch/978-981-19-5256-2_66.html
   My bibliography  Save this book chapter

A Spatial Autocorrelation Analysis for Land Use Change in the Guangdong-Hong Kong-Macao Greater Bay Area

In: Proceedings of the 26th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Xiao Tang

    (The University of Manchester)

  • Clyde Zhengdao Li

    (Shenzhen University
    Shenzhen University
    Shenzhen University)

  • Lin Jiang

    (Shenzhen University)

  • Xulu Lai

    (Shenzhen University)

  • Limei Zhang

    (Shenzhen University)

Abstract

The rise of the megalopolis has become a crucial force in urbanization throughout the world. Its land-use change has become a central factor that will affect the benign development of the megalopolis. This paper conducts a spatial autocorrelation analysis to study the spatial dependence and heterogeneity of the land use/land cover change in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China from 1990 to 2018. It also proposes the land spatial development strategy combined with the results of empirical analysis. The findings include: 1) From 1990 to 2018, Moran's I values for agricultural land, forest land, and construction land were all range from 0.078 to 0.32. The spatial autocorrelation of forest land has been decreased since 1990, but the spatial autocorrelation of construction land and agricultural land showed a slight rebound trend in 2010, although it has been gradually decreasing since 1990. 2) Land use in the GBA region shows a High-Low agglomeration phenomenon, of which Shenzhen has been in a High-Low correlation from 1990 to 2010, while the High-Low correlation is no longer shown after 2010. 3) The areas presenting High-Low correlations between construction land and agricultural land or forest land are mainly located in regions with rapid economic development, such as Shenzhen. Low-Low areas are mainly concentrated in economically developed regions such as Macau and Hong Kong.

Suggested Citation

  • Xiao Tang & Clyde Zhengdao Li & Lin Jiang & Xulu Lai & Limei Zhang, 2022. "A Spatial Autocorrelation Analysis for Land Use Change in the Guangdong-Hong Kong-Macao Greater Bay Area," Lecture Notes in Operations Research, in: Hongling Guo & Dongping Fang & Weisheng Lu & Yi Peng (ed.), Proceedings of the 26th International Symposium on Advancement of Construction Management and Real Estate, pages 847-858, Springer.
  • Handle: RePEc:spr:lnopch:978-981-19-5256-2_66
    DOI: 10.1007/978-981-19-5256-2_66
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:lnopch:978-981-19-5256-2_66. 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: 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.