IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0200493.html
   My bibliography  Save this article

Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China

Author

Listed:
  • Chen Liping
  • Sun Yujun
  • Sajjad Saeed

Abstract

Land use and land cover change research has been applied to landslides, erosion, land planning and global change. Based on the CA-Markov model, this study predicts the spatial patterns of land use in 2025 and 2036 based on the dynamic changes in land use patterns using remote sensing and geographic information system. CA-Markov integrates the advantages of cellular automata and Markov chain analysis to predict future land use trends based on studies of land use changes in the past. Based on Landsat 5 TM images from 1992 and 2003 and Landsat 8 OLI images from 2014, this study obtained a land use classification map for each year. Then, the genetic transition probability from 1992 to 2003 was obtained by IDRISI software. Based on the CA-Markov model, a predicted land use map for 2014 was obtained, and it was validated by the actual land use results of 2014 with a Kappa index of 0.8128. Finally, the land use patterns of 2025 and 2036 in Jiangle County were determined. This study can provide suggestions and a basis for urban development planning in Jiangle County.

Suggested Citation

  • Chen Liping & Sun Yujun & Sajjad Saeed, 2018. "Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    • Handle: RePEc:plo:pone00:0200493
    DOI: 10.1371/journal.pone.0200493
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0200493
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0200493&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0200493?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:plo:pone00:0200493. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.