IDEAS home Printed from https://ideas.repec.org/a/ags/asagre/155852.html
   My bibliography  Save this article

Quantitative Classification of Forestry Division in Ceheng County

Author

Listed:
  • Zhao, Hua
  • Liu, Yong
  • Liu, Longde
  • Sun, Jihui
  • Gu, Yongshun

Abstract

To determine the main functions of regional forest and focus of forestry construction to form the regional forestry economy with characteristics and ecological service system pattern with obvious advantages, we select some indicators on Ceheng County in Guizhou Province, such as natural geography, socio-economic conditions, ecological environment and forests status. Using the quantitative classification method combining factor analysis and system clustering, we conduct quantitative county level forestry division. The results show that first using factor analysis to establish factor analysis model, and then using a handful of factors loading large amounts of information to carry out system clustering, is an effective quantitative classification method of forestry division, which can not only overcome the weakness of previous division mainly focusing on qualitative analysis, but also eliminate the correlation between indicators in the conventional classification methods; through the factor analysis of 30 indicators influencing the forestry development of each township in Ceheng County, the factor analysis model is established, 6 factors loading 89.94 5% of information amount are used to conduct system clustering on 14 townships in Ceheng County, and finally Ceheng County can be divided into five zones. This study not only enriches the theory of forestry division, but also provides reference for the forestry planning in Guizhou and division of related industries.

Suggested Citation

  • Zhao, Hua & Liu, Yong & Liu, Longde & Sun, Jihui & Gu, Yongshun, 2013. "Quantitative Classification of Forestry Division in Ceheng County," Asian Agricultural Research, USA-China Science and Culture Media Corporation, vol. 5(07), pages 1-7, July.
  • Handle: RePEc:ags:asagre:155852
    DOI: 10.22004/ag.econ.155852
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/155852/files/26.PDF
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.155852?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

    Keywords

    Agribusiness;

    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:ags:asagre:155852. 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: AgEcon Search (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.