KUKU

KU ScholarWorks

  • myKU
  • Email
  • Enroll & Pay
  • KU Directory
    • Login
    View Item 
    •   KU ScholarWorks
    • Geographic Information Systems
    • GIS Conference Papers, Presentations, Etc.
    • View Item
    •   KU ScholarWorks
    • Geographic Information Systems
    • GIS Conference Papers, Presentations, Etc.
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Optimatization of sample points for monitoring arable land quality by simulated annealing while considering spatial variations

    Thumbnail
    View/Open
    gis_day2016student_wang.pdf (1.278Mb)
    Issue Date
    2016-11-16
    Author
    Wang, Junxiao
    Wang, Xiaorui
    Zhou, Shenglu
    Wu, Shaohua
    Publisher
    GIS Day @ KU Planning Committee
    Type
    Poster
    Metadata
    Show full item record
    Abstract
    Arable land is the basis of food production, the most valuable input in agricultural production, and an important factor in sustainable agricultural development and national food security. In China, the reduction and degradation of arable land due to industrialization and urbanization has gradually emerged as one of the most prominen challenges. In this context, the long-term dynamic monitoring of arable land quality becomes important for protecting arable land resources. However, little consideration has been given to optimizing sample points number and layout in previous monitoring studies on arable land quality. When considering the optimization of sample points, various strategies are needed, depending on the indicators. In addition, the distributio of soil properties displays spatial variations. However, existing sampling studies have paid little attention to spatial variations during scenarios with multiple indicators.Therefore, it is necessary to further investigate how to improve the efficiency and accuracy of arable land quality monitoring and evaluation by optimizing the number and layout of sample points when there are spatial variations in multiple indicators.
    Description
    This presentation was given as part of the GIS Day@KU symposium on November 16, 2016. For more information about GIS Day@KU activities, please see http://gis.ku.edu/gisday/2016/.
    URI
    http://hdl.handle.net/1808/23355
    Collections
    • GIS Conference Papers, Presentations, Etc. [203]

    Items in KU ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.


    We want to hear from you! Please share your stories about how Open Access to this item benefits YOU.


    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    Browse

    All of KU ScholarWorksCommunities & CollectionsThis Collection

    My Account

    Login

    Statistics

    View Usage Statistics

    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    The University of Kansas
      Contact KU ScholarWorks
    Lawrence, KS | Maps
     
    • Academics
    • Admission
    • Alumni
    • Athletics
    • Campuses
    • Giving
    • Jobs

    The University of Kansas prohibits discrimination on the basis of race, color, ethnicity, religion, sex, national origin, age, ancestry, disability, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression and genetic information in the University’s programs and activities. The following person has been designated to handle inquiries regarding the non-discrimination policies: Director of the Office of Institutional Opportunity and Access, IOA@ku.edu, 1246 W. Campus Road, Room 153A, Lawrence, KS, 66045, (785)864-6414, 711 TTY.

     Contact KU
    Lawrence, KS | Maps