IDEAS home Printed from https://ideas.repec.org/p/ags/unasrr/234361.html
   My bibliography  Save this paper

A new land cover classification based stratification method for area sampling frame construction

Author

Listed:
  • Boryan, Claire G.
  • Yang, Zhengwei

Abstract

This paper proposes a new automated USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) based method for stratifying U.S. land cover. The proposed method is used to stratify the NASS state level Area Sampling Frames (ASFs) by automatically calculating percent cultivation at the Primary Sampling Unit (PSU) level based on the CDL data. The CDL based stratification experiment was successfully conducted for Oklahoma, Ohio, Virginia, Georgia, and Arizona. The stratification accuracies of the traditional and new automated CDL stratification methods were compared based on 2010 June Area Survey (JAS) data. Experimental results indicated that the CDL based stratification method achieved higher accuracies in the intensively cropped areas while the traditional method achieved higher accuracies in low or non agricultural areas. The differences in the accuracies were statistically significant at a 95% confidence level. It is concluded that the CDL based stratification method will improve efficiency and reduce cost in NASS ASF construction, and improve the precision of NASS JAS estimates.

Suggested Citation

  • Boryan, Claire G. & Yang, Zhengwei, 2012. "A new land cover classification based stratification method for area sampling frame construction," NASS Research Reports 234361, United States Department of Agriculture, National Agricultural Statistics Service.
    • Handle: RePEc:ags:unasrr:234361
    DOI: 10.22004/ag.econ.234361
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/234361/files/BoryanYang_AgroGeoinformatics2012_final.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.234361?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gerling, Michael & Lawson, Linda & Weaber, Jillayne & Dotts, Alan & Vardeman, Andrew & Wilson, Eric, 2015. "Field Data Collection Using Geographic Information Systems Technologies and iPads on the USDA’s June Area Frame Survey," NASS Research Reports 234386, United States Department of Agriculture, National Agricultural Statistics Service.
    2. repec:ags:unassr:234386 is not listed on IDEAS
    3. Md. Shahinoor Rahman & Liping Di & Eugene Yu & Chen Zhang & Hossain Mohiuddin, 2019. "In-Season Major Crop-Type Identification for US Cropland from Landsat Images Using Crop-Rotation Pattern and Progressive Data Classification," Agriculture, MDPI, vol. 9(1), pages 1-21, January.

    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:unasrr:234361. 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: https://www.nass.usda.gov/ .

    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.