• DocumentCode
    576706
  • Title

    Deriving 2011 cultivated land cover data sets using usda National Agricultural Statistics Service historic Cropland Data Layers

  • Author

    Boryan, Claire ; Yang, Zhengwei ; Di, Liping

  • Author_Institution
    U.S. Dept. of Agric., Nat. Agric. Stat. Service, Fairfax, VA, USA
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    6297
  • Lastpage
    6300
  • Abstract
    This paper describes the method used to derive 30 meter resolution 2011 US cultivated data sets based on multi-year National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) data. This paper presents different sets of rules (models) to build the cultivated data sets, and a comparison of the resulting cultivated data set accuracies to the accuracies of the original CDL input data. Nine models to create 2011 cultivated data sets for nine US states are tested. Each model provides a set of rules for merging pixels of multi-year (2007-2011) CDL data. The cultivated data accuracy was assessed against in situ 2011 Farm Service Agency (FSA) Common Land Unit (CLU) data. It was found that accuracies were close among the cultivated data generated using the different models. The strongest models for all states achieved overall (producer and user) accuracies greater than 94% for cultivated and non cultivated categories.
  • Keywords
    agricultural engineering; agriculture; crops; terrain mapping; vegetation mapping; FSA CLU data; US cultivated data sets; USDA National Agricultural Statistics Service historic cropland data layers; cultivated data accuracy; cultivated land cover data sets; in situ 2011 Farm Service Agency Common Land Unit data; multiyear NASS cropland data layer data; Accuracy; Agriculture; Buildings; Data models; Information filtering; Spatial resolution; Training data; CDL; crop mask; cultivated data layer; land cover; multi-year cultivated data layer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6352699
  • Filename
    6352699