• DocumentCode
    826889
  • Title

    On the use of prior and posterior information in the subpixel proportion problem

  • Author

    Kolaczyk, Eric D.

  • Author_Institution
    Dept. of Math. & Stat., Boston Univ., MA, USA
  • Volume
    41
  • Issue
    11
  • fYear
    2003
  • Firstpage
    2687
  • Lastpage
    2691
  • Abstract
    Although the problems of classification and subpixel proportion estimation in remote sensing land cover characterization generally are held to be distinct (though related), often elements of the former are adopted in addressing the latter that blur this distinction - particularly, regarding the use of prior and posterior information. The author examines this issue in more detail, using simple, canonical versions of the two problems and, in the course of this examination, provides analytical expressions upon which to build discussion of improvements to subpixel proportion estimation from a statistical viewpoint.
  • Keywords
    Bayes methods; image classification; vegetation mapping; Bayesian estimation; land cover classification; posterior information; prior information; remote sensing; statistical approach; subpixel proportion estimation; subpixel proportion problem; Ecosystems; Image processing; Interpolation; Mathematics; Monitoring; Pixel; Predictive models; Remote sensing; Satellites; Statistics;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2003.817194
  • Filename
    1245258