The Use of Fuzzy Set Theory in Remote Sensing Pattern Recognition

Manfred M. Fischer, Josef Benedikt

    Publication: Working/Discussion PaperWU Working Paper

    Abstract

    Satellite images increasingly become a major data source for monitoring changes in the
    natural environment. A main task in the analysis of satellite images is concerned with the
    modelling of land use classes by reducing uncertainty during a classification process. In the
    approach presented in this paper uncertainty is perceived to be due to the vagueness of
    geographical categories caused by either the complexity of the category (like 'urban area') or
    by the use of the category in several application contexts. Two circumstances of use of an
    extended set theoretical concept (fuzzy sets) are discussed. First, two algorithms from the
    ISODATA class are used to determine the grades of membership to three a priori defined
    classes (woodland, suburban area, urban area) of a LANDSAT TM satellite image of Vienna,
    Austria. The results are visualized by a RGB image of the grades of membership to each
    category. Second, a measure of fuzziness is employed on the results. The measure relies on
    the concept of distance between a seUcategory and its complement. The so determined
    vagueness provide more information on the uncertainty of the different categories and may
    improve further information processing tasks. (authors' abstract)
    Original languageEnglish
    Place of PublicationVienna
    PublisherWU Vienna University of Economics and Business
    Publication statusPublished - 1996

    Publication series

    NameDiscussion Papers of the Institute for Economic Geography and GIScience
    No.50/96

    WU Working Paper Series

    • Discussion Papers of the Institute for Economic Geography and GIScience

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