Evaluation of classification methods with polarimetric ALOS/PALSAR data

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific


    This article compares four land cover classification methods using ALOS Palsar fully polarimetric data. Two methods are based on supervised classification and two on unsupervised classification. Both full polarimetric and intensity data were used. Fully polarimetric data gave better results (85.5%–80.8%) than intensity data only (84%–76.1%) but the differences in the overall accuracies between the methods were not more than 6%. When using intensity data only, classification results with HH and HV features were as good as using in additionally also VV, HH+VV and HH-VV bands.
    Original languageEnglish
    Title of host publicationForests and Remote Sensing
    Subtitle of host publicationMethods and Operational Tools (Forestsat 2007)
    Number of pages5
    Publication statusPublished - 2007
    MoE publication typeB3 Non-refereed article in conference proceedings
    EventForests and Remote Sensing: Methods and Operational Tools, Forestsat 2007 - Montpellier, France
    Duration: 5 Nov 20077 Nov 2007


    ConferenceForests and Remote Sensing: Methods and Operational Tools, Forestsat 2007
    Abbreviated titleForestsat


    • Polarimetric synthetic aperture radar
    • land cover

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