Evaluation of classification methods with polarimetric ALOS/PALSAR data

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


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: Methods and Operational Tools (Forestsat 2007). Montpellier, France, 5-7 Nov. 2007
Number of pages5
Publication statusPublished - 2007
MoE publication typeNot Eligible
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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