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2 December 2008 Contribution of radar polarimetric data for the cartography in tropical environment
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The Support Vector Machine (SVM) algorithm is assessed for the classification of polarimetric radar data for the cartography of natural vegetation. Fully polarimetric data has been acquired in L and P bands during an AIRSAR mission over the French Polynesian Island named Tubuai. The results show significant improvement when compared to those obtained with the classification based on the maximum likehood criterion applied to the theoretical Wishart distribution that are supposed a priori to be verified by radar data. Obviously, this hypothesis is not verified with the present experimental data over the study site. The addition of other polarimetric indicators to the elements of the polarimetric coherency matrix still improves the classification accuracy. The evaluation of different partial polarimetric modes shows that even the best results are obtained for fully polarimetric data, the π4 mode gives the best compromise with respect to the ASAR Alternate Polarization mode or the PALSAR Dual Polarization mode. This latter shows in turn better results than the Alternate Polarization mode, indicating the significant contribution of the polarimetric differential phase between 2 polarization channels.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
C. Lardeux, P-L. Frison, J-C. Souyris, C. Tison, B. Stoll, and J-P. Rudant "Contribution of radar polarimetric data for the cartography in tropical environment", Proc. SPIE 7154, Microwave Remote Sensing of the Atmosphere and Environment VI, 71540G (2 December 2008);

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