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Classification strategies for fully polarimetric SAR data of sea ice

Bernd Scheuchl (1), Ian Cumming(1) , and Irena Hajnsek(2)

(1) University of British Columbia, 2356 Main Mall, V6T 1Z4 Vancouver, BC, Canada
(2) German Aerospace Center e.V., P.O. Box 1116, D-82230 Wessling, Germany


The potential of polarimetric SAR data for classification purposes is widely recognised. More information on scattering mechanisms is now available and models have been developed to estimate contributions of these mechanisms to the total backscatter. In this paper we investigate the separation of scattering mechanisms for the classification of sea ice. Airborne data from the JPL AIRSAR as well as from the Canadian CV-580 is used. Based on the eigenvector decomposition of the coherency matrix, we sort the three resulting rank-one coherency matrices by the alpha angle estimate of the eigenvectors (as opposed to sorting by their corresponding eigenvalues). This sorting allows an interpretation of the scattering mechanism involved, a concept first introduced in [1]. In a multi-stage approach, we first focus on surface scattering, the main factor for first year ice (FYI), and investigate how other contributions (i.e. volume scattering and double bounce) can then best be used to refine the classification result. The multi-stage classifier results are compared to single-stage classification results. Our main objective is the classification of C-band polarimetric data, to develop RADARSAT-2 applications. But as AIRSAR data are available in C-, L-, and P- band, a multi-frequency approach will also be discussed and will be used as reference result.


[1] Scheuchl B., I. Hajnsek, and I. Cumming, 'Model based Sea Ice Classification Using Polarimetric SAR Data,' Proc. IGARSS 02, Toronto, 2002.


Full paper


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