Area 3 was used for investigation of the classification results. The results are shown in Table 2 . The table shows that clustering of VV data gave the best results with an error rate of 7.2%. The least good results were obtained for crosspolarization with an error rate of 12.2%. ABSTRACT Results from analysis of data obtained in the Snow and Ice experiment within the European Multi-sensor Airborne Campaign (EMAC'95) [2] are presented in this paper. The study area is located in Norway, 66 o N,

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... 4 o E. Fully polarimetric C-and L-band SAR data from EMISAR, a airborne instrument operated by the Danish Centre for Remote Sensing, combined with ERS SAR, airborne photos and field data were analyzed in order to determine the capabilities for snow parameter estimation in mountainous areas. The backscatter statistics of EMISAR C-band data from two areas partly covered with wet snow was studied. There was a difference in mean values between the two areas of up to 4.4 dB for snow and up to 1.3 dB for bare ground. For the purpose of classification, this indicates that local class statistics has to be applied. A classification test on a small area of Kmeans clustering showed that the best results was obtained for VV polarization with an error rate of 7.2%. All error rates were between 7.2 and 12.2%. The C-band polarization responses derived from the snowcover corresponds to smooth surface scattering. The extent of the wet snowcover observed by ERS SAR correspond to EMISAR observation.