SINGLE-PASS SEA/ICE DISCRIMINATION USING ERS-2 SCATTEROMETER DATA

this paper presents a new method to perform sea/ice discrimination in single-pass ers-2 scatterometer data. existing methods are 1rst reviewed and compared in a consistent framework. next, the ice probability according to the individual existing methods is learned through the use of a neural network. finally, the individual criteria are combined together in order to increase the sea-ice discrimination accuracy. the proposed method is shown to provide an acceptable performance even on single-pass data, i.e., without requiring temporal averaging