An algorithm for automatic classification of land surfaces from multifrequency polarimetric SAR data is presented. Discriminations among different classes of agricultural land surfaces have been carried out on the basis of calibrated backscattering coefficients measured for each field. Nine classes of agricultural surfaces have been identified with a very low error rate
Analysis of an Automatic Method for Surface Classification Using Multifrequency Multipolarization SAR Data
S Baronti;G Macelloni;S Paloscia;P Pampaloni;
1995
Abstract
An algorithm for automatic classification of land surfaces from multifrequency polarimetric SAR data is presented. Discriminations among different classes of agricultural land surfaces have been carried out on the basis of calibrated backscattering coefficients measured for each field. Nine classes of agricultural surfaces have been identified with a very low error rateFile in questo prodotto:
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