CLASSIFICATION OF MULTIPOLARIZED AIRBORNE RADAR DATA IN AGRICULTURE

We have examined the contribution of multipolarized airborne radar dat a for the discrimination of crops. An unsupervised classification algo rithm and a maximum likelihood supervised classification were used and compared. The results show that multipolarized radar data offer an ac curate means of identifying crops. The average classification accuraci es were 83 and 79 per cent for the supervised and unsupervised methods respectively. Comparison of the two methods using the same data sugge sts that the unsupervised method gives essentially similar results to those using the supervised classification method; however, the unsuper vised method requires far less field effort and computer time.