Abstract
SUMMARYFour channel synthetic aperture radar imagery was interpreted to determine corn field identification accuracies obtainable using single channel, multi-channel and multi-date radar data. Image tone and texture of agricultural fields in the training set were used to derive discrimination criteria which were applied to fields in the testing set. The confusion of other agricultural crops with corn at X-band frequencies and forest cover with corn at L-band frequencies leads to errors of omission and inclusion. Corn field identification accuracies ranged from 58 to 100% using single channel imagery. The use of multi-channel imagery reduces the identification errors and accuracies exceeding 90% were consistently obtained. Individuals lacking radar interpretation experience but familiar with tonal and textural discrimination on airphotos obtained similar results with a short training period. Only two channels (one X-band, one L-band) are needed for the discrimination of corn from all other surface cover ty...
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