Use of landsat-derived temporal profiles for corn-soybean feature extraction and classification

Using the multitemporal multispectral data acquired by Landsat satellites and a physical model describing this behavior, new features that are crop specific have been derived. The new feature space is two-dimensional irrespective of the number of Landsat observations. A feasibility study, over 40 sites, has been performed to classify the segment pixels into those of corn, soybeans, and others using these new features and a linear classifier. The results compare very favorably with other existing methods. The results also indicate where additional accuracy gains can be made.