Crop Classification Using Airborne Radar and Landsat Data

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Abstract
Airborne radar data acquired with a 13.3-GHz scatterometer over a test site near Colby, KS, were used to investigate the statistical properties of the scattering coefficient of three types of vegetation cover and of bare soil. A statistical model for radar data was developed that incorporates signal fading and natural within-field variabilities. Estimates of the within-field and between-field coefficients of variation were obtained for each cover type and compared with similar quantities derived from Landsat images of the same fields. The second phase of this study consisted of evaluating the classification accuracy provided by Landsat alone, radar alone, and both sensors combined. The results indicate that the addition of radar to Landsat improves the classification accuracy by about 10 percentage points when the classification is performed on a pixel basis and by about 15 points when performed on a field-average basis. As with all crop-classification studies, these results pertain to the specific dates, geographic region, and crop categories.

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