Improving PolSAR Land Cover Classification With Radiometric Correction of the Coherency Matrix

Abstract

The brightness of a SAR image is affected by topography due to varying projection between ground and image coordinates. For polarimetric SAR (PolSAR) imagery being used for purposes of land cover classification, this radiometric variability is shown to affect the outcome of a Wishart unsupervised classification in areas of moderate topography. The intent of this paper is to investigate the impact of applying a radiometric correction to the PolSAR coherency matrix for a region of boreal forest in interior Alaska. The gamma naught radiometric correction estimates the local illuminated area at each grid point in the radar geometry. Then, each element of the coherency matrix is divided by the local area to produce a polarimetric product that is radiometrically “flat.” This paper follows two paths, one with and one without radiometric correction, to investigate the impact upon classification accuracy. Using a Landsat-derived land cover reference, the radiometric correction is shown to bring about significant qualitative and quantitative improvements in the land cover map. Confusion matrix analysis confirms the accuracy for most classes and shows a 15% improvement in the classification of the deciduous forest class.