Fully polarimetric classification of the Black Forest MAESTRO 1 AIRSAR data

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Abstract
In this paper we present a study on the application of polarimetric supervised classification techniques to the case of a forested area where the influence of topography is important. For the experimental part of the study, we use the polarimetric AIRSAR data at C, Land P band, acquired over the Black Forest near Freiburg “Germany” during the 1989 MAESTRO I Campaign. Two classification schemes are considered: one is of the classical Bayes type, while the other is based on the concept of maximum contrast. We show practical results of the use of both classifiers in a classification context based on tree age classes. Also the dependency of the classification accuracy on a number of parameters, such as calibration, feature vector dimensions and covariance matrix representation, is discussed. Finally, we focus on the influence of topography on classification and indicate how we can improve the classification results using a priori knowledge of the terrain slope.