Classification of full polarimetric SAR data using artificial neural networks and fuzzy algorithms

Kurzfassung

In this paper we outline a classification based on the Entropy (H)-alpha decomposition Theorem extended by the use of the first eigenvalue of the coherency matrix. Fuzzy algorithms as well as Artificial Neural Networks (ANN) strategies are applied to improve the classification accuracy and to enhance the handling. The algorithms are applied to a L-band data set of the test site Oberpfaffenhofen, Germany, acquired with DLR’s airborne Experimental SAR (E-SAR) in April 1997. The classification results are discussed and compared to reference data i.e. topographic maps in the scale 1:25000 (maps 7833 and 7933) and airborne optical data acquired with a ZEISS RMK A30/23 camera in August 1997.