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Unsupervised classification of a central italy landscape by polarimetric L-band SAR data

This paper reports on the classification of a Central Italy landscape imaged by the JPL/NASA AirSAR in the frame of the MAC-Europe 91 campaign. The coherence matrices have been computed from the scattering vector obtained through Pauli decomposition, and subsequently filtered. An H/A/α decomposition has been carried out preliminarily to the Wishart H/A/α classification procedure, fed by the coherence matrices, the results of the previous H/α classification and the anisotropy values. The iterative procedure has been terminated by a proper lower threshold on the percentage of pixels changing classes in subsequent steps. Given the nature of the imaged landscape, the number of classes has been suitably reduced to match that actually identified in the scene. Accuracy matrices have been computed from the obtained results and the ground truth map co-registered with the AirSAR image, and a comparison has been carried out with the results yielded for agricultural parcels by a classification scheme based on the physical modeling of the interaction between radar electromagnetic wave and crops.