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In recent years two polarimetric decompositions methods, the A/E method (Cloude and Pottier, 1997) and the three-component decomposition method (Freeman and Durden, 1998) have become the main methods of the polarimetric synthetic aperture radar data classification in radar imagery applications. In both methods the structural composition of the land cover is modelled using the main backscatter responses, as a function of the polarised channels, the level of energy received and the associated backscatter angles. To enhance the coherence in the polarimetric decompositions, data are generally multi-looked and de-speckled. The authors have applied and compared the 'Freeman' three-component decomposition followed by the Wishart complex classifier with the A/E decomposition algorithms to the de-speckled and edge-enhanced Glen Affric, fully polarimetric L-band radar data. The Glen Affric radar site was chosen for its extensive and diverse semi-natural woodlands of native Scots Pine, and its varied topography. The application results demonstrate the response of the radar classification from a semi-natural land cover on a rapid topography.