Peatland delineation under forest canopy with polsar data using model based decomposition technique

The paper describes evaluating the potential of peatland detection under forest canopy with L-band space borne quad-polarization data in the boreal forest zone. Particular emphasis was made on under what seasonal conditions this detection was possible using single SAR data-take. For this purpose multitemporal ALOS PALSAR imagery acquired over Kuortane test site in central Finland during 2007-2008 was used. Supervised classification experiments employing selected polarimetric features were performed using standard maximum likelihood approach and probabilistic neural network (PNN). Strong non-gaussianity effects were noted, with better performance demonstrated by PNN, utilizing non-parametric estimation of probability distributions of the respective polarimetric features. Suitability of several techniques aimed at compensating the presence of forest canopy was studied as well.