## 4 Discussion  
Correlation analyses of the PolSAR features indicated that the quad-polarized Kennaugh Matrix elements K0, K1, K3, K4 and K7 were highly correlated with corresponding elements of the dual-polarized Kennaugh Matrices. As the dual-polarized Kennaugh matrix is a submatrix of the full-polarized Kennaugh Matrix generated out of these elements, the elements are therefore interchangeable and the dual-polarized data provide a substitute of the full quad-polarized data, at least  
\begin{table}
\begin{tabular}{c  
for the tundra land cover investigated in this research. Contrary to this, the quad-polarized Kennaugh Matrix elements K5 and K6 were less correlated to the corresponding elements of the cross-polarized Kennaugh Matrix. Nevertheless, there are still benefits associated with the Kennaugh Matrix, since all kinds of PolSAR data can be stored, processed and analyzed in the same manner. It also provides a unified framework without any loss of information, and the capacity to interpret decomposed elements in a coherent and incoherent way since any other incoherent or coherent scattering matrix can be derived if necessary [31; 42]. The Stokes coordinate system used for the definition of the Kennaugh Matrix seems to offer an appropriate approach to characterize the environment investigated in this research. For the examined tundra land cover of the Tuktoyaktuk Peninsula, it was further shown that the elements of the Two Component Decompositions of [14] and [30] were highly correlated with the corresponding elements of the Yamaguchi Decomposition and--with lower significance--volume scattering, and HV intensity, respectively. Thus, the HH/VV-polarized data provide crucial information for describing the land covers considered in this research. As pointed out by [14], the correspondence of these quad- and HH/VV-polarized decomposition features is a function of the presence and influence of volume scattering processes, relative to contributions from the ground. Thus, due to the relatively short stature (height) of tundra vegetation, the observed correlations were high due to a lack of a significant volume scattering component. Further, the correlations between the features were generally higher at L-Band, compared to features at C-Band. This can be attributed to the longer wavelength of the ALOS and ALOS-2 sensors, and the absence/weakness of random scattering processes as the penetration depth is higher and volume scattering is less likely (thus the volume component is small relative to surface scattering). The backscatter characteristics of the tundra land cover classes were examined via box- and scatterplots of the individual PolSAR features. It was shown that X-, C- and L-Band data exhibit distinct scattering characteristics for the different land cover classes. Results indicate that the L-Band data were more sensitive to the bare ground classes; thus, it is better suited to investigate and monitor ground properties, e.g., soil moisture, or the surface heave and subsidence (via InSAR) caused by the freezing and thawing of the active layer (compare [17; 20; 21]); especially in sites dominated by shrubs. In contrast, use of short wavelengths (X- and C-Band) is beneficial for characterizing tundra and wetland vegetation. This observation is in accordance with other studies [9; 12; 15]. It is worth noting the clear distinction of the land cover class: driftwood accumulation (BW) in the L-Band data. The coverage of BW is characterized by non-vegetated, dead woody debris, and frequently such accumulations exhibit a very high surface roughness, since dead wood and stems pile up more than a meter high (compare Figure 2c). Even though this should be a clearly visible target, and distinct feature in the PolSAR data, the position of BW is less clear in the feature spaces of X- and C-Band compared to the position of BW in the L-Band feature space. For BW the highest HH and HV intensity values (derived from ALOS in 2010) were found among all land cover classes.