## 6 Discussion on Best Results Achieved  
This section summarizes best results achieved from the dynamic and single regression analyses (Table 12). Due to the reciprocity property of cross-polarizations, only outcomes achieved by using \(\sigma^{\circ}_{\text{HV}}\) and \(\sigma^{\circ}_{\text{PP}}\) channels are further discussed. In addition, this part will be focused on the _quasi_- and significant correlations only. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & \multicolumn{10}{c}{\(\sigma^{\circ}\) Dynamic Analysis–\(\Delta\sigma^{\circ}\)} & \multicolumn{10}{c}{\(\sigma^{\circ}\) vs. SVV Analysis} \\ \cline{3-13} \multirow{3}{*}{**Channel**} & \multirow{2}{*}{**Channel Pairs**} & \multicolumn{4}{c}{**Bare Soils**} & \multicolumn{4}{c}{**Vegetated**} \\ \cline{3-13}  & & & \(\sigma^{\circ}\) vs. \(h^{\prime}\) & \(\sigma^{\circ}\) vs. \(m_{\text{v}}\) & \(\sigma^{\circ}\) vs. \(h^{\prime}\) & \(\sigma^{\circ}\) vs. \(m_{\text{v}}\) & \(\sigma^{\circ}\) vs. \(m_{\text{v}}\) & \(\sigma^{\circ}\) vs. \(F_{\text{v}}\) & \(\sigma^{\circ}\) vs. \(LAI\) \\ \cline{2-13}  & & \(\mathbf{Varying}\) & \(\mathbf{LAI}\) (\(\mathbf{\sigma^{\circ}}\)) & \(\mathbf{Varying}\) & \(\mathbf{LAI}\) (\(\mathbf{\sigma^{\circ}}\)) & (\(\mathbf{dB}\)) (\(\mathbf{\sigma^{\circ}}\)) & (\(\mathbf{dB}\)) (\(\mathbf{\sigma^{\circ}}\)) & (\(\mathbf{dB}\)) (\(\mathbf{\sigma^{\circ}}\)) & (\(\mathbf{dB}\)) (\(\mathbf{\sigma^{\circ}}\)) & (\(\mathbf{dB}\)) (\(\mathbf{\sigma^{\circ}}\)) & (\(\mathbf{dB}\)) \\ \cline{2-13}  & & & & & & & & & & & & & & \\ \hline \(X_{\text{HH}}\) & 7.50 & 6.99 & - & - & 0.79 & 0.81 & - & - & 0.37 & 1.03 & 0.90 & 0.54 & 0.63 & 1.28 \\ \(X_{\text{VV}}\) & 7.20 & 6.16 & - & - & 0.82 & 0.66 & - & - & 0.46 & 1.05 & 0.85 & 0.74 & 0.62 & 1.48 \\ \(C_{\text{HH}}\) & 6.40 & 5.79 & - & - & 0.83 & 0.71 & - & - & 0.38 & 1.22 & 0.87 & 0.75 & 0.64 & 0.90 \\ \(C_{\text{HV}}\) & 10.00 & 10.39 & - & - & - & - & - & - & 0.46 & 1.41 & 0.90 & 0.62 & 0.91 & 0.54 \\ \(C_{\text{VV}}\) & 7.80 & 5.02 & - & - & - & - & - & - & - & 0.87 & 0.61 & - & - \\ \(L_{\text{HH}}\) & 11.40 & 11.72 & - & - & 0.99 & 0.24 & - & - & 0.51 & 2.44 & 0.87 & 0.76 & 0.98 & 0.29 \\ \(L_{\text{HV}}\) & 12.10 & 13.96 & - & - & 0.99 & 0.15 & - & - & 0.66 & 1.79 & 0.95 & 0.67 & 0.95 & 0.83 \\ \(L_{\text{VV}}\) & 11.30 & 10.95 & - & - & 0.99 & 0.22 & - & - & 0.55 & 1.61 & 0.90 & 0.83 & 0.89 & 0.88 \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Best results achieved through the dynamic and correlation analyses; significant correlations are highlighted in light-grey, _quasi_-significant correlations are underlined; other correlations are not reported; for each correlation MAE is also reported. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & \multicolumn{10}{c}{\(\sigma^{\circ}\) Dynamic Analysis–\(\Delta\sigma^{\circ}\)} & \multicolumn{10}{c}{\(\sigma^{\circ}\) vs. SVV Analysis} \\ \cline{3-13}  & \multicolumn{10}{c}{**(dB)**} & \multicolumn{10}{c}{**Bare Soils**} & \multicolumn{10}{c}{**Vegetated**} \\ \cline{3-13} \multirow{3}{*}{**Channel**} & \multirow{2}{*}{**Whole Dataset**} & \multicolumn{4}{c}{**\(\sigma^{\circ}\) vs. \(h^{\prime}\)**} & \(\sigma^{\circ}\) vs. \(m_{\text{v}}\) & \(\sigma^{\circ}\) vs. \(h^{\prime}\) & \(\sigma^{\circ}\) vs. \(m_{\text{v}}\) & \(\sigma^{\circ}\) vs. \(m_{\text{v}}\) & \(\sigma^{\circ}\) vs. \(F_{\text{v}}\) & \(\sigma^{\circ}\) vs. \(LAI\) \\ \cline{2-13}  & \multicolumn{10}{c}{**Varying \(h^{\prime}\), \(m_{\text{v}}\)**} & \(\mathbf{Varying}\) & \(\mathbf{LAI}\) (\(\mathbf{\sigma^{\circ}}\)) & (\(\mathbf{dB}\)) (\(\mathbf{\sigma^{\circ}}\)) & (\(\mathbf{dB}  
The dynamic analysis highlighted that \(\Delta\sigma^{\circ}\) at C\({}_{\rm HV}\) and L frequency generally showed the highest \(\Delta\sigma^{\circ}\) (\(\approx\)10-12 dB); however, individual contributions of _h'_, \(m_{\rm v}\), \(F_{\rm v}\) and _LAI_ were not definitely distinguishable.