## 4 Results
### Relationships Between Cross-Correlation Coefficient and Sea Ice Image Properties  
In the MCC approach, a high cross-correlation coefficient consolidates more accurate motion measurement without outliers that demand additional removal processes such as filtering or averaging nearby vectors. Links between the cross-correlation coefficient and image properties representing sea ice conditions such as sea ice coverage and entropy of image blocks (i.e., template window images) were assessed to identify the relationships. The cross-correlation coefficient and the sea ice coverage of the image blocks from the prior image showed negative correlations as negative [PERSON]'s tau coefficients, implying ordinal association considering non-parametric variables with ties, in the image pairs of both spatial resolutions [44] (Figure 10a,c). On the other hand, the cross-correlation coefficient and the entropy of the image blocks from the prior image showed positive correlations as positive [PERSON]'s tau coefficients in the image pairs of both spatial resolutions (Figure 10b,d). The trends of the correlation coefficients (tau) of the other image pairs were similar to Figure 10 (Table 6). The correlation coefficients (tau) between the cross-correlation coefficient and sea ice coverage were negative, and the correlation coefficients (tau) between the cross-correlation coefficient and entropy were positive. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Correlation Coefficient (Tau)**} \\ \cline{2-5}
**Image Pair** & \multicolumn{2}{c}{**Spatial Resolution of 4 m**} & \multicolumn{2}{c}{**Spatial Resolution of 15 m**} \\ \cline{2-5}  & **Cross-Correlation** & **Cross-Correlation** & **Cross-Correlation** & **Cross-Correlation** \\  & **Coefficient vs. Sea Ice** & **Coefficient vs.** & **Coefficient vs. Sea Ice** & **Coefficient vs.** \\  & **Coverage** & **Entropy** & **Coverage** & **Entropy** \\ \hline
1 & \(-\)0.341 & 0.338 & \(-\)0.221 & 0.222 \\
2 & \(-\)0.200 & 0.195 & \(-\)0.166 & 0.166 \\
3 & \(-\)0.287 & 0.277 & \(-\)0.026 & 0.026 \\
4 & \(-\)0.233 & 0.230 & \(-\)0.193 & 0.193 \\
5 & \(-\)0.121 & 0.116 & \(-\)0.236 & 0.237 \\
6 & \(-\)0.235 & 0.231 & \(-\)0.258 & 0.258 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: The relationships between cross-correlation coefficient and sea ice image properties. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Dataset** & **Parameter** & **RMSE** & **Bias** \\ \hline \multirow{3}{*}{Spatial resolution of 4 m} & Displacement & 57.7 m & \(-\)11.4 m \\  & Velocity & 19.0 m\(\cdot\)h\({}^{-1}\) & \(-\)4.6 m\(\cdot\)h\({}^{-1}\) \\  & Direction & 4.0\({}^{\circ}\) & \(-\)1.5\({}^{\circ}\) \\ \hline \multirow{3}{*}{Spatial resolution of 15 m} & Displacement & 60.7 m & \(-\)13.5 m \\  & Velocity & 18.7 m\(\cdot\)h\({}^{-1}\) & \(-\)4.3 m\(\cdot\)h\({}^{-1}\) \\ \cline{1-1}  & Direction & 3.8\({}^{\circ}\) & \(-\)2.0\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Quality assessment of the sea ice motion measurement by comparing the image-derived motion vectors with the motions connecting the time-interpolated buoy locations. Figure 10: _Cont._  
Among the sea ice coverage and the entropy of the matched image block from the pair of the KOMPSAT-2 image acquired on 14 August 2014 (i.e., prior image) and the KOMPSAT-3 image acquired on 14 August 2014 (i.e., posterior image) resampled to the spatial resolution of 4 m (Figure 11), the image block of the prior image showing the maximum sea ice coverage parameter yielded very low entropy, and the image block showing the sea ice coverage parameter of about 50% yielded the maximum entropy. In the case of the sea ice coverage and entropy of the matched block from the same image pair resampled to the spatial resolution of 15 m (Figure 12), an identical trend was observed.