## 5 Discussion  
The results of the sea ice motion measurements illustrate that the dense distributions of the moving distance and direction from the image pairs of the 4 m spatial resolution revealed spatial patterns reflecting characteristics of sea ice motion (Figure 5). Thus, from the high-resolution satellite image-derived spatial gradient pattern of the moving distance and direction, small-scale discontinuities in motion could be visualized. For the dataset spatially resampled to 15 m, the pixel aggregation during spatial resampling smoothed the surface texture of sea ice, so that effects from small scale irregular motions, e.g., isolated drifting floe, appeared to be decreased. Increased sea ice coverage, decreased entropy and slightly more discrete colors of the motion vectors in Figure 8 when compared with Figure 5, were from a relatively increased displacement unit caused by enlarged pixel size. The displacements of the sea ice motion varied between 409.6 and 2921.4 m for the image pairs of the spatial resolution of 4 m and between 415.0 and 2919.1 m for the image pairs of the spatial resolution of 15 m, respectively. This means that the measured sea ice motions were larger than twice of the geolocation errors of the images, i.e., minimum detectable displacement between images, approximately 100 m. Thus, the sea ice motion can be considered to be partly affected by the geolocation errors of the images. When the images partly including land area over arctic coastal region are used for coastal and land fast sea ice motion measurement, geolocation errors of satellite sensors can be decreased by assigning ground control points to accurate geographic coordinates on land area. If other high-resolution spaceborne optical sensors of higher geolocation accuracy with few meters error are applied, more accurate sea ice motion and deformation measurements can be accomplished by decreasing minimum detectable displacement. The RMSEs and biases of the sea ice motion parameters such as displacements, directions and velocities were known to be increased in coarser resolution datasets associated with extended unit distance of the images given the errors' dependency on the spatial resolution [17; 46], and changed image texture to less sensitive conditions for precise measurement from an enlarged spatial resolution. However, results regarding the sea ice motion showed similar RMSEs and biases for both resolution datasets. Figure 14: The histogram of the sea ice deformation using the same image pair with Figure 13: the histograms of divergence from (**a**) the image pair resampled to the spatial resolutions of 4 m; and (**b**) the same image pair resampled to the spatial resolutions of 15 m, and the histograms of shear from (**c**) the image pair resampled to the spatial resolutions of 4 m; and (**d**) the same image pair resampled to the spatial resolutions of 15 m.  
The distances between the center of the selected motion vectors from the image pair of the spatial resolution of 4 m and the center of the corresponding time-interpolated ITP80 locations varied from 17.3-69.0 m, similarly, the distances extracted from the image pairs of the spatial resolution of 15 m varied from 10.3-70.8 m. From these distance ranges varying tens of meters, the selected image-derived motion vectors of both spatial resolutions were considered to be located on the same rigid plate where ITP80 located. Thus, the differences in the RMSEs and biases between the datasets was assumed to be affected by the compound of discretization uncertainty from different pixel sizes, GPS positioning uncertainty and errors from time-interpolated ITP80. Although the pixel size was enlarged from 4 to 15 m by pixel aggregation, the RMSEs and biases of displacements, directions and velocities did not degrade distinctly. In addition to the discretization uncertainty, possible causes of errors inducing the RMSEs and biases were GPS positioning errors in the ITP80 location records and geolocation errors of the satellite images [17].