## 3 Results
### Regional Analysis of Coordinate Differences
This difference highlights that processing methodology can influence not only the absolute positions but also the dispersion of results, particularly in edge regions. Additionally, Chungnam province shows a modest but clear eastward bias in the Bernese solution (mean \(\Delta\)E: +0.28 cm). Such a bias could originate from regional asymmetries in the station distribution or differing treatments of atmospheric delay, antenna phase center variations, or mapping functions. Table 4 directly compares the GAMIT/GLOBK and Bernese solutions to assess their internal consistency. Overall, differences between the two processing approaches remain well within the sub-centimeter level for most provinces, indicating a strong degree of methodological convergence. However, systematic discrepancies are still present in specific areas. For instance, Gyeongbuk shows a noticeable northward bias (mean \(\Delta\)N: +0.35 cm), while Chungnam exhibits a westward bias relative to Bernese (mean \(\Delta\)E: \(-\)0.37 cm). These offsets, though modest, could signal underlying differences in reference frame realization or baseline weighting strategies between the two software packages. Once again, Jeonnam shows the highest level of variability, with the north component RMS reaching 2.55 cm. This is consistent with the patterns observed in both Tables 1 and 2, reinforcing the notion that this region is particularly sensitive to network design, processing assumptions, or possibly local instabilities. Taken together, the results from all three tables highlight a few key observations. First, both GNSS solutions reproduce the KGD2002 frame with high accuracy at the national scale. Second, regional discrepancies do exist--typically on the order of 1-3 mm but occasionally exceeding 2 cm in terms of RMS. These discrepancies are most pronounced in provinces with challenging network geometry or known environmental complexity. Finally, the repeatability and divergence across processing strategies provide useful diagnostic information. They not only indicate areas that may require closer geodetic control or reprocessing but also suggest that future adjustments or frame transitions should account for such regional sensitivities. These numerical differences provide a statistical overview of regional discrepancies in coordinate estimates. To better visualize the spatial characteristics and relative magnitude of these differences, a graphical comparison of horizontal RMS errors by province is presented. Figure 5 summarizes these regional RMS values, offering an intuitive assessment of consistency between solutions and highlighting areas of elevated scatter. Figure 5 presents a regional analysis of horizontal root mean square (RMS) differences among coordinate estimates derived from GAMIT/GLOBK, Bernese, and the KGD2002 reference frame. Each bar represents the horizontal RMS value (in mm) calculated from the \(\Delta\)N and \(\Delta\)E components for each province. Blue bars correspond to the RMS of differences between GAMIT and Bernese solutions, red bars represent the differences between GAMIT and KGD2002, and yellow bars show the differences between Bernese and KGD2002. Figure 5 presents the horizontal RMS differences per province in bar chart form, highlighting that Jeonnam and Gyeongbuk tend to show relatively larger discrepancies regardless of the comparison pair. To further visualize the spatial distribution of these differences, Figure 6 illustrates the regional RMS values for each comparison--GAMIT vs. KGD2002, Bernese vs. KGD2002, and GAMIT vs. Bernese--using color-coded maps. In the left panel (GAMIT-KGD2002), the largest RMS differences appear in Gyeongbuk (orange) and Jeonnam (green-yellow), suggesting greater variability in those areas. The middle panel (Bernese-KGD2002) shows a generally lower and more uniform distribution of RMS values, with most regions shaded in blue, indicating values under 10 mm.