## 3 Results
### Analysis of Coordinate Differences
The direct comparison between GAMIT and Bernese reveals slightly more variability, underscoring the practical importance of consistent processing strategies in high-precision GNSS applications. In both cases, the RMS values are nearly identical to the standard deviations, reflecting the fact that the mean differences are near zero and systematic biases are negligible. Notably, the Bernese solution exhibits a slightly lower SD in both components--by approximately 0.001 m (1 mm)--compared to the GAMIT/GLOBK solution. This suggests that the Bernese-derived coordinates are marginally more internally consistent, with a slightly tighter distribution around the official KGD2002 values. While the difference in scatter is small, it is discernible given the large sample size and the precision of the data. To further assess the spatial agreement among the coordinate solutions in a fully three-dimensional context, we constructed 3D scatter plots of the residuals in local East-North-Up (ENU) coordinates, as shown in Figure 11. This representation complements the previous 2D horizontal analyses by incorporating the vertical component (\(\Delta\)U), thereby enabling a more comprehensive evaluation of the geometric consistency of the solutions. Points exceeding \(\pm 1\sigma\) in any dimension are highlighted in red to emphasize potential outliers and to better visualize the volumetric distribution of residuals. Figure 10: Comparison of horizontal coordinate differences in topocentric East–North–Up (ENU) components for three solution pairs: GAMIT/GLOBK vs. KGD2002 (**left**), Bernese vs. KGD2002 (**center**), and GAMIT/GLOBK vs. Bernese (**right**). Each column shows the following, from top to bottom: a 2D density contour map of \(\Delta\)E vs. \(\Delta\)N residuals, a corresponding scatter plot, and a polar histogram of the horizontal residual directions. All panels share the same axis scaling for consistent visual comparison. In the GAMIT vs. KGD2002 comparison, the residual distribution appears generally more isotropic and concentrated, with noticeably fewer outliers than in the other cases. This suggests not only that the GAMIT/GLOBK solution is highly consistent with the official KGD2002 coordinates but also that it maintains a well-balanced internal precision across all three components--AN, \(\Delta\)E, and \(\Delta\)U. The uniformity in the spread of the residuals across spatial axes implies that errors are not directionally biased, and that the coordinate differences are spatially symmetric. This behavior may reflect effective network-scale adjustment, the use of distance-dependent weighting schemes, or error-canceling mechanisms related to the observation geometry and processing configuration. In contrast, the GAMIT vs. Bernese residuals, while still showing good overall agreement, exhibit noticeably greater spread in the vertical (Up) direction. This indicates that although horizontal components are well-aligned, vertical discrepancies are more prominent, with several residuals extending away from the center in the \(\Delta\)U dimension. The broader distribution in height differences likely reflects differences in how the two software packages handle vertical positioning. Such discrepancies may arise from distinct definitions of local reference frames, ellipsoidal height modeling strategies, or tropospheric correction methods. For instance, Bernese might be more sensitive to baseline geometry in vertical estimation due to its processing approach, while GAMIT/GLOBK may apply more conservative weighting to the Up component. Even subtle differences in vertical constraints, elevation weighting, or height-dependent error mitigation techniques can result in the kinds of residual asymmetry observed here. Ultimately, the elevated dispersion in the vertical direction in the GAMIT vs. Bernese comparison suggests that the differences go beyond simple alignment errors and may reflect underlying algorithmic and modeling distinctions in how the two processing systems optimize and distribute positional uncertainties.