## 4 Discussion and Conclusions
Using ChkPts measured with RTK-GNSS enabled the assessment of both the horizontal and vertical error in RTK-assisted photogrammetry, showing a similar tendency to the DoD analysis, whereby 5 GCPs were necessary to achieve optimum accuracy and precision. Under this configuration, the global 3D precision (RMSE) remained below 0.05 m (3.6 GSD). We observed larger horizontal error over vertical error (ratios as large as 1:4), which is contrary to most previous research, where, generally, horizontal error is the lower bound (e.g., Refs. [46; 56]). A reason may be the use of suboptimal photogrammetric targets for the present study. The targets we used had no marks at the center point where RTK-GNSS measurement is carried out, meaning that the target geolocation in the images can be prone to large horizontal uncertainties. The targets have been upgraded recently to include a chequerboard-like pattern, which has been recommended for pinpoint accuracy in RTK-GNSS measures and image positioning [71]. Nevertheless, we showed that error evaluation using ground targets can produce optimistic estimates, particularly when the error is evaluated at GCPs (used for photogrammetric processing). A difference in the error estimates between GCPs and ChkPts was also identified in [PERSON] et al. [46], where it was suggested using a magnification coefficient to artificially inflate the error measures in the absence of independent ground controls (i.e., ChkPts). Although it may prove useful for guessing the precision within results (SDE), we showed, however, that using GCPs failed at detecting bias in the measurements, thus reinforcing that, ideally, numerous and well-distributed independent ChkPts should be used to characterize the DEM error. Larger-scale experiments were conducted at La Palue field site to validate the workflow. Three operators were necessary to carry out the field operations, which included GNSS measurements of \(\sim\)20 photogrammetric targets distributed over the whole beach (\(\sim\)2500 \(\times\) 400 m\({}^{2}\)), using the bike-mounted GNSS to acquire ground truth data near the water line, performing all the flights, for finally removing the targets, all within a two-hour window around low tide. Five \"permanent targets\" were prepared before the September survey, consisting of red-painted crosses. They were created over flat and stable areas of the study site, all man-made and localized above the highest high tides so as not to introduce error in photogrammetry, which could otherwise arise due to imprecise identification in images or terrain changes. This means, however, that the spatial distribution of these permanent targets was limited to the landward side of the site. Between 177 and 1381 RTK-GNSS survey points were used to assess the photogrammetric reconstruction for different processing scenarios (e.g., varying image resolution) both before and after model densification. In comparison to Sillon de Talbert, the best-case vertical precision achieved at La Palue was slightly worse, which may be related to an increased flying height and the different error evaluation methods used. Larger DEM error was measured at peripheral zones where the effective overlap index (i.e., apparition in images) is reduced, which is consistent with previous observations (e.g., Refs. [44; 46; 72]). Although of a small magnitude, the effect was increasing measurement noise and potentially centimeter-scale deformations of the photogrammetric model. Enlarging the survey area, especially on the seaward side (e.g., by adding an additional alongshore flight track), could strengthen the photogrammetric block and reduce the error at these distant locations. Regardless of the model densification, the DEM errors showed a similar pattern (Figure 5), reinforcing the fact that the DEM shape is essentially the result of image alignment and photogrammetric optimization taking place before dense point matching.