## 4 Discussion  
The drone surveying has been limited for long-term ground settlement measurement because few studies have been carried out. Therefore, this study applied drone LiDAR surveying for long-term ground settlement measurement at a very large land reclamation area with soft ground near harbor facilities to check its applicability and accuracy. To this end, periodic drone surveying was carried out for about one and a half years to measure the ground settlement. The vertical accuracy of the surface from the LiDAR surveying was compared to settlement ground truth points acquired using engineering levels. The results from the graph of embankment heights and cumulative settlements showed differences of \(-\)185 mm to +6 mm, resulting in 13 cm RMSE errors. Compared to recent drone LiDAR vertical accuracy results of [PERSON] et al. (2017), [PERSON] (2013), and [PERSON] et al. (2014), the error range seems reasonable. The accuracy may be improved, but the uneven surface around the points of embankment soil was an obstacle. Note that the embankment soil specification is less than 0.03 m\({}^{3}\)/EA, with each rock showing about less than 30 cm in width. The reduction \begin{table}
\begin{tabular}{c c c c} \hline
**Location** & **R\({}^{2}\)** & **Predicted Settlement (m)** & **Consolidation (\%)** \\ \hline K-SK-10 (surface) & 0.988 & 3.162 & 67.1 \\ K-SK-10 & 0.968 & 3.154 & 62.2 \\ K-SK-10-001 & 0.990 & 2.560 & 71.1 \\ K-SK-10-002 & 0.990 & 2.629 & 73.0 \\ K-SK-10-003 & 0.935 & 3.737 & 60.2 \\ K-SK-10-004 & 0.895 & 1.788 & 94.7 \\ K-SK-11 (surface) & 0.991 & 2.293 & 62.7 \\ K-SK-11 & 0.943 & 2.485 & 57.1 \\ K-SK-11-001 & 0.922 & 2.034 & 62.6 \\ K-SK-11-002 & 0.968 & 2.018 & 59.0 \\ K-SK-11-003 & 0.968 & 2.479 & 53.5 \\ K-SK-11-004 & 0.934 & 3.477 & 49.3 \\ \hline \end{tabular}
\end{table} 
Table 6: Predicted settlements and rates of consolidation of each point using drone survey at K-SK-10 and K-SK-11. Figure 13: Settlement graphs of sites near K-SK-10 and K-SK-11. of the vertical error may be achievable with large, stable surface drone survey targets. However, this was not carried out and is a major limitation of the study. Installing large and flat surfaces to isolate the uneven soil effects should be considered for future studies. The periodic drone LiDAR surveying enabled long-term settlement and consolidation prediction based on the hyperbolic method. The settlement prediction showed \(-906\) mm to \(+192\) mm with \(49.2\) cm RMSE errors. As [PERSON] et al. [25] reported, long-term settlement prediction based on conventional surface measurements showed errors in the range of dozens of centimeters compared to ground truth settlement. Therefore, the prediction results from the drone LiDAR surveying, showing less than \(50\) cm, seem reasonable. In addition, the predicted consolidation rate ranged from \(-5.56\%\) to \(+8.44\%\), resulting in \(6.23\%\) RMSE errors. This error seems within the controlled value, as typical consolidation predictions show large differences, such as up to more than \(10\%\) for each prediction method, as reported in [PERSON] and [PERSON] [26]. Therefore, the long-term settlement and consolidation predictions, less than \(50\) cm and \(10\%\), respectively, can serve as valuable reference information to control embankment progress and stability of the soft ground with large settlement. The study continued to carry out the settlement and consolidation prediction for \(8\) more points where no settlement was installed (see Figure 12). The points K-SK-10 \(.004\) showed relatively smaller settlement than those near K-SK-10 in Figure 13. K-SK-10\(.004\) seems to be affected by the nearby CY1-15 embankment, which was completed in Dec 2020 before CY2-04 (Jan 2021). K-SK-11\(.004\) showed relatively larger settlement than the area near K-SK-11 in Figure 13. This is because the embankments of CY3-10 and CY3-11 were completed in Feb 2021, which had a more significant impact on the settlement of K-SK-11\(.004\) than on K-SK-11.