## 3 Results
### Underwater Photogrammetric Model
#### 3.2.2 Underwater Georeferenced Model  
As previously mentioned, 41 positions of the snorkeler were computed. However, not all these positions were usable, as in some cases the snorkeler was passing over deep water areas, making it impossible to orient the underwater images with the model. This highlights a limitation of the methodology, as it depends on depth and water transparency for constructing underwater models. After filtering the data, 21 useful positions were  
Figure 9: Manual camera calibration with parameters estimated from. retained, where clear underwater visibility allowed for accurate image orientation. From these 21 positions we could evaluate the error by BBA (Table 1). The average error for the \(x\) coordinate is 0.068 m, while the \(y\) coordinate exhibits a slightly higher of 0.093 m, resulting in a total mean error of 0.080 m. The standard deviation reveals greater variability in the \(y\) direction (0.09 m) compared to the \(x\) direction (0.05 m). The error distribution also shows a wider range for \(y\) direction with a maximum error of 0.34 m, whereas the \(x\) axis reaches a maximum error of 0.16 m. The minimum error across both axes remains low, starting at 0.01 m for both \(x\) and \(y\), indicating that some measurements are highly accurate. This distribution suggests that while overall errors remain relatively small, the system or process might face more challenges maintaining accuracy along the \(y\) axis. Evaluation of the total error is presented in the histogram reported in Figure 10.  
The histogram of overall error presents a frequency distribution of error values ranging from approximately 0.025 m to 0.200 m. The highest frequency of errors falls within the 0.025 m to 0.050 m range. As the error increases, there is a notable decline in frequency, with moderate frequencies between 0.075 m and 0.100 m, and a further decrease as the error exceeds 0.100 m. This distribution shows that while the majority of data points exhibit small errors, some outliers are present. To further explore the source of this variability, the data were categorized into two groups based on the snorkeler position in the orthophoto: \"M\" for positions in the middle area, and \"B\" for positions near the boundary area of the orthophoto used to estimate the snorkeler's position. Statistical analysis (Table 2) shows \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Error [m]** & \(x\) & \(y\) & **Total** \\ \hline Mean & 0.068 & 0.093 & 0.08 \\ \hline Standard deviation & 0.05 & 0.09 & 0.05 \\ \hline Minimum & 0.01 & 0.01 & 0.02 \\ \hline Maximum & 0.16 & 0.34 & 0.19 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Error analysis over \(x\) and \(y\) coordinates and the total error in meters. Figure 10: Histogram shows the frequencies of the overall error (expressed in meters) of \(x\) and \(y\) coordinates. that frames in category \"M\" tend to have lower and less disperse errors, with a narrower range of values. In contrast, category \"B\" exhibits both higher mean error and greater variability, indicating more pronounced inaccuracies and potential outliers. A scatter plot of the \(x\) and \(y\) errors by category further supports these findings, with category \"B\" displaying a wider spread of errors compared to the more tightly clustered errors in category \"M\" (Figure 11). This suggests that frames categorized as \"B\" are less accurate, potentially due to frame distortions between the middle and boundaries of the orthorectified images. Following the error evaluation, the underwater 3D models were constructed from the collected images and georeferenced using the computed coordinates from the orthorectified images. These 3D models captured various features on the seabed, including rocky regions, sandy areas, and the presence of both healthy and dead seagrass. This detailed representation of the underwater environment highlights the method capability to accurately capture and represent diverse seabed characteristics, providing valuable insights for coastal management and conservation efforts.