## 2 Materials and Methods
### Experiments  
The purpose of the experiment is to evaluate the accuracy in the reconstruction of 3D models using images obtained from the variation and combination of different parameters of flight planning and data capture (digital photographs); specifically, variations in the combinations of camera angles (vertical-oblique), image overlaps and flight height, relative to a study surface that simulates a deteriorating pavement with bumps of different size, with the specific purpose of extrapolating the results to actual pavement. Accuracy was assessed from the comparison of the actual values versus the measurement made in each of the 3D models reconstructed from the data obtained by each flight, according to each of the defined plans. The study surface corresponds to a rectangular prism of plaster, which has been treated with surface paint for the purpose of simulating the characteristic color of an asphalt pavement, as seen in the Figure 3. Seven concave surfaces of different sizes were made on the study surface, the characteristics of which are exposed in Table 1, each responding to different sizes and severities, according to [12], to assess the capture sensitivity of the sensor or camera. There are three levels of severity to classify potholes: low severity is a pothole with a depth less than 30 mm, mean severity is between a depth of 30 to 50 mm and high severity must be greater than 50 mm. Figure 3: Study surface. (**a**) Reconstructed surface. (**b**) Real surface. Data capture from the study surface was performed in a place free of objects that may cause shadow. In addition, these were made on sunny days, starting the capture of images at 12:52 P.M. until 14:52 P.M. (hours with less shadow), without the presence of clouds that could alter the color tones in the images. The combination of analyzed variables includes the incorporation of oblique photographs into the set of photographs taken perpendicular to the terrain (vertical), overlap between photographs and flight height. The values of the variables and the justification of that value are detailed below:  
* Incorporation of oblique photographs into a set of vertical photographs; due to the lack of research on the effect of incorporating vertical photographs with oblique images and their influence on the accuracy of the 3D model in cases of pavement inspection, this research was carried out in order to evaluate the accuracy of the results obtained through this configuration, which combined the cases of 90\({}^{\circ}\), 90\({}^{\circ}\)-80\({}^{\circ}\), 90\({}^{\circ}\)-70\({}^{\circ}\), 90\({}^{\circ}\)-60\({}^{\circ}\), 90\({}^{\circ}\)-45\({}^{\circ}\). Vertical photos with any combination have twice as many images compared to 90\({}^{\circ}\), as it only has the corresponding set of photos. * Overlap: the longitudinal/transverse percentage overlap considered for the development of the research was 75/68, 80/72, 85/77 and 90/81. These overlapping levels covered the vast majority of usual configurations according to state of the art for road inspection cases. * Heights: The heights considered for analysis are 2, 5, 8, 10, 15, 20, 25, 30 and 40 m. This is because it is intended to achieve precisions of under one centimeter, so 40 m would be the limit in terms of the value of GSD (GSD (40 m) \(\times\) 1.07 cm/pixel). In summary, 180 configurations are shown in Figure 4. These describe the combination of the variables that influence the accuracy of the model obtained by UAV SfM-MVS. \begin{table}
\begin{tabular}{c c c c c} \hline
**Pothole [\#]** & **Diameter [mm]** & **Deep [mm]** & **Volume [cm\({}^{3}\)]** & **Severity Level** \\ \hline
1 & 19.0 & 8.5 & 1798 & Low \\
2 & 37.0 & 21.0 & 13,274 & Low \\
3 & 57.0 & 27.0 & 48,478 & Low \\
4 & 79.0 & 38.0 & 129,102 & Middle \\
5 & 100.0 & 50.0 & 261,804 & Middle \\
6 & 151.0 & 74.0 & 901,373 & High \\
7 & 200.0 & 101.5 & 2,094,398 & High \\ \hline \end{tabular}
\end{table} 
Table 1: Characteristics of studio surface potholes.