## 3 Materials and Methods  
To monitor the restoration work, a HORUS type video monitoring system was chosen, the scheme of which is shown in Figure 2. The system consists of a battery of digital cameras, which were placed in several locations of a certain height (posts, buildings, etc.) so that we could observe the entire study area. The cameras were connected to a local computer that stored the information and transmitted it to another processing computer in real time, which is where the image processing software is installed. The number and location of cameras that need to be installed in a monitoring station is defined according to the dimensions of the study area. To this effect, it is important to take into account concepts such as spatial resolution, which refers to the minimum size that an object must have to be recognized within the image, and which depends on the distance to the camera of the region of interest and the number of pixels that its sensor has [8]. In this case, we decided to use the battery of three cameras (Stingray F-504C model from the AVT company) on a 12-m post, in the south end of the bridge, as can be seen in Figure 3.  
Figure 2: Configuration of HORUS type video monitoring system. On the other hand, Figure 4 shows the orientation and area of coverage of each of the cameras installed in the La Rabia estuary, depending on the orography and their resolution. Figure 4: Orientation and area of coverage the cameras in the La Rabia estuary. Figure 3: Spatial placement of the cameras in the La Rabia estuary. It is important to calibrate the camera before associating an image to a real word coordinate system (x, z, y). For this purpose, the HORUS software provides the pinhole model [9] based on the principle of collinearity, in which each point of an object in space is projected into the image by a straight line passing through the focal point of the camera. Thus, the coordinates of the camera's focus (Xc, Yc, Zc) are established according to the coordinate system of the object. Then, a point from the object is taken in space (x, y, z) and its corresponding projection in the image will be found in the coordinate points u, v [8] as can be seen in Figure 5.  
For the HORUS system to solve the pinhole model, it is necessary to know the position (x, y, z) of at least six points that appear within the image, called ground control points (GCP). With the aim of applying the calibration process previously described to the La Rabia estuary monitoring station, a topographic field campaign was carried out to determine the position of certain observable points in the space from the three cameras of the station. Figure 6 shows all of the control points selected for Camera 1. In the first place, the bases of the bridge's footbridge were taken as fixed points (green circles in Figure 6a). On the other hand, due to the fact that there is no type of building that allows any GCP to be fixed beyond the bridge, we opted for the construction of flat and square plastic targets with a vinyl layer (Figure 6b) which facilitates image visualization while ensuring high longevity in exposed areas close to the coast. These targets were coupled to wooden structures in order to establish fixed points on the hillsides in front of Camera 1 (Figure 6b,c). Figure 5: Representation of the collinearity principle for the camera projections. Following the same process for Camera 2 and Camera 3 of the \"La Rabia\" station, the control points shown in Figures 7 and 8 were taken, where the green circles indicate that they are fixed control points, while the red circles refer to those taken with the targets. Figure 6: Points of selected field controls for Camera 1. (**a**) Fixed points at bridge’s footbridge. (**b**) Vinyl layer plastic targets. (**c**) Fixed points made by vinyl targets coupled to wooden structures. Figure 7: Points of selected field controls for Camera 2. In total, 47 control points were established for Camera 1, 40 for Camera 2, and 29 for Camera 3.