## 5 Discussion  
Traditionally, in many aerial and terrestrial photogrammetric applications, using a good network of GCPs has been shown to be an important prerequisite to guarantee the quality of the SfM reconstruction (e.g., [14; 16]). In the framework of a coastal observatory, such as DYNALIT, using recurrent surveys for monitoring beach and cliff morphodynamics, measurement quality is critical for producing reliable estimates of sediment budgets and, hence, for assessing the tendency to erosion for a particular section of the coast. Yet, the necessity to adopt a protocol as simple, quick, and standardized as possible to limit the operator dependency of the results is perhaps as much important when considering repeated surveys. When compared to field applications of photogrammetry using a GNSS for independently measuring GCPs distributed on the ground, our approach replaces the GCPs by a solid frame connecting the camera and the GNSS antenna. Not requiring GCPs, this RTK GNSS-assisted method enables saving time in the field, since it is notorious that setting up a good network of GCPs can be time consuming, and it also reduces the bulk of the equipment needed on site. Furthermore, it is sometimes impracticable to use GCPs in some parts of the study site because of inaccessibility or the impossibility of GNSS measurement due to obstructions (e.g., cliff, trees). The GNSS-assisted method also enables avoiding the time-consuming step of GCP identification, whereby GCPs must be identified from photographs during the photogrammetric processing. In terms of the quality of photogrammetric results, the independency to GCP distribution limits the risks of geometrical distortions in the SfM reconstruction induced by poor GCP distribution [18]. In the present work, we achieved centimeter-scale accuracy without the need for a-priori camera calibration. The latter is important for process simplification and for the larger uptake of the technique, including outside academic circles. Furthermore, as the GNSS antenna and the camera are aligned on the same vertical axis, our system enables taking several pictures from the same position by spinning the camera. This fan-shaped acquisition enhances the image overlap, which is favorable for bundle adjustment. Furthermore, we obtained highly satisfying results, with mean errors lower than a centimeter, whereas previous studies achieved absolute accuracies on check points ranging from 4 to 7 cm [25]. That can be due to the fact that previous work concentrated on applications in an urban area, where the GNSS signal is not optimal. Moreover, we simplified the method by aligning our RTK GNSS antenna and our camera along the same vertical axis, reducing the number of additional measurements. Among other advantages, the system that we present is simple to implement, low cost (as the frame can be custom-built out of simple wood), versatile (it is compatible with any GNSS antenna and virtually any type of cameras from bulky reflex to Smartphone cameras), and it offers long autonomy, enabling long survey sessions, only being limited by the GNSS battery autonomy (in our case, around 4 h for a battery). The operator time during processing is drastically reduced, since no GCP pointing on the photographs is needed. Throughout the tests that we performed, the method provided very satisfying results, both in terms of point density and accuracy, even near a cliff face, which must rate as a difficult measurement site because of the obstructed view of the satellite constellation, of the complex geometry of the face with concavities, fissures, and vegetated areas. This approach is very promising for cliff face reconstruction, since it is very difficult to install GCPs in this environment and given that a terrestrial point of view is favorable to capture its complexity.