## 4 Discussion
The Salinas area (Figures 3, 4, 6 and 7) shows different deformations resulting from terrain instabilities detected thanks to the combined use of the two software tools. In this case, the GEP platform has detected more active PS than PSIG. In the first case, the detected deformations are directly produced by the effects of the sea on the shoreline (Figure 7c, TB-IIa and TB-IIb). The VLOS present rates from \(2.7\)-\(2.8\) mm year\({}^{-1}\), with accumulated displacements of \(6.1\) and \(7.5\) mm. The coastline here is the seafton of Salinas, which was affected by severe storms [65]. These extreme episodes have produced collapses in the seafton and important beach and dune erosion [46; 66]. According to [65], this area is located in a zone with high coastal recession and erosion. At this point, these authors have measured a change in the vertical distance between the top of the seafton promenade and the upper beach of \(-2.9\) m between 1998 and 2010. In the second case (Figure 7c, TB-IIIa and TB-IIIb), the detected ground motion may be related to slope instabilities, since at this location, two mass movements occurred in November 2003 and June 2010 [46]. The involved materials are slope and rasa deposits, both composed of siliciclastic pebbles and abundant clay matrix. In this study, we have demonstrated that the GEP service can be a useful tool to detect and monitor ground motion at a local scale. GEP had already proven itself as a powerful tool to identify and monitor soil instabilities on a regional scale [59]. However, it has not been possible to directly relate the areas prone to instabilities with the A-DInSAR results (Figure 7). With respect to this problem, we were able to observe and demonstrate the main limitation factors: (i) the orientation of the terrain; the principal zone of slope instabilities in Salinas presents a NE orientation (Figure 7), thus, slope movements are parallel to satellite sensor displacement direction. Therefore, these movements are practically impossible to detect by A-DInSAR. (ii) The high inclination of the slopes, which produces a foreshortening effect [67] and, therefore, a drastic reduction of the spatial resolution. (iii) The velocity of the landslide development; the nature of the slope instabilities, which are mainly rockfalls and flows, with movement velocities ranging from slow to extremely fast (\(>\)13 m month\({}^{-1}\)\(\rightarrow\)5 m s\({}^{-1}\)). Consequently, these slope instability typologies are undetectable by A-DInSAR [47]. Regarding Asturian coastal retreat data, at present, there are very few quantitative data, with rates ranging from \(0.25\) and \(2.19\) m year\({}^{-1}\)[45]. These authors have evaluated different retreat rates in several local sectors (Table 5). In this research, we have identified different LOS velocity rates and LOS accumulated displacements for the same local areas (Table 5). An important point to consider is that the zones reclaimed from the sea have a high incidence of movements and also significant damage to the civil and port infrastructures [68; 69]. In this study, the most intense deformations have been found in the Musel port (Figures 4 and 5B and Table 3). These ground motions are directly related to differential settlements in unconsolidated soils and coastal processes, as has been mentioned in other areas [69]. In addition, we should highlight that between 2006 and 2017, there were several important meteorological events. For example, in June 2010 and February 2014, there were storms and intense rainfall episodes. These events resulted in numerous instabilities and damage along the Asturian coast [44; 45; 46]. The majority of landslides registered [46] are rockfalls, flows, and undetermined events. According to [44; 45], these movements were directly associated with littoral and gravity processes. However, as we mentioned above, these slope instabilities cannot be measured by A-DInSAR due to their high velocity and sudden development.