## 5 Conclusions  
In this study, we highlighted the potential of SAR S1 data in three different sites to identify and monitor coastal morphological changes across different temporal scales. These processes encompass long-term changes in the VL, seasonal fluctuations in beach profiles, inter-annual beach rotation, and changes induced by extreme TWL events. Overall, our analysis indicates that SAR-SL measurements consistently correspond to positions above the high-water mark across all three sites. Moreover, we demonstrated that in certain coastal settings, such as a low-lying beach (e.g., Bull Island), SAR-SLs can effectively monitor coastal change. The annual CR derived by SAR shows a very solid correlation (and low overall error) with a robust and long-term used method (SL change measured by employing time-series VLs). It has also been noted that several factors impact SAR-SL detection, including coastline orientation, coastal topography, radar signal incidence angle, backshore type, and soil moisture. Ongoing research endeavors are focusing on comprehensively understanding the influence of these factors on SAR-based SL detection and the use of the presented conceptual model, which could serve as a valuable reference for future studies focused on understanding and interpreting SAR-SLs. This deeper understanding will be instrumental in deriving consistent and accurate SAR-SLs for useful coastal change assessments. Moreover, this research shows that SAR data offer advantages over optical data in areas where the use of optical data is challenging, as SAR S1 enables the monitoring of high-frequency coastal dynamics due to its provision of dense shoreline time-series data compared with optical S2. In conclusion, this study illustrates the effective utilization of SAR images to monitor and understand coastal morphological changes across varying temporal scales and coastal environments. It presents a new methodology to specifically monitor some coastal settings as an alternative to what is currently available in the scientific community, and it proposes the next steps for the future research to unravel the intricate dynamics and factors influencing SAR-SL detection. Conceptualization, S.S., J.M.S., A.P., A.G.-M. and X.M. ; methodology, S.S., P.G.d.S., J.M.S., A.G.T., A.P., A.G.-M. and X.M. ; waterlines extraction software, S.S., M.E.P. and A.G.-M.; validation, P.G.d.S., J.M.S., A.G.T., A.P., X.M. and Y.C. ; formal analysis, S.S., J.M.S., A.P., A.G.-M., X.M. and Y.C. ; investigation, S.S., P.G.d.S., A.P. and X.M. ; resources, A.G.T. and A.P. ; data curation, S.S.; writing--original draft preparation, S.S., J.M.S., A.P. and X.M. ; writing--review and editing, S.S., P.G.d.S., A.P. and X.M. ; visualization, S.S., A.G.T. and A.P. ; supervision, A.G.-M.; funding acquisition, J.M.S., A.P., A.G.-M. and X.M. All authors have read and agreed to the published version of the manuscript. This work was financially supported by the Coastal Erosion From Space project, which was funded via the Science for Society allocation of the 5 th Earth Observation Envelope Programme (EOEP-5) of the European Space Agency. A.P. was funded by the CHAMFER project (NE/W004992/1). This study forms part of the ThinkInAzul programme and was supported by Ministerio de Ciencia e Innovacion with funding from European Union NextGeneration EU (PPRT-C17.I1) and by Comunidad de Cantabria. The data presented in this study are available upon request from the corresponding author. A.P. acknowledges the contribution of [PERSON] to the initial analysis of SAR data in Start Bay. J.M.S., P.G.d.S. and A.G.T. acknowledge the Ministry for the Ecological Transition and the Demographic Challenge of the Government of Spain for providing the beach subaerial topography data used for the evaluation of the Salinas study site. **Conflicts of Interest:** Authors [PERSON], [PERSON] and [PERSON] were employed by the company isardSAT UK.