## 2 Review Methodology  
The literature review workflow was conducted using the Web of Science database, with the search date appointed as 2 April 2024. The Web of Science (WoS) database was chosen as the database source for identifying relevant journal articles [24; 25; 26]. This decision was based on WoS's comprehensive indexing of high-quality, peer-reviewed journals across disciplines, its advanced search capabilities, and its inclusion of citation metrics, which are critical for evaluating the impact of research. We identified papers researching coastal erosion and shoreline analysis using satellite images from the Sentinel mission and Landsat over the past three years (1 January 2021-1 March 2024). The list of chosen keywords was suggested to ensure all-round coverage and included \"Coastal Erosion\", \"Shoreline\", \"Satellite\", \"Remote Sensing\", \"Earth Observation\", \"Copernicus\", \"Landsat\", and \"Sentinel\". We chose the \"Title\" option in the search table to identify journals' titles containing the keywords \"Coastal Erosion\" OR \"Shoreline\" and utilized the \"AND\" Topic feature to limit the study to the specific subject of interest by including the keywords \"satellite OR remote sensing OR earth observation\". Also, keywords such as \"Copernicus OR Sentinel OR Landsat\" expanded the search scope of the subject. Applying the \"Publication Date\" option, we tuned the search to include only the past three years: \"1 January 2021-1 March 2024\". The timeframe was chosen mainly due to the Sentinel mission, first deployed in 2015, considering that it has established a research background over the past decade, with significant advancements revealed in research methods in the last three years as we intended to preserve it as a core technology in the review [27]. The search process followed the proposed flow chart of Figure 1, which identified 103 journal articles. We reviewed the articles' keywords, DOIs, topic relevance, titles, and language (English). The screening results were analyzed using Microsoft Excel(r) (Microsoft, Redmond, Washington, DC, USA), sorting the thematic sections using filtering options and classifying the citations from highest to lowest in each thematic section. Figure 1: Flow diagram showing the systematic process reviewing WOS articles: 103 retrieved, screened by titles, keywords, DOIs, and language, yielding 58 eligible articles. The most-cited (at least 3 at the time the literature review was conducted) articles were reviewed by thematic section, technique, and method. The chosen period (2021-2024) captures a time of fast development in the domain of remote sensing, facilitated by the confluence of AI and high-resolution satellite technology. [PERSON] and [PERSON] (2022) [28] exemplified how AI has transformed the work structure of geospatial analysis by maximizing classification accuracy and streamlining processing. Equally, [PERSON] and [PERSON] (2022) [29] showed how the blending of UAV data and big data brought novel paradigms of analysis, allowing for greater insight into coastal monitoring. This is a move toward more sophisticated, AI-capable data processing methods that underpin a number of the studies under review. We only considered the eligibility of articles concerning the scope of our research, with a preference for those with the highest citations [30]. Articles that had been cited a minimum of at least three times during the period of our study, spanning the three-year timeframe of the review, were shortlisted for further consideration. Out of the 103 research papers, only 58 were studied more closely, incorporating remote sensing along different dimensions such as the methodology and the employment of tools and equipment. This approach aims to prioritize highly relevant and impactful articles, always during the timeframe of the research. Articles were selected based on the following eligibility criteria:  
* Minimum of 3 citations (as of April 2024). * Alignment with the study's scope (shoreline detection and coastal erosion).