The article "Shoreline Definition and Detection: A Review" by Elizabeth H. Boak and Ian L. Turner, published in the *Journal of Coastal Research* in 2005, provides a comprehensive review of the methods and techniques used to define and detect shorelines. The authors highlight the dynamic nature of the shoreline boundary, which is influenced by temporal and spatial scales, and discuss the challenges in quantifying its position accurately. They categorize shoreline indicators into two types: visually discernible features (e.g., high-water line [HWL]) and tidal datum-based features (e.g., mean high water [MHW]). A third category, based on image-processing techniques, has emerged more recently. The article reviews various data sources for shoreline investigation, including historical photographs, coastal maps, aerial photography, beach surveys, and digital elevation data from remote sensing platforms. It emphasizes the importance of selecting appropriate shoreline indicators and detecting them within the available data. The most common method of shoreline detection is visual interpretation, which can be subjective and prone to errors. Recent advancements in photogrammetry, topographic data collection, and digital image-processing techniques have improved the objectivity and robustness of shoreline detection methods. The authors also discuss the limitations of traditional shoreline indicators and the need for a process-based definition of detected shoreline indicators. They explore the use of time-averaged images and image-processing techniques to improve the accuracy and repeatability of shoreline detection. The article concludes by emphasizing the ongoing research focus on defining the physical characteristics of shoreline indicators and their relationship to the land-water interface.The article "Shoreline Definition and Detection: A Review" by Elizabeth H. Boak and Ian L. Turner, published in the *Journal of Coastal Research* in 2005, provides a comprehensive review of the methods and techniques used to define and detect shorelines. The authors highlight the dynamic nature of the shoreline boundary, which is influenced by temporal and spatial scales, and discuss the challenges in quantifying its position accurately. They categorize shoreline indicators into two types: visually discernible features (e.g., high-water line [HWL]) and tidal datum-based features (e.g., mean high water [MHW]). A third category, based on image-processing techniques, has emerged more recently. The article reviews various data sources for shoreline investigation, including historical photographs, coastal maps, aerial photography, beach surveys, and digital elevation data from remote sensing platforms. It emphasizes the importance of selecting appropriate shoreline indicators and detecting them within the available data. The most common method of shoreline detection is visual interpretation, which can be subjective and prone to errors. Recent advancements in photogrammetry, topographic data collection, and digital image-processing techniques have improved the objectivity and robustness of shoreline detection methods. The authors also discuss the limitations of traditional shoreline indicators and the need for a process-based definition of detected shoreline indicators. They explore the use of time-averaged images and image-processing techniques to improve the accuracy and repeatability of shoreline detection. The article concludes by emphasizing the ongoing research focus on defining the physical characteristics of shoreline indicators and their relationship to the land-water interface.