The transition between land and water, in practice often taken as the intersection of mean high water and the shore.
The terms shoreline and coastline are often used indiscriminately as synonyms. However, it is generally preferable to define the shoreline as the physical transition between land and water and the coastline as a proxy of the shoreline position that designates the boundary between land and sea for use in shoreline management, see the article Coastline.
The line delineating the shoreline on Nautical Charts (Sea Maps) approximates the Mean High Water (MHW) line.
Shoreline detection techniques
A large number of techniques can be used to determine the shoreline. A brief overview of the main techniques is given below.
Aerial photography. Today, drones are most commonly used for this purpose. Software is available for georectification of the images and extraction of the shoreline.
LIDAR aerial beach surveys. Digital elevation maps (DEMs) of the beach can be obtained by airborne LIDAR at low water. High costs are an impediment for frequent surveys.
Video Imaging. The video cameras are installed at a fixed location at sufficient height for covering a coastal stretch of up to 2 km length. Argus video monitoring technique enables the detection of shoreline evolution and beach width, erosional and accretional sediment volumes of the intertidal beach, subtidal beach bathymetry and wave run-up, see Argus applications.
Fixed LIDAR laser scanners. A rooftop-fixed scanning LIDAR provides very high frequency and high spatial resolution data of various morphological and hydrodynamic features, similar to Argus video, but with higher accuracy.
Surfcams. Recreational surf cameras existing in many popular surf destinations can be used for shoreline detection if properly calibrated, using advanced geo-referencing techniques.
GPS surveys. Use of a kinematic differential GPS mounted on a four-wheel-drive vehicle, which is driven at a constant speed along the visibly discernible line of interest. This method is relatively rapid, low cost, and highly accurate.
CoastSnap. An application of smartphones to obtain crowd-sourced photos of beaches supplied by the community via digital media platforms. The underlying concept of CoastSnap (https://www.facebook.com/coastsnap) is that a mounting bracket is installed at sites of interest to provide a fixed location and camera view angle, where community participants can then place their own phone and take a snapshot.
Satellite images. Publicly available optical satellite images have a progressive increasing resolution and decreasing revisit period which make them suitable for shoreline detection: 80 m pixel size, revisit period 18 days for Landsat missions 1–3 (1972–1983), 30 m and 16 days for Landsat 4–8 (1982 – present) and 10 m and 5 days for Sentinel-2 (2015 – present). A refined version of the sub-pixel resolution shoreline detection technique has been developed by Liu et al. (2017)  and later augmented with the addition of an image classification component to refine the detection of the sand/water interface. In this way the horizontal root-mean-squared error can be reduced to less than about 10 m.
All the above described techniques require corrections for tide and wave run-up. Tide correction requires knowledge of the beach slope and the time at which the shoreline position was determined. The beach slope can be derived from satellite images. By using wave run-up formulas it is possible to determine the correct average shoreline position.
- CIRIA (1996). Beach management manual. CIRIA Report 153.
- Boak, E.H. and Turner, I.L. 2005. Shoreline definition and detection: a review. J. Coast. Res. 214: 688–703
- Splinter, K.D., Harley, M.D. and Turner, I.L. 2018. Remote Sensing Is Changing Our View of the Coast: Insights from 40 Years of Monitoring at Narrabeen-Collaroy, Australia. Remote Sens. 10: 1744
- Liu, Q., Trinder, J. and Turner, I.L. 2017. Automatic super-resolution shoreline change monitoring using Landsat archival data: a case study at Narrabeen–Collaroy Beach, Australia. J. Appl. Remote Sens. 11: 016036
- Vos, K., Harley, M.D., Splinter, K.D., Simmons, J.A. and Turner, I.L. 2019. Sub-annual to multidecadal shoreline variability from publicly available satellite imagery. Coastal Engineering 150: 160–174
- Vos, K., Harley, M.D., Splinter, K.D., Walker, A. and Turner, I.L. 2020. Beach Slopes From Satellite-Derived Shorelines. Geophys. Res. Letters 47: e2020GL088365
- Castelle, B., Masselink, G., Scott, T., Stokes, C., Konstantinou, A., Marieu, V. and Bujan, S. 2021. Satellite-derived shoreline detection at a high-energy meso-macrotidal beach. Geomorphology 383: 107707
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