Variance‐based shoreline extraction from nearshore video monitoring systems

• Published in: Earth surface processes and landforms Vol. 50; no. 6
• Main Authors: Jaud, Marion, Augereau, Emmanuel, Saint‐Cyr, Titouan, Le Dantec, Nicolas, Delacourt, Christophe
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01.05.2025; Wiley
• Subjects: Cameras; coastal morphodynamics; Coastal morphology; Coastal zone; Coastal zones; Digital Elevation Models; Environmental Sciences; Foreshore; Intertidal environment; Intertidal zone; Morphology; Physical characteristics; Radiometry; shoreline detection; Shorelines; Tidal cycles; Tides; Variance; Variation; Vegetation; Vibrations; video imagery; Wave breaking; Weather; Weather conditions; shoreline detection; intertidal zone; video imagery; coastal morphodynamics intertidal zone shoreline detection video imagery; coastal morphodynamics
• ISSN: 0197-9337; 1096-9837
• DOI: 10.1002/esp.70077

Under the effect of various hydrodynamic forcings, the morphology of the coastal zone and more particularly the intertidal zone is subject to short‐term variations. Capable of autonomous continuous recording, video camera systems offer a good opportunity to capture these short‐term morphological variations. Extracting a topography of the intertidal zone from these videos involves detecting successive shorelines on the foreshore during a tidal cycle by assigning them an altitude. Detecting this shoreline is therefore a key stage. Here, considering the shoreline as the boundary between a moving zone (wave breaking) and a supposedly stable zone, we propose a method based on ‘variance images’ (in reality, calculated as the median for 5 min video of the standard deviations on radiometry of each pixel over 10 s intervals). The method was evaluated at four sites with different geo‐morphological characteristics, different camera installations and with a wide range of weather conditions (including stormy ones). Of the 111 randomly selected images, 73% of the shorelines were correctly detected (reaching 95% for the Ruscumunoc site). These raw results could be further improved by adding a filtering step or by optimising the installation (avoiding mast vibrations, pruning vegetation, etc.). The Digital Elevation Models (DEMs) generated potentially on a daily basis over the intertidal zone will make it possible to study topographic variations under different conditions (reconstructive regime, impact of an extreme event, etc.). This article presents an original, direct and robust method, based on variance images, for shoreline detection from nearshore video monitoring systems. Detecting these successive shorelines on the foreshore during a tidal cycle is a key step to capture short‐term morphological variations.