A fully automated method for monitoring the intertidal topography using Video Monitoring Systems
| Autor: | Ángel David Gutiérrez Barceló, Nicolas Lecoq, Benoit Laignel, Olivier Maquaire, Stéphane Costa, Benjamin Bazin, Antoine Soloy, Imen Turki, Loïc Le Louargant, Yves Soufflet |
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| Přispěvatelé: | Morphodynamique Continentale et Côtière (M2C), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), SandS Corp S.I., Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Brest (UBO)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (Nantes Univ - IGARUN), Nantes Université - pôle Humanités, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Humanités, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Echanges Côte-Large (ECOLA), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), ANR-16-CE03-0008,RICOCHET,Évaluation multirisques de territoires côtiers en contexte de changement global(2016) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Intertidal topography
Coastal morphodynamics Mask R–CNN Environmental Engineering 010504 meteorology & atmospheric sciences 010505 oceanography Intertidal zone [SDU.STU]Sciences of the Universe [physics]/Earth Sciences Ocean Engineering Context (language use) 01 natural sciences Training (civil) Water level Waterline symbols.namesake symbols Environmental science Segmentation Coastal video monitoring Noise (video) Scale (map) Pebble beach 0105 earth and related environmental sciences Remote sensing Shoreline detection |
| Zdroj: | Coastal Engineering Coastal Engineering, 2021, 167, pp.103894. ⟨10.1016/j.coastaleng.2021.103894⟩ |
| ISSN: | 0378-3839 |
| Popis: | (IF 5.42; Q1); International audience; Coastal systems are extremely dynamic environments exposed to many hazards, making accurate and regular monitoring a major challenge, particularly in the context of global change and sea level rise. In this frame of reference, high-frequency, high-resolution coastal Video Monitoring Systems (VMS) have been installed on three megatidal (tidal amplitude > 9 m) sites of Normandy (France) including a sandy beach at Villers-sur-Mer, a pebble beach at Etretat and a composite beach at Hautot-sur-Mer. This article proposes the use of Mask R–CNN to process images acquired at these sites and perform the automatic segmentation of the visible bodies of water in order to extract the waterline. The extracted waterlines are associated with a measured water level, which makes it possible to reconstruct the topography of the beaches at the scale of the tidal cycle. After training the neural network on manually labeled data, the segmentation by Mask R–CNN is very efficient by achieving a satisfactory segmentation on 69.87% of the images of Villers-sur-Mer, on 67.11% at Hautot-sur-Mer, and on 97.33% at Etretat. Once the waterlines have been extracted and georeferenced, the reproduction of the beaches’ morphology is satisfactory (averaged vertical RMSE = 28 cm). These results confirm that segmentation by Mask R–CNN is a particularly powerful tool that allows efficient and low-cost monitoring of the evolution of beach morphology, particularly in response to marine conditions. Its capabilities to detect and segment bodies of water while not being affected by the various sources of noise make it a notably effective tool for coastal science applications. |
| Databáze: | OpenAIRE |
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