Classification of underwater photogrammetry data for temperate benthic rocky reef mapping

Autor: Ternon, Quentin, Danet, Valentin, Thiriet, Pierre, Ysnel, Frédéric, Feunteun, Eric, Collin, Antoine
Přispěvatelé: Biologie des Organismes et Ecosystèmes Aquatiques (BOREA), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), Centre De Recherche et d'Enseignement sur les Systèmes Côtiers (CRESCO), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Patrimoine naturel (PatriNat), Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Office français de la biodiversité (OFB), Université de Rennes (UR), 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), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL), European Regional Development Fund, ERDF
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Estuarine, Coastal and Shelf Science
Estuarine, Coastal and Shelf Science, 2022, 270, pp.107833. ⟨10.1016/j.ecss.2022.107833⟩
ISSN: 0272-7714
1096-0015
DOI: 10.1016/j.ecss.2022.107833⟩
Popis: International audience; The fine characterization of the substrate is a baseline to thoroughly investigate the relations between organisms and their biotopes. Cutting edge spatial technologies now provide access to accurate information on biotopes and biocenoses both in terrestrial and in marine environments. Photogrammetry is one of them and has recently been applied in submarine environments especially in shallow clear water. In this study, we investigated the potential of photogrammetry to characterise benthic habitats in turbid environments. Although more challenging, turbid environments are more frequent in temperate marine coastal areas. We selected two rocky sites in the bay of Saint-Malo (Brittany, France), differentiated by their level of turbidity, one being a marine site exposed to natural tides (Buharats), while the other (Bizeux) is subjected to both natural tides and artificial currents created by the functioning of a hydroelectric dam. The different substrates observed were classified into eight classes at a centimetre resolution using photogrammetry-based spatial and multispectral predictors. The spatial benthic terrain predictors were derived from a digital surface model (DSM) at various spatial scales, and the multispectral predictors were retrieved from the red-green-blue (RGB, natural colours) orthomosaic imagery. An overall classification was computed for Buharats and Bizeux, with accuracies of 84.76% and 79.54% respectively, revealing a good quality of the substrate classification. The combination of RGB, DSM, and several spatial benthic terrain variables, with a pixel resolution of 5 and 10 mm, and a kernel size of 30, 60 and 90 pixels leads to the best benthic substrate classification (highest overall accuracy). At the class scale, producer's (PA) and user's (UA) accuracy showed that big boulders and field material were correctly distinguished. Small boulders and cobbles, having similar sizes, showed the lowest classification performances. This classification methodology provides new perspectives for mesoscale (100 m2 to 1 km2) semi-automatic mapping of the fine resolution (1 cm) relationship between benthic organisms and their substrate.
Databáze: OpenAIRE
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