| Summary: | Since the 90’s, the Pacific oyster Crassostrea gigas, is considered as an invasive species because of their negative environmental impacts. However, oyster producers are reconsidering wild oyster populations as a resource due to recent high mortalities affecting cultivated oysters since the summer 2008. The social conflicts existing around natural oyster beds require spatial distribution maps for management purposes. The objective of this work is to evaluate the ability of visible and near infrared remote sensing to identify wild oyster reefs using various spectral, spatial and temporal resolutions. Firstly, maps obtained with an airborne campaign at a shellfish ecosystem scale, showed the importance of hyperspectral data, to identify oysters according to the reef structure. Spectral reflectance shapes surprisingly revealed the existence of chlorophyll absorption bands, suggesting the presence of a visually invisible microalgal biofilm colonizing the shell surface. At microscale, oyster shells were imaged using a hyperspectral HySpex camera in the laboratory with a sub-millimeter spatial resolution. The second derivative peaks at 462, 524, 571 and 647 nm were related to the presence of diatoms, cyanobacteria, rhodophytes and chlorophytes. Further pigment analysis by high performance liquid chromatography (HPLC) and microscopic observations confirmed the presence of these epilithic and endolithic biofilms. Finally, despite the high hyperspectral resolution, misclassification of oyster reefs occurred in muddy areas due to spectral mixing with mud and microphytobenthos. This could be overcome by combining optical data with radar images, sensitive to the surface roughness. L’huître creuse Crassostrea gigas, est considérée depuis les années 90 comme une espèce invasive à cause de son impact sur l’environnement. Cependant, suite aux surmortalités qui touchent les huîtres en élevage depuis l’été 2008, les huîtres sauvages sont considérées comme une réelle ressource. Cela nécessite la production de cartes pour ...
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