6533b855fe1ef96bd12b0898

RESEARCH PRODUCT

Discrimination of coral reflectance spectra in the Red Sea

Manuel MarchiorettiJean JaubertJohn R. M. ChisholmAudrey Minghelli-roman

subject

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciences[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCoral0211 other engineering and technologies02 engineering and technologyAquatic Science01 natural sciencesSpectral line[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing14. Life underwaterComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinggeographygeography.geographical_feature_categoryfungiPigment compositionCoral reefReflectivityWavelengthSpectroradiometerBenthic zone[SDE]Environmental SciencesEnvironmental science[SDE.BE]Environmental Sciences/Biodiversity and Ecology

description

Benthic populations can potentially be mapped from remotely acquired spectral imagery, provided that they have distinctive reflectance signatures. We examined the spectral reflectance characteristics of 14 genera of Red Sea coral using a submersible spectroradiometer. Coral spectra varied quantitatively and qualitatively over the depth interval 5–20 m. Tissue pigment content had a larger effect on reflectance than colony morphology. Ten coral genera could be discriminated with a statistical probability of 52% on the basis of their absolute reflectance. Six groups of two to three coral genera could be discriminated with a probability of 60% on the basis of their rates of change in reflectance at specific wavelengths. All coral genera could be discriminated with a minimum probability of 59% on the basis of their proportionate reflectance at one wavelength as compared with another. Ratio analysis holds significant potential for interpretation of remotely sensed imagery because measurement of reflectance at six wavelengths generates 15 different parameters that can be used to identify and discriminate the component classes. The method distinguishes spectra on the basis of their shape rather than their amplitude, which helps to factor out light-induced variation in pigment concentration, exposing taxon-specific differences in pigment composition and morphology.

10.1007/s00338-002-0249-2https://hal.archives-ouvertes.fr/hal-01859118