Spectral characteristics of coralline algae: a multi-instrumental approach, with emphasis on underwater hyperspectral imaging

Abstract

Coralline algae constitute a cosmopolitan group of calcifying rhodophytes (red algae) that display characteristic optical fingerprints due to light absorption by specific light-harvesting pigments. The spectrally conspicuous nature of coralline algae makes them potential candidates for optical remote sensing surveys. Recently, underwater hyperspectral imaging (UHI), which we believe is a novel optical remote sensing technique, also has become the subject of marine research. The aim of the study was to characterize the spectral properties of different coralline algal species and to assess the potential of UHI as a coralline algal identification and mapping tool. Four species of coralline algae were investigated: Corallina officinalis, Lithothamnion glaciale, Phymatolithon lenormandii, and Phymatolithon tenue. Important coralline algal pigments were identified using spectrophotometry and high-performance liquid chromatography (HPLC). Reflectance spectra of all species were obtained using both a spectrometer and UHI. Multivariate statistical analyses were performed on the reflectance data to identify spectral differences between the species and the instruments. Supervised classification of coralline algae in UHI transects recorded both in vivo and in situ was also carried out. R-phycoerythrin and chlorophyll a were found to be the most dominant coralline algal pigments. The analyzed species of coralline algae displayed highly similar reflectance spectra, and dips in reflectance corresponding to the absorbance peaks of R-phycoerythrin and chlorophyll a were identified in all spectra. Wavelengths corresponding to R-phycoerythrin light absorbance were the greatest contributors to interspecific spectral differences, but the investigated coralline algal species could not be spectrally distinguished with great accuracy. Optical signatures recorded using different instruments were comparable, but inter-instrumental spectral differences were found to be greater than interspecific differences. Supervised UHI classification was unable to accurately map different coralline algal species due to the similarity of the optical fingerprints; however, as a group, coralline algae could easily be identified. In the future, large-scale UHI surveys of coralline algal habitats should be carried out using platforms such as remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs) to enhance our understanding of this widespread and ecologically important organism group.