How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)

OLMEDO-MASAT, O. MAGALÍ; RAFFO, M. PAULA; RODRÍGUEZ-PÉREZ, DANIEL; ARIJÓN, MARIANELA; SÁNCHEZ-CARNERO, NOELA

Remote Sensing

MDPI

Lugar: Basel; Año: 2020 vol. 12

Macroalgae have attracted the interest of remote sensing as targets to study coastal marineecosystems because of their key ecological role. The goal of this paper is to analyze a new spectrallibrary, including 28 macroalgae from the South-West Atlantic coast, in order to assess its use inhyperspectral remote sensing. The library includes species collected in the Atlantic Patagonian coast(Argentina) with representatives of brown, red, and green algae, being 22 of the species includedin a spectral library for the first time. The spectra of these main groups are described, and theintraspecific variability is also assessed, considering kelp differentiated tissues and depth range,discussing them from the point of view of their effects on spectral features. A classification and anindependent component analysis using the spectral range and simulated bands of two state-of-the-artdrone-borne hyperspectral sensors were performed. The results show spectral features and clustersidentifying further algae taxonomic groups, showing the potential applications of this spectral libraryfor drone-based mapping of this ecological and economical asset of our coastal marine ecosystems.