Cargando...
Fecha
2020-11-26
Derechos de acceso
info:eu-repo/semantics/openAccess
Título de la revista
ISSN de la revista
Título del volumen
Editorial
MDPI
Citas
Resumen
Macroalgae have attracted the interest of remote sensing as targets to study coastal marine ecosystems because of their key ecological role. The goal of this paper is to analyze a new spectral library, including 28 macroalgae from the South-West Atlantic coast, in order to assess its use in hyperspectral 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 included in a spectral library for the first time. The spectra of these main groups are described, and the intraspecific 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 an independent component analysis using the spectral range and simulated bands of two state-of-the-art drone-borne hyperspectral sensors were performed. The results show spectral features and clusters identifying further algae taxonomic groups, showing the potential applications of this spectral library for drone-based mapping of this ecological and economical asset of our coastal marine ecosystems.
Descripción
The registered version of this article, first published in “Remote Sensing, 12(23), (2020), 3870", is available online at the publisher's website: MDPI, https://doi.org/10.3390/rs12233870
La versión registrada de este artículo, publicado por primera vez en “Remote Sensing, 12(23), (2020), 3870", está disponible en línea en el sitio web del editor: MDPI, https://doi.org/10.3390/rs12233870
La versión registrada de este artículo, publicado por primera vez en “Remote Sensing, 12(23), (2020), 3870", está disponible en línea en el sitio web del editor: MDPI, https://doi.org/10.3390/rs12233870
Categorías UNESCO
Palabras clave
Coastal macroalgae, Spectral features, Hyperspectral sensors
Citación
Olmedo Masat, O. M., Raffo. M. P., Rodríguez Pérez, D., Arijón, M. y Sánchez Carnero, N., (2020). “How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)”. Remote Sensing, 12(23), 3870; DOI:10.3390/rs12233870
Centro
Facultad de Ciencias
Departamento
Física Matemática y de Fluídos
Grupo de investigación
Física Médica