dc.creatorOlmedo Masat, Olga Magalí
dc.creatorRaffo, María Paula
dc.creatorRodríguez Pérez, Daniel
dc.creatorArijón, Marianela
dc.creatorSanchez Carnero, Noela Belen
dc.date.accessioned2022-03-10T17:21:29Z
dc.date.accessioned2022-10-15T16:50:08Z
dc.date.available2022-03-10T17:21:29Z
dc.date.available2022-10-15T16:50:08Z
dc.date.created2022-03-10T17:21:29Z
dc.date.issued2020-12
dc.identifierOlmedo Masat, Olga Magalí; Raffo, María Paula; Rodríguez Pérez, Daniel; Arijón, Marianela; Sanchez Carnero, Noela Belen; How far can we classify macroalgae remotely? An example using a new spectral library of species from the south west atlantic (argentine patagonia); MDPI AG; Remote Sensing; 12; 23; 12-2020; 1-33
dc.identifier2072-4292
dc.identifierhttp://hdl.handle.net/11336/153187
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4411516
dc.description.abstractMacroalgae 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.
dc.languageeng
dc.publisherMDPI AG
dc.relationinfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2072-4292/12/23/3870
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3390/rs12233870
dc.rightshttps://creativecommons.org/licenses/by/2.5/ar/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectCOASTAL MACROALGAE
dc.subjectHYPERSPECTRAL SENSORS
dc.subjectSPECTRAL FEATURES
dc.titleHow far can we classify macroalgae remotely? An example using a new spectral library of species from the south west atlantic (argentine patagonia)
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/publishedVersion


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