Repositorio Institucional
Repositorio Institucional
CONICET Digital
  • Inicio
  • EXPLORAR
    • AUTORES
    • DISCIPLINAS
    • COMUNIDADES
  • Estadísticas
  • Novedades
    • Noticias
    • Boletines
  • Ayuda
    • General
    • Datos de investigación
  • Acerca de
    • CONICET Digital
    • Equipo
    • Red Federal
  • Contacto
JavaScript is disabled for your browser. Some features of this site may not work without it.
  • INFORMACIÓN GENERAL
  • RESUMEN
  • ESTADISTICAS
 
Artículo

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, Olga MagalíIcon ; Raffo, María PaulaIcon ; Rodríguez Pérez, Daniel; Arijón, MarianelaIcon ; Sanchez Carnero, Noela BelenIcon
Fecha de publicación: 12/2020
Editorial: MDPI AG
Revista: Remote Sensing
ISSN: 2072-4292
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Biología Marina, Limnología; Ciencias de las Plantas, Botánica; Oceanografía, Hidrología, Recursos Hídricos

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.
Palabras clave: COASTAL MACROALGAE , HYPERSPECTRAL SENSORS , SPECTRAL FEATURES
Ver el registro completo
 
Archivos asociados
Thumbnail
 
Tamaño: 8.216Mb
Formato: PDF
.
Descargar
Licencia
info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution 2.5 Unported (CC BY 2.5)
Identificadores
URI: http://hdl.handle.net/11336/153187
URL: https://www.mdpi.com/2072-4292/12/23/3870
DOI: http://dx.doi.org/10.3390/rs12233870
Colecciones
Articulos(CESIMAR)
Articulos de CENTRO PARA EL ESTUDIO DE SISTEMAS MARINOS
Citación
Olmedo 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
Compartir
Altmétricas
 

Enviar por e-mail
Separar cada destinatario (hasta 5) con punto y coma.
  • Facebook
  • X Conicet Digital
  • Instagram
  • YouTube
  • Sound Cloud
  • LinkedIn

Los contenidos del CONICET están licenciados bajo Creative Commons Reconocimiento 2.5 Argentina License

https://www.conicet.gov.ar/ - CONICET

Inicio

Explorar

  • Autores
  • Disciplinas
  • Comunidades

Estadísticas

Novedades

  • Noticias
  • Boletines

Ayuda

Acerca de

  • CONICET Digital
  • Equipo
  • Red Federal

Contacto

Godoy Cruz 2290 (C1425FQB) CABA – República Argentina – Tel: +5411 4899-5400 repositorio@conicet.gov.ar
TÉRMINOS Y CONDICIONES