ArtĆ­culo

Relating Biophysical Parameters of Coastal Marshes to Hyperspectral Reflectance Data in the Bahia Blanca Estuary, Argentina

Gonzalez Trilla, Gabriela Liliana Icon; Pratolongo, Paula Daniela Icon; Beget, M. E. ; Kandus, P. ; Marcovecchio, Jorge Eduardo Icon; Di Bella, Carlos Marcelo Icon

Otros responsables

Fecha

01/2013

Editorial

Coastal Education & Research Foundation

Revista

Journal Of Coastal Research

TĆ­tulo del libro

Nombre del evento

Fecha del evento

Institución organizadora

ISSN

0749-0208

eISSN

ISBN

Idioma

InglƩs

Tipo del evento

Resumen

Salt marshes occupying the tidal fringe of estuaries and protected coasts provide valuable ecosystem services, and remote sensing is a powerful tool for their large scale monitoring. However, in order to apply remote sensing techniques to evaluate the ecological state of salt marshes, a deeper understanding is needed on the interactions between field biophysical parameters and the electromagnetic signal. The main objective of this work is to analyze and quantify the influence of different biophysical parameters characterizing stands of Spartina alterniflora marshes in the Bahia Blanca estuary, Argentina on their spectral response. Spectral reflectance at high resolution was measured in S. alterniflora canopies under natural conditions, manipulating standing biomass by means of successive harvestings. Reflectance data were acquired using a FieldSpecĀ® sprectroradiometer (Analytical Spectral Devices, Inc.) in visible, near-infrared and shortwave infrared bands. Spectral indices including the Normalized Difference Vegetation Index (NDVI), were calculated for each biomass situation, leaf area index (LAI), percentage canopy cover (PCC), water content and soil properties were measured. LAI, PCC and biomass were positively correlated between them. As a general trend, as biomass decreased, absorption in red wavelengths increased and reflectance in near infrared decreased. Several indices explained the variability in LAI, biomass and PCC. For example, NDVIRouse had a positive regression with PCC (R2 = 0.80, N = 75) and LAI (R2 = 0.67, N = 75). Results indicate that LAI, biomass and PCC of Spartina alterniflora could be accurately determined from spectral data. 

Aprobación

Revisión

Complementado por

Referenciado por

Licencia Creative Commons

Excepto donde se indique lo contrario, la licencia de este Ć­tem se describe como by-nc-sa