7 April 2016 Assessment of remotely sensed chlorophyll-a concentration in Guanabara Bay, Brazil
Eduardo N. Oliveira, Alexandre M. Fernandes, Milton Kampel, Renato C. Cordeiro, Nilva Brandini, Susana B. Vinzon, Renata M. Grassi, Fernando N. Pinto, Alessandro M. Fillipo, Rodolfo Paranhos
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Abstract
The Guanabara Bay (GB) is an estuarine system in the metropolitan region of Rio de Janeiro (Brazil), with a surface area of ∼346  km2 threatened by anthropogenic pressure. Remote sensing can provide frequent data for studies and monitoring of water quality parameters, such as chlorophyll-a concentration (Chl-a). Different combination of Medium Resolution Imaging Spectrometer (MERIS) remote sensing reflectance band ratios were used to estimate Chl-a. Standard algorithms such as Ocean Color 3-band, Ocean Color-4 band, fluorescence line height, and maximum chlorophyll index were also tested. The MERIS Chl-a estimates were statistically compared with a dataset of in situ Chl-a (2002 to 2012). Good correlations were obtained with the use of green, red, and near-infrared bands. The best performing algorithm was based on the red (665 nm) and green (560 nm) band ratio, named “RG3” algorithm (r2=0.71, chl-a=62,565 * x1.6118). The RG3 was applied to a time series of MERIS images (2003- to 2012). The GB has a high temporal and spatial variability of Chl-a, with highest values found in the wet season (October to March) and in some of the most internal regions of the estuary. Lowest concentrations are found in the central circulation channel due to the flushing of ocean water masses promoted by pumping tide.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2016/$25.00 © 2016 SPIE
Eduardo N. Oliveira, Alexandre M. Fernandes, Milton Kampel, Renato C. Cordeiro, Nilva Brandini, Susana B. Vinzon, Renata M. Grassi, Fernando N. Pinto, Alessandro M. Fillipo, and Rodolfo Paranhos "Assessment of remotely sensed chlorophyll-a concentration in Guanabara Bay, Brazil," Journal of Applied Remote Sensing 10(2), 026003 (7 April 2016). https://doi.org/10.1117/1.JRS.10.026003
Published: 7 April 2016
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Cited by 23 scholarly publications.
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KEYWORDS
Magnesium

In situ remote sensing

Remote sensing

Absorption

Reflectivity

Luminescence

Atmospheric corrections

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