Scientia Marina, Vol 83, No 1 (2019)

An empirical remote sensing algorithm for retrieving total suspended matter in a large estuarine region


https://doi.org/10.3989/scimar.04847.22A

Martina D. Camiolo
Universidad Provincial del Sudoeste (UPSO) - Subprograma de Sensoramiento Remoto, Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina
orcid http://orcid.org/0000-0002-3754-869X

Ezequiel Cozzolino
Subprograma de Sensoramiento Remoto, Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP), Argentina
orcid http://orcid.org/0000-0003-3693-3702

Ana I. Dogliotti
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) - Instituto de Astronomía y Física del Espacio (IAFE), CONICET, Universidad de Buenos Aires - Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (UMI/IFAECI/CNRS/CONICET/UBA), Argentina
orcid http://orcid.org/0000-0001-8834-4374

Claudia G. Simionato
Centro de Investigaciones del Mar y la Atmósfera (CIMA/CONICET/UBA) - Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (UMI/IFAECI/CNRS/CONICET/UBA) - Departamento de Ciencias de la Atmósfera y los Océanos, FCEN, Universidad de Buenos Aires, Argentina
orcid http://orcid.org/0000-0002-6108-037X

Carlos A. Lasta
Subprograma de Sensoramiento Remoto, Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP), Argentina
orcid http://orcid.org/0000-0002-7154-7084

Abstract


The Río de la Plata is a large, shallow estuary located at approximately 35°S and flowing into the southwestern Atlantic Ocean. It carries a high amount of nutrients and suspended particulate matter, both organic and inorganic, to the adjacent shelf waters and is considered among the most turbid estuarine systems in the world. Knowledge of the concentration and spatial and temporal variability of these materials is critical for any biological study in the Río de la Plata. In this work, the relationship between suspended particulate matter and turbidity is empirically established in order to derive suspended particulate matter maps from satellite data (MODIS-Aqua) for the Río de la Plata region. A strong correlation between suspended particulate matter and turbidity was found (Pearson correlation coefficient =0.91) and the linear regression (slope =0.76 and intercepts =12.78, R2=0.83) explained 83% of the variance. The validation of the empirical algorithm, using co-located and coincident satellite and in situ measurements, showed good results with a low mean absolute error (14.60%) and a small and positive bias (3.04%), indicating that the estimated suspended particulate matter values tend to slightly overestimate the field values.

Keywords


empirical algorithm; suspended particulate matter; Río de la Plata; in situ measurements; MODIS-Aqua satellite image

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