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Advisor(s)
Abstract(s)
Chlorophyll a concentration (Chl) product validation off theWestern Iberian coast is here undertaken by directly
comparing remote sensing data with in situ surface reference values. Both standard and recently developed
alternative algorithms are considered for match-up data analysis. The investigated standard products are those
produced by the MERIS (algal 1 and algal 2) and MODIS (OC3M) algorithms. The alternative data products include
those generatedwithin the CoastColour Project and Ocean Color Climate Change Initiative (OC-CCI) funded
by ESA, as well as a neural net model trained with field measurements collected in the Atlantic off Portugal
(MLPATLP). Statistical analyses showed that satellite Chl estimates tend to be larger than in situ reference values.
The study also revealed that a non-uniform Chl distribution in the water column can be a concurring factor to the
documented overestimation tendency when considering larger optical depth match-up stations. Among standard
remote sensing products, MODIS OC3M and MERIS algal 2 yield the best agreement with in situ data. The
performance of MLPATLP highlights the capability of regional solutions to further improve Chl retrieval by accounting
for environmental specificities. Results also demonstrate the relevance of oceanographic regions such
as the Nazaré area to evaluate how complex hydrodynamic conditions can influence the quality of Chl products.
Description
Keywords
Chlorophyll a Ocean color remote sensing MERIS and MODIS sensors Validation
Citation
Publisher
Elsevier