remote sensing Article Phytoplankton Bloom Dynamics in the Baltic Sea Using a Consistently Reprocessed Time Series of Multi-Sensor Reflectance and Novel Chlorophyll-a Retrievals Vittorio E. Brando 1,* , Michela Sammartino 1, Simone Colella 1, Marco Bracaglia 1, Annalisa Di Cicco 1, Davide D’Alimonte 2, Tamito Kajiyama 2 , Seppo Kaitala 3 and Jenni Attila 3 1 Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, Italy;
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[email protected] (A.D.C.) 2 Aequora, 1600-774 Lisbon, Portugal;
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[email protected] (T.K.) 3 Finnish Environment Institute (SYKE), 00790 Helsinki, Finland; seppo.kaitala@ymparisto.fi (S.K.); Jenni.Attila@ymparisto.fi (J.A.) * Correspondence:
[email protected] Abstract: A relevant indicator for the eutrophication status in the Baltic Sea is the Chlorophyll-a concentration (Chl-a). Alas, ocean color remote sensing applications to estimate Chl-a in this brackish Citation: Brando, V.E.; Sammartino, basin, characterized by large gradients in salinity and dissolved organic matter, are hampered M.; Colella, S.; Bracaglia, M.; Di Cicco, by its optical complexity and atmospheric correction limits. This study presents Chl-a retrieval A.; D’Alimonte, D.; Kajiyama, T.; improvements for a fully reprocessed multi-sensor time series of remote-sensing reflectances (R ) at Kaitala, S.; Attila, J. Phytoplankton rs Bloom Dynamics in the Baltic Sea ~1 km spatial resolution for the Baltic Sea. A new ensemble scheme based on multilayer perceptron Using a Consistently Reprocessed neural net (MLP) bio-optical algorithms has been implemented to this end.