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The aim of this study was to test and develop the indicators for the remote sensing assessment of cyanobacterial blooms as an input to the estimation of eutrophication and the environmental status (ES) under the Marine Strategy Framework Directive (MSFD) in the optically varying Estonian coastal regions (the Baltic Sea). Here, the assessment of cyanobacteria blooms considered the chlorophyll-a (chl-a), turbidity, and biomass of N2-fixing cyanobacteria. The Sentinel-3 A/B Ocean and Land Colour Instrument (OLCI) data and Case-2 Regional CoastColour (C2RCC) processor were used for chl-a and turbidity detection. The ES was assessed using four methods: the Phytoplankton Intensity Index (PII), the Cyanobacterial Surface Accumulations Index (CSA), and two variants of the Cyanobacterial Bloom Indicator (CyaBI) either with in situ-measured cyanobacterial biomass or with satellite-estimated cyanobacterial biomass. The threshold values for each coastal area ES assessment are presented. During 2022, the NW Gulf of Riga reached good ES, but most of the 16 coastal areas failed to achieve good ES according to one or multiple indices. Overall, the CyaBI gives the most comprehensive assessment of cyanobacteria blooms, with the CyaBI (in situ) being the best suited for naturally turbid areas. The CyaBI (satellite) could be more useful than in situ in large open areas, where the coverage of in situ sampling is insufficient.

Nutrients are important elements in marine ecosystems and water quality, and have a major role in the eutrophication of water bodies. Monitoring nutrient loads is especially important for the Baltic Sea, which is especially sensitive to the eutrophication. Using optical remote sensing data in mapping total nitrogen (TN) and total phosphorus (TP) is challenging because these substances do not have a direct influence on the water optics that remote sensing sensors can detect. On the other hand, it would be very rewarding. In this study, more than 25,000 Sentinel-3 Ocean and Land Colour Instrument (OLCI) data algorithms were tested in order to detect the TN and TP concentrations in the Estonian marine waters between 2016–2021. The TN estimations were well derived for Estonian marine waters (R2 = 0.73, RMSE = 4.87 µmolN L−1, MAPE = 14%, n = 708), while the TP estimations were weaker (R2 = 0.38, RMSE = 0.23 µmolP L−1, MAPE = 24%, n = 730). The Estonian marine waters were divided into six geographic regions in order to study the effect of regional water quality on the TN and TP retrievals. The nutrient concentrations were derived in every region when spring and summer periods were treated separately. In this study, the detection of both nutrients was more successful in more closed areas with P deficiency, while in open sea areas it was more challenging. This study shows that it is possible to estimate nutrients, especially TN, from remote sensing data. Consequently, remote sensing could provide a reliable support to the conventional monitoring by covering large marine areas with high temporal and spatial resolution data.