## 5 Conclusions  
Cyanobacterial blooms are a nuisance to ecosystems, aquaculture, and public health. Thus, monitoring bloom parameters is of importance to society at large. Under the MSFD, European waters, including the Baltic Sea, must reach and maintain GES. Using satellite remote sensing for monitoring purposes could be a useful way to fill any gaps in the data and supplement the monitoring process. The impacts of climate change on the cyanobacteria communities will vary geographically and no single solution is applicable to all [84; 88; 89]. Here, we show four different approaches to assessing the ES of Estonian coastal areas based on satellite-derived chl-a, turbidity, and cyanobacterial biomass estimates. Satellite data allow for spatial and temporal resolution which in situ measurements cannot match. However, in situ sampling provides the necessary validation and can be useful for tuning the algorithms and developing new RS-based methods. Different approaches to assessing coastal areas are recommended as the areas differ from each other regarding chl-a, turbidity, and N\({}_{2}\)-fixing cyanobacteria biomass. However, overall, the CyaBI gives the most comprehensive assessment of cyanobacteria blooms, with the satellite-derived CyaBI being better suited in large areas which would be difficult to accurately cover with in situ sampling and which are less impacted by CDOM and TSM. The CSA index could be useful in Haapsalu Bay in the absence of in situ cyanobacteria biomass data, where a peak in chl-a is followed by a slight increase in turbidity. We have presented threshold values for all 16 coastal areas and four indices to be used in assessments. As new data emerge, threshold values can be updated to reflect the environmental status better. Comparing the 2022 index results to the threshold values, it was found that most coastal areas failed to achieve GES under one or multiple indices. The NW Gulf of Riga was the only area where GES was achieved according to all four indices. Five areas, mostly closed bays, did not achieve GES under any of the four indices. We have also discussed the current limitations and inaccuracies associated with using satellite data in Case-2 coastal waters. Research into improving the current processors needs to be undertaken, especially in complex areaswhich are heavily influenced by various environmental parameters. Assessing bloom parameters with satellite data could complement in situ monitoring practices with the provision of a more frequent and spatially expansive overview. Conceptualization, I.-A.R., K.K. and K.A. ; Methodology, I.-A.R., K.K. and K.A. ; Resources, K.K., K.A. and A.J. ; Validation, I.-A.R., K.K. and K.A. ; Formal analysis, I.-A.R. ; Investigation, I.-A.R., Data curation, I.-A.R., K.K., K.A. and A.J. ; Writing--original draft preparation, I.-A.R. ; Writing--review and editing, K.K., K.A. and A.J. ; Supervision, K.K. and K.A. ; Visualization, I.-A.R. ; Project administration, K.K. and K.A. ; Funding acquisition, K.K. and K.A. All authors have read and agreed to the published version of the manuscript. This research was funded by the Estonian Environmental Agency, under the project \"Further development of evaluation indicators of criterion D5C3 in accordance with the EU Marine Strategy Framework Directive (2008/56/EC) for specifying assessments of the state of the Estonian coastal area\", and by the European Commission project No. FPA 275/G/GRO/COPE/17/10042, FPCUP (Framework Partnership Agreement on Copernicus User Uptake) action 2020-3-24 (Open Data Framework in the Baltic Sea Catchment Area). Data Availability Statement: Data are available upon request, [link KESE]. We thank the ESA for the availability of the Sentinel 3/OLCI data, the Estonian Marine Institute for the in situ monitoring data, the Estonian Environmental Agency for the temperature data, and the Estonian Land Board for the availability of the processing environment ESTHub. We would also like to thank the three anonymous reviewers for their comments and ideas for improving the article.