{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T17:19:36Z","timestamp":1775841576402,"version":"3.50.1"},"reference-count":91,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T00:00:00Z","timestamp":1628035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Copernicus Marine Environment and Monitoring Service","award":["77-CMEMS-TAC-OC"],"award-info":[{"award-number":["77-CMEMS-TAC-OC"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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 basin, characterized by large gradients in salinity and dissolved organic matter, are hampered by its optical complexity and atmospheric correction limits. This study presents Chl-a retrieval improvements for a fully reprocessed multi-sensor time series of remote-sensing reflectances (Rrs) at ~1 km spatial resolution for the Baltic Sea. A new ensemble scheme based on multilayer perceptron neural net (MLP) bio-optical algorithms has been implemented to this end. The study documents that this approach outperforms band-ratio algorithms when compared to in situ datasets, reducing the gross overestimates of Chl-a observed in the literature for this basin. The Rrs and Chl-a time series were then exploited for eutrophication monitoring, providing a quantitative description of spring and summer phytoplankton blooms in the Baltic Sea over 1998\u20132019. The analysis of the phytoplankton dynamics enabled the identification of the latitudinal variations in the spring bloom phenology across the basin, the early blooming in spring in the last two decades, and the description of the spatiotemporal coverage of summer cyanobacterial blooms in the central and southern Baltic Sea.<\/jats:p>","DOI":"10.3390\/rs13163071","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T21:45:06Z","timestamp":1628113506000},"page":"3071","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Phytoplankton Bloom Dynamics in the Baltic Sea Using a Consistently Reprocessed Time Series of Multi-Sensor Reflectance and Novel Chlorophyll-a Retrievals"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2193-5695","authenticated-orcid":false,"given":"Vittorio E.","family":"Brando","sequence":"first","affiliation":[{"name":"Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michela","family":"Sammartino","sequence":"additional","affiliation":[{"name":"Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simone","family":"Colella","sequence":"additional","affiliation":[{"name":"Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Bracaglia","sequence":"additional","affiliation":[{"name":"Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Annalisa","family":"Di Cicco","sequence":"additional","affiliation":[{"name":"Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Davide","family":"D\u2019Alimonte","sequence":"additional","affiliation":[{"name":"Aequora, 1600-774 Lisbon, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3148-9705","authenticated-orcid":false,"given":"Tamito","family":"Kajiyama","sequence":"additional","affiliation":[{"name":"Aequora, 1600-774 Lisbon, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seppo","family":"Kaitala","sequence":"additional","affiliation":[{"name":"Finnish Environment Institute (SYKE), 00790 Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jenni","family":"Attila","sequence":"additional","affiliation":[{"name":"Finnish Environment Institute (SYKE), 00790 Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s10533-010-9508-4","article-title":"Getting the Measure of Eutrophication in the Baltic Sea: Towards Improved Assessment Principles and Methods","volume":"106","author":"Andersen","year":"2011","journal-title":"Biogeochemistry"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.ecolind.2014.08.022","article-title":"Recent developments in assessment methodology reveal that the baltic sea eutrophication problem is expanding","volume":"48","author":"Andersen","year":"2015","journal-title":"Ecol. Indic."},{"key":"ref_3","unstructured":"HELCOM (2007). HELCOM Baltic Sea Action Plan, HELCOM."},{"key":"ref_4","unstructured":"HELCOM (2018). State of the Baltic Sea\u2014Second HELCOM Holistic Assessment 2011\u20132016, HELCOM."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"670","DOI":"10.3389\/fmars.2020.00670","article-title":"The globalization of cultural eutrophication in the coastal ocean: Causes and consequences","volume":"7","author":"Malone","year":"2020","journal-title":"Front. Mar. Sci."},{"key":"ref_6","unstructured":"HELCOM (2017). Manual for Marine Monitoring in the COMBINE Programme of HELCOM, HELCOM."},{"key":"ref_7","unstructured":"HELCOM (2019). HELCOM Guidelines for Monitoring of Chlorophyll a, HELCOM."},{"key":"ref_8","unstructured":"Ahlman, M., Alenius, P., Attila, J., Arnkil, A., Arponen, H., Below, A., Blankett, P., B\u00e4ck, A., Cederberg, T., and Forsman, L. (2020). Seurantak\u00e4sikirja Suomen Merenhoitosuunnitelman Seurantaohjelmaan Vuosille 2020\u20132026 (Manual for Marine Monitoring in Finland 2020\u20132026)., Suomen Ymp\u00e4rist\u00f6keskus."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.pocean.2013.12.008","article-title":"A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans","volume":"123","author":"Gower","year":"2014","journal-title":"Prog. Oceanogr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"485","DOI":"10.3389\/fmars.2019.00485","article-title":"Satellite Ocean Colour: Current Status and Future Perspective","volume":"6","author":"Groom","year":"2019","journal-title":"Front. Mar. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.rse.2019.04.021","article-title":"Chlorophyll Algorithms for Ocean Color Sensors\u2014OC4, OC5 & OC6","volume":"229","author":"Werdell","year":"2019","journal-title":"Remote. Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Sathyendranath, S., Brewin, R., Brockmann, C., Brotas, V., Calton, B., Chuprin, A., Cipollini, P., Couto, A., Dingle, J., and Doerffer, R. (2019). An ocean-colour time series for use in climate studies: The experience of the ocean-colour climate change initiative (OC-CCI). Sensors, 19.","DOI":"10.3390\/s19194285"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.rse.2017.04.017","article-title":"Ocean-colour products for climate-change studies: What are their ideal characteristics?","volume":"203","author":"Sathyendranath","year":"2017","journal-title":"Remote. Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"C00H04","DOI":"10.1029\/2011JC007230","article-title":"Are the world\u2019s oceans optically different?","volume":"116","author":"Szeto","year":"2011","journal-title":"J. Geophys. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"127","DOI":"10.5194\/os-15-127-2019","article-title":"Mediterranean Ocean Colour Level 3 Operational Multi-Sensor Processing","volume":"15","author":"Volpe","year":"2019","journal-title":"Ocean Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Heiskanen, A.-S., Bonsdorff, E., and Joas, M. (2019). Baltic Sea: A Recovering Future From Decades of Eutrophication. Coasts and Estuaries, Elsevier.","DOI":"10.1016\/B978-0-12-814003-1.00020-4"},{"key":"ref_17","first-page":"469","article-title":"Satellite detection of increased cyanobacteria blooms in the Baltic Sea: Natural fluctuation or ecosystem change?","volume":"23","author":"Kahru","year":"1994","journal-title":"Ambio"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Lepp\u00e4ranta, M., and Myrberg, K. (2009). Physical Oceanography of the Baltic Sea, Springer.","DOI":"10.1007\/978-3-540-79703-6"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Hjerne, O., Hajdu, S., Larsson, U., Downing, A.S., and Winder, M. (2019). Climate driven changes in timing, composition and magnitude of the Baltic Sea Phytoplankton Spring Bloom. Front. Mar. Sci., 6.","DOI":"10.3389\/fmars.2019.00482"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Simis, S.G.H., Yl\u00f6stalo, P., Kallio, K.Y., Spilling, K., and Kutser, T. (2017). Contrasting seasonality in optical-biogeochemical properties of the Baltic Sea. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0173357"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.scitotenv.2018.06.019","article-title":"MERIS observations of phytoplankton phenology in the Baltic Sea","volume":"642","author":"Zhang","year":"2018","journal-title":"Sci. Total. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1579\/0044-7447-30.4.172","article-title":"The history of cyanobacterial blooms in the Baltic Sea","volume":"30","author":"Finni","year":"2001","journal-title":"Ambio"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"6365","DOI":"10.1038\/s41598-018-24829-7","article-title":"Unexplained interannual oscillations of cyanobacterial blooms in the Baltic Sea","volume":"8","author":"Kahru","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.rse.2012.07.009","article-title":"MERIS Case II Water Processor Comparison on Coastal Sites of the Northern Baltic Sea","volume":"128","author":"Attila","year":"2013","journal-title":"Remote. Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.rse.2003.10.012","article-title":"An Evaluation of MODIS and SeaWiFS Bio-Optical Algorithms in the Baltic Sea","volume":"89","author":"Darecki","year":"2004","journal-title":"Remote. Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.oceano.2016.08.002","article-title":"Testing the performance of empirical remote sensing algorithms in the Baltic Sea waters with modelled and in situ reflectance data","volume":"59","author":"Ligi","year":"2017","journal-title":"Oceanologia"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kratzer, S., and Moore, G. (2018). Inherent optical properties of the Baltic Sea in comparison to other seas and oceans. Remote. Sens., 10.","DOI":"10.3390\/rs10030418"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Berthon, J.-F., and Zibordi, G. (2010). Optically black waters in the Northern Baltic Sea. Geophys. Res. Lett., 37.","DOI":"10.1029\/2010GL043227"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2104","DOI":"10.1016\/j.rse.2011.04.013","article-title":"Cross-Site Consistent in Situ Measurements for Satellite Ocean Color Applications: The BiOMaP Radiometric Dataset","volume":"115","author":"Zibordi","year":"2011","journal-title":"Remote. Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Aavaste, A., Sipelgas, L., Uiboupin, R., and Uudeberg, K. (2021). Impact of thermohaline conditions on vertical variability of optical properties in the Gulf of Finland (Baltic Sea): Implications for water quality remote sensing. Front. Mar. Sci., 8.","DOI":"10.3389\/fmars.2021.674065"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"563","DOI":"10.3389\/fmars.2020.00563","article-title":"Ubiquitous Patchiness in Chlorophyll a Concentration in Coastal Archipelago of Baltic Sea","volume":"7","author":"Scheinin","year":"2020","journal-title":"Front. Mar. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"25657","DOI":"10.1364\/OE.19.025657","article-title":"Assessment of MERIS Reflectance Data as Processed with SeaDAS over the European Seas","volume":"19","author":"Zibordi","year":"2011","journal-title":"Opt. Express"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/j.rse.2017.08.024","article-title":"Radiometric Validation of Atmospheric Correction for MERIS in the Baltic Sea Based on Continuous Observations from Ships and AERONET-OC","volume":"200","author":"Qin","year":"2017","journal-title":"Remote. Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.1109\/LGRS.2018.2849329","article-title":"A Regional Assessment of OLCI Data Products","volume":"15","author":"Zibordi","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"6574","DOI":"10.1109\/TGRS.2016.2587106","article-title":"Ocean color remote sensing of atypical marine optical cases","volume":"54","author":"Kajiyama","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"379","DOI":"10.5194\/os-12-379-2016","article-title":"Remote Sensing of Chlorophyll in the Baltic Sea at Basin Scale from 1997 to 2012 Using Merged Multi-Sensor Data","volume":"12","author":"Pitarch","year":"2016","journal-title":"Ocean Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.rse.2011.11.013","article-title":"Review of constituent retrieval in optically deep and complex waters from satellite imagery","volume":"118","author":"Odermatt","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/j.rse.2012.05.022","article-title":"Performance and Applicability of Bio-Optical Algorithms in Different European Seas","volume":"124","author":"Zibordi","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"211","DOI":"10.5697\/oc.52-2.211","article-title":"Improvement of MERIS Level 2 Products in Baltic Sea Coastal Areas by Applying the Improved Contrast between Ocean and Land Processor (ICOL)\u2014Data Analysis and Validation","volume":"52","author":"Kratzer","year":"2010","journal-title":"Oceanologia"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"(2019). Kyryliuk, Dmytro; Kratzer, Susanne Evaluation of Sentinel-3A OLCI Products Derived Using the Case-2 Regional CoastColour Processor over the Baltic Sea. Sensors, 19.","DOI":"10.3390\/s19163609"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"140","DOI":"10.3389\/fmars.2017.00140","article-title":"The OLCI Neural Network Swarm (ONNS): A Bio-Geo-Optical Algorithm for Open Ocean and Coastal Waters","volume":"4","author":"Hieronymi","year":"2017","journal-title":"Front. Mar. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Toming, K., Kutser, T., Uiboupin, R., Arikas, A., Vahter, K., and Paavel, B. (2017). Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument Imagery in the Baltic Sea. Remote Sens., 9.","DOI":"10.3390\/rs9101070"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"234","DOI":"10.3389\/fmars.2019.00234","article-title":"From Observation to Information and Users: The Copernicus Marine Service Perspective","volume":"6","author":"Reppucci","year":"2019","journal-title":"Front. Mar. Sci."},{"key":"ref_44","first-page":"S1","article-title":"Copernicus Marine Service Ocean State Report, Issue 3","volume":"12","author":"Smith","year":"2019","journal-title":"J. Oper. Oceanogr."},{"key":"ref_45","unstructured":"D\u2019Alimonte, D., Zibordi, G., Berthon, J.-F., Canuti, E., and Kajiyama, T. (2011). Bio-Optical Algorithms for European Seas: Performance and Applicability of Neural-Net Inversion Schemes, Publications Office of the European Union."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1080\/01431160410001720298","article-title":"SeaWiFS Ocean Colour Chlorophyll Algorithms for the Southern Baltic Sea","volume":"26","author":"Darecki","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_47","unstructured":"NASA Ocean Biology Processing Group (2021). Chlorophyll a (Chlor_a) Product Summary."},{"key":"ref_48","unstructured":"NASA Ocean Biology Processing Group (2018). Visible and Infrared Imager\/Radiometer Suite (VIIRS) Ocean Color Data."},{"key":"ref_49","unstructured":"NASA Ocean Biology Processing Group (2018). SEAWIFS-ORBVIEW-2 Level 2 Ocean Color Data Version R2018.0."},{"key":"ref_50","unstructured":"NASA Ocean Biology Processing Group (2018). Moderate-Resolution Imaging Spectroradiometer (MODIS) Aqua Ocean Color Data."},{"key":"ref_51","unstructured":"NASA Ocean Biology Processing Group (2017). VIIRS-SNPP Level 2 Ocean Color Data Version R2018.0."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"9783","DOI":"10.1364\/OE.19.009783","article-title":"Atmospheric Correction in Presence of Sun Glint: Application to MERIS","volume":"19","author":"Steinmetz","year":"2011","journal-title":"Opt. Express"},{"key":"ref_53","unstructured":"Gregg, W.W. (2007). Ocean-Colour Data Merging, IOCCG."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"5755","DOI":"10.1364\/AO.41.005755","article-title":"Deriving Inherent Optical Properties from Water Color: A Multiband Quasi-Analytical Algorithm for Optically Deep Waters","volume":"41","author":"Lee","year":"2002","journal-title":"Appl. Opt."},{"key":"ref_55","unstructured":"Lee, Z., Carder, K.L., and Arnone, R.A. (2014). Update of the Quasi-Analytical Algorithm (QAA_V6), IOCCG."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2262","DOI":"10.1364\/OE.23.002262","article-title":"Band Shifting for Ocean Color Multi-Spectral Reflectance Data","volume":"23","author":"Sclep","year":"2015","journal-title":"Opt. Express"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1016\/j.rse.2013.07.029","article-title":"Comparison between MERIS and Regional High-Level Products in European Seas","volume":"140","author":"Zibordi","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1109\/LGRS.2018.2883539","article-title":"Algorithms Merging for the Determination of Chlorophyll-a Concentration in the Black Sea","volume":"16","author":"Kajiyama","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1162\/neco.1991.3.1.79","article-title":"Adaptive mixtures of local experts","volume":"3","author":"Jacobs","year":"1991","journal-title":"Neural Comput."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.1109\/TNNLS.2012.2200299","article-title":"Twenty Years of Mixture of Experts","volume":"23","author":"Yuksel","year":"2012","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_61","unstructured":"Nabney, I. (2002). NETLAB: Algorithms for Pattern Recognitions, Springer."},{"key":"ref_62","unstructured":"Bishop, C.M. (2005). Neural Networks for Pattern Recognition, Oscar Publications."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"24937","DOI":"10.1029\/98JC02160","article-title":"Ocean Color Chlorophyll Algorithms for SeaWiFS","volume":"103","author":"Maritorena","year":"1998","journal-title":"J. Geophys. Res."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1634","DOI":"10.1175\/2009JTECHO654.1","article-title":"AERONET-OC: A Network for the Validation of Ocean Color Primary Products","volume":"26","author":"Zibordi","year":"2009","journal-title":"J. Atmos. Oceanic Technol."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Zibordi, G., Holben, B.N., Talone, M., D\u2019Alimonte, D., Slutsker, I., Giles, D.M., and Sorokin, M.G. (2020). Advances in the Ocean Color Component of the Aerosol Robotic Network (AERONET-OC). J. Atmos. Ocean. Technol., 1.","DOI":"10.1175\/JTECH-D-20-0085.1"},{"key":"ref_66","unstructured":"(2020, April 10). NASA AERONET Ocean Color, Available online: https:\/\/aeronet.gsfc.nasa.gov\/new_web\/ocean_color.html."},{"key":"ref_67","first-page":"171","article-title":"Solar irradiance reference spectra","volume":"Volume 141","author":"Pap","year":"2004","journal-title":"Geophysical Monograph Series"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s10750-005-1006-7","article-title":"Phytoplankton Spring Bloom Intensity Index for the Baltic Sea Estimated for the Years 1992 to 2004","volume":"554","author":"Fleming","year":"2006","journal-title":"Hydrobiologia"},{"key":"ref_69","first-page":"75","article-title":"Coastal Water Monitoring and Remote Sensing Products Validation Using Ferrybox and Above-Water Radiometric Measurements","volume":"7","author":"Kaitala","year":"2008","journal-title":"EARSeL eProceedings"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/0278-4343(90)90055-Q","article-title":"The Phytoplankton Spring Bloom in the Baltic Sea in 1985, 1986: Multitude of Spatio-Temporal Scales","volume":"10","author":"Kahru","year":"1990","journal-title":"Cont. Shelf Res."},{"key":"ref_71","first-page":"s21","article-title":"Phytoplankton blooms in the Baltic Sea. In Copernicus Marine Service Ocean State Report","volume":"12","author":"Smith","year":"2019","journal-title":"J. Oper. Oceanogr."},{"key":"ref_72","first-page":"s110","article-title":"Eutrophication and hypoxia in the Baltic Sea. In Copernicus Marine Service Ocean State Report","volume":"11","author":"Smith","year":"2018","journal-title":"J. Oper. Oceanogr."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"4959","DOI":"10.5194\/bg-13-4959-2016","article-title":"Spring Blooms in the Baltic Sea Have Weakened but Lengthened from 2000 to 2014","volume":"13","author":"Groetsch","year":"2016","journal-title":"Biogeosciences"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1126\/science.1069174","article-title":"The North Atlantic Spring Phytoplankton Bloom and Sverdrup\u2019s Critical Depth Hypothesis","volume":"296","author":"Siegel","year":"2002","journal-title":"Science"},{"key":"ref_75","unstructured":"HELCOM (2020, April 10). HELCOM Subbasins with Coastal and Offshore Division 2018 (ID: 4). Available online: https:\/\/maps.helcom.fi\/arcgis\/rest\/services\/MADS\/Sea_environmental_monitoring\/MapServer\/4."},{"key":"ref_76","unstructured":"Hansson, M., Pamberton, P., H\u00e5kansson, B., Reinart, A., and Alikas, K. (July, January 28). Operational Nowcasting of Algal Blooms in the Baltic Sea Using MERIS and MODIS. Proceedings of the ESA Living Planet Symposium, Bergen, Norway."},{"key":"ref_77","unstructured":"\u00d6berg, J. (2018). Cyanobacterial Blooms in the Baltic Sea. HELCOM Baltic Sea Environment Fact Sheet 2017, HELCOM."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"15","DOI":"10.3354\/meps06943","article-title":"Satellite measurements of cyanobacterial bloom frequency in the Baltic Sea: Interannual and spatial variability","volume":"343","author":"Kahru","year":"2007","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"2179","DOI":"10.4319\/lo.2004.49.6.2179","article-title":"Quantitative Detection of Chlorophyll in Cyanobacterial Blooms by Satellite Remote Sensing","volume":"49","author":"Kutser","year":"2004","journal-title":"Limnol. Oceanogr."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.ecss.2005.11.024","article-title":"Monitoring Cyanobacterial Blooms by Satellite Remote Sensing","volume":"67","author":"Kutser","year":"2006","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.rse.2006.02.013","article-title":"Comparison of Different Satellite Sensors in Detecting Cyanobacterial Bloom Events in the Baltic Sea","volume":"102","author":"Reinart","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"011507","DOI":"10.1117\/1.2834769","article-title":"The Baltic Algae Watch System\u2014A remote sensing application for monitoring cyanobacterial blooms in the Baltic Sea","volume":"1","author":"Hansson","year":"2007","journal-title":"J. Appl. Remote Sens"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.5194\/essd-11-1037-2019","article-title":"A Compilation of Global Bio-Optical in Situ Data for Ocean-Colour Satellite Applications\u2014Version Two","volume":"11","author":"Valente","year":"2019","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"481","DOI":"10.5194\/essd-13-481-2021","article-title":"Global Maps of Forel\u2013Ule Index, Hue Angle and Secchi Disk Depth Derived from 21 Years of Monthly ESA Ocean Colour Climate Change Initiative Data","volume":"13","author":"Pitarch","year":"2021","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"3619","DOI":"10.5194\/bg-11-3619-2014","article-title":"Multidecadal Time Series of Satellite-Detected Accumulations of Cyanobacteria in the Baltic Sea","volume":"11","author":"Kahru","year":"2014","journal-title":"Biogeosciences"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"101739","DOI":"10.1016\/j.hal.2019.101739","article-title":"Cyanobacterial Blooms in the Baltic Sea: Correlations with environmental factors","volume":"92","author":"Kahru","year":"2020","journal-title":"Harmful Algae"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"7740","DOI":"10.1002\/2015GL064901","article-title":"Atmospheric and Oceanic Conditions and the Extremely Low Bothnian Bay Sea Ice Extent in 2014\/2015","volume":"42","author":"Uotila","year":"2015","journal-title":"Geophys. Res. Lett."},{"key":"ref_88","first-page":"145","article-title":"A novel earth observation based ecological indicator for cyanobacterial blooms","volume":"64","author":"Anttila","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_89","unstructured":"Hansson, M. (2005). HELCOM Baltic Sea Environment Fact Sheet 2005. Cyanobacterial Blooms in the Baltic Sea, HELCOM."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.rse.2013.11.021","article-title":"An Optical Water Type Framework for Selecting and Blending Retrievals from Bio-Optical Algorithms in Lakes and Coastal Waters","volume":"143","author":"Moore","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"2424","DOI":"10.1016\/j.rse.2009.07.016","article-title":"A Class-Based Approach to Characterizing and Mapping the Uncertainty of the MODIS Ocean Chlorophyll Product","volume":"113","author":"Moore","year":"2009","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3071\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:40:42Z","timestamp":1760164842000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3071"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,4]]},"references-count":91,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["rs13163071"],"URL":"https:\/\/doi.org\/10.3390\/rs13163071","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,4]]}}}