{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:46:58Z","timestamp":1772909218003,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2016,3,5]],"date-time":"2016-03-05T00:00:00Z","timestamp":1457136000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Union","doi-asserted-by":"publisher","award":["POIG.01.01.02\u221222\u2212011\/09"],"award-info":[{"award-number":["POIG.01.01.02\u221222\u2212011\/09"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"name":"IO UG","award":["DS\/530\u2212G210\u2212D425\u221214\u22121C"],"award-info":[{"award-number":["DS\/530\u2212G210\u2212D425\u221214\u22121C"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Commonly used parameters to assess cyanobacteria blooms are chlorophyll a concentration and cyanobacterial cell counts. Chlorophyll a is contained in all phytoplankton groups and therefore it is not a good estimator when only detection of cyanobacteria is desired. Moreover, laboratory determination of cyanobacterial cell counts is difficult and it requires a well-trained specialist. Instead of that, cyanobacterial blooms can be assessed using phycocyanin, a marker pigment for cyanobacteria, which shows a strong correlation with the biomass of cyanobacteria. The objective of this research is to develop a simple, remote sensing reflectance-based spectral band ratio model for the estimation of phycocyanin concentration, optimized for the waters of the Baltic Sea. The study was performed using hyperspectral remote sensing reflectance data and reference pigment concentration obtained in the optically complex coastal waters of the Baltic Sea, where cyanobacteria bloom occur regularly every summer, often causing severe damages. The presented two-band model shows good estimation results, with root-mean-square error (RMSE) 0.26 and determination coefficient (R2) 0.73. Moreover, no correlation with chlorophyll a concentration is observed, which makes it accurate in predicting cyanobacterial abundance in the presence of other chlorophyll-containing phytoplankton groups as well as for the waters with high colored dissolved organic matter (CDOM) concentration. The developed model was also adapted to spectral bands of the recently launched Sentinel-3 Ocean and Land Color Imager (OLCI) radiometer, and the estimation accuracy was comparable (RMSE = 0.28 and R2 = 0.69). The presented model allows frequent, large-scale monitoring of cyanobacteria biomass and it can be an effective tool for the monitoring and management of coastal regions.<\/jats:p>","DOI":"10.3390\/rs8030212","type":"journal-article","created":{"date-parts":[[2016,3,7]],"date-time":"2016-03-07T10:25:00Z","timestamp":1457346300000},"page":"212","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":56,"title":["Empirical Model for Phycocyanin Concentration Estimation as an Indicator of Cyanobacterial Bloom in the Optically Complex Coastal Waters of the Baltic Sea"],"prefix":"10.3390","volume":"8","author":[{"given":"Monika","family":"Wo\u017aniak","sequence":"first","affiliation":[{"name":"Institute of Oceanography, University of Gdansk, Al. Pilsudskiego 46, 81\u2212378 Gdynia, Poland"},{"name":"Department of Earth and Space Sciences, Chalmers University of Technology, 412 96 Gothenburg, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katarzyna","family":"Bradtke","sequence":"additional","affiliation":[{"name":"Institute of Oceanography, University of Gdansk, Al. Pilsudskiego 46, 81\u2212378 Gdynia, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miroslaw","family":"Darecki","sequence":"additional","affiliation":[{"name":"Institute of Oceanology Polish Academy of Sciences, Powstancow Warszawy 55, 81\u2013712 Sopot, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7930-3009","authenticated-orcid":false,"given":"Adam","family":"Kr\u0119\u017cel","sequence":"additional","affiliation":[{"name":"Institute of Oceanography, University of Gdansk, Al. Pilsudskiego 46, 81\u2212378 Gdynia, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,3,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"36","DOI":"10.2478\/v10102-009-0006-2","article-title":"Toxins produced in cyanobacterial water blooms-toxicity and risks","volume":"2","author":"Blaha","year":"2009","journal-title":"Interdiscip. Toxicol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/20026491051695","article-title":"The effects of harmful algal blooms on aquatic organisms","volume":"10","author":"Landsberg","year":"2002","journal-title":"Rev. Fish. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.1016\/j.ecolind.2008.11.013","article-title":"Phytoplankton bloom status: Chlorophyll a biomass as an indicator of water quality condition in the southern estuaries of Florida, USA","volume":"9","author":"Boyer","year":"2009","journal-title":"Ecol. Indic."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4009","DOI":"10.1016\/j.rse.2008.06.002","article-title":"Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments, chlorophyll a and phycocyanin","volume":"112","author":"Randolph","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_5","unstructured":"Ahn, C.-Y., Joung, S.-H., Yoon, S.-K., and Oh, H.-M. (2007). Alternative alert system for cyanobacterial bloom, using phycocyanin as a level determinant. J. Microbiol., 98\u2013104."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"947","DOI":"10.1093\/plankt\/24.9.947","article-title":"A chlorophyll-retrieval algorithm for satellite imagery (Medium Resolution Imaging Spectrometer) of inland and coastal waters","volume":"24","author":"Gons","year":"2002","journal-title":"J. Plankton Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1080\/01431160410001723682","article-title":"Spectral absorption and fluorescence characteristics of phytoplankton in different size fractions across a salinity gradient in the Baltic Sea","volume":"26","author":"Kuosa","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2065","DOI":"10.1007\/s10811-014-0244-3","article-title":"Quantitative analysis of extracted phycobilin pigments in cyanobacteria\u2014An assessment of spectrophotometric and spectrofulorometric methods","volume":"26","author":"Kosakowska","year":"2014","journal-title":"J. Appl. Phycol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.ecoinf.2013.02.006","article-title":"Remote detection of cyanobacteria through phycocyanin for water supply source using three-band model","volume":"15","author":"Song","year":"2013","journal-title":"Ecol. Inform."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4774","DOI":"10.3390\/rs5104774","article-title":"A Performance review of reflectance based algorithms for predicting phycocyanin concentrations in inland waters","volume":"5","author":"Ogashawara","year":"2013","journal-title":"Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"758","DOI":"10.3390\/rs1040758","article-title":"A novel algorithm for predicting phycocyanin concentrations in cyanobacteria: A proximal hyperspectral remote sensing approach","volume":"1","author":"Mishra","year":"2009","journal-title":"Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3996","DOI":"10.1016\/j.rse.2007.11.019","article-title":"An evaluation of algorithms for the remote sensing of cyanobacterial biomass","volume":"112","author":"Simis","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"237","DOI":"10.4319\/lo.2005.50.1.0237","article-title":"Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water","volume":"50","author":"Simis","year":"2005","journal-title":"Limnol. Oceanogr."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Larkum, A.W.D. (2003). Photosynthesis in Algae, Springer.","DOI":"10.1007\/978-94-007-1038-2"},{"key":"ref_15","unstructured":"Dekker, A.G. (1993). Detection of Optical Water Quality Parameters for Eutrophic Waters by High Resolution Remote Sensing. [Ph.D. Thesis, Vrije Universiteit]."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.ecss.2007.02.015","article-title":"Ship-of-opportunity based phycocyanin fluorescence monitoring of the filamentous cyanobacteria bloom dynamics in the Baltic Sea","volume":"73","author":"Kaitala","year":"2007","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Riha, S., and Krawczyk, H. (2011). Development of remote sensing algorithm for cyanobacterial phycocyanin pigment in the Baltic Sea using neural network approach. Proc. SPIE, 8175.","DOI":"10.1117\/12.898081"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.rse.2011.10.001","article-title":"Detection of coccolithophore blooms in ocean color satellite imagery: A generalized approach for use with multiple sensors","volume":"117","author":"Moore","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1029\/2004EO450002","article-title":"MODIS detects a devastating algal bloom in Paracas Bay, Peru","volume":"85","author":"Kahru","year":"2004","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5414","DOI":"10.1364\/AO.45.005414","article-title":"Use of hyperspectral remote sensing reflectance for detection and assessment of the harmful alga, Karenia brevis","volume":"45","author":"Craig","year":"2006","journal-title":"Appl. Opt."},{"key":"ref_21","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_22","doi-asserted-by":"crossref","first-page":"709","DOI":"10.4319\/lo.1977.22.4.0709","article-title":"Analysis of variations in ocean color","volume":"22","author":"Morel","year":"1977","journal-title":"Limnol. Oceanogr."},{"key":"ref_23","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_24","doi-asserted-by":"crossref","first-page":"083634","DOI":"10.1117\/1.JRS.8.083634","article-title":"In-air spectral signatures of the Baltic Sea macrophytes and their statistical separability","volume":"8","author":"Kotta","year":"2014","journal-title":"J. Appl. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/S0278-4343(02)00222-4","article-title":"Optical characteristic of two contrasting case 2 waters and their influence on remote sensing algorithms","volume":"23","author":"Darecki","year":"2003","journal-title":"Cont. Shelf Res."},{"key":"ref_26","first-page":"287","article-title":"The absorption of yellow substance in the Baltic Sea","volume":"22","author":"Kowalczuk","year":"2002","journal-title":"Oceanologia"},{"key":"ref_27","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_28","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_29","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_30","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_31","doi-asserted-by":"crossref","first-page":"2705","DOI":"10.1016\/j.rse.2010.06.006","article-title":"Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes","volume":"114","author":"Hunter","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_32","unstructured":"Wo\u017aniak, M. (2014). Identification of the Dominant Phytoplankton Groups in the Algal Blooms in the Waters of the Baltic Sea using Remote Sensing Methods. [Ph.D. Thesis, University of Gdansk]."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Barale, V., and Gade, M. (2008). Remote Sensing of the European Seas, Springer.","DOI":"10.1007\/978-1-4020-6772-3"},{"key":"ref_34","first-page":"261","article-title":"The hydrological and hydrochemical division of the surface waters in the Gulf of Gda\u0144sk","volume":"40","author":"Nowacki","year":"1998","journal-title":"Oceanologia"},{"key":"ref_35","unstructured":"Yasumoto, T., Oshima, Y., and Fukuyo, Y. (1996). Harmful and Toxic Algal Blooms, IOC UNESCO."},{"key":"ref_36","first-page":"255","article-title":"Toxic Nodularia spumigena blooms in the coastal waters of the Gulf of Gda\u0144sk: A ten-year survey","volume":"48","author":"Kobos","year":"2006","journal-title":"Oceanologia"},{"key":"ref_37","first-page":"173","article-title":"Ekologia toksycznych sinic. Zakwity sinic (cyjanobakterii)","volume":"59","author":"Kobos","year":"2010","journal-title":"Kosmos"},{"key":"ref_38","unstructured":"Mueller, J.L., and Austin, R.W. (1992). Ocean Optics Protocols. NASA Tech Memo, NASA Goddard Space Flight Center."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1088\/1464-4258\/8\/3\/005","article-title":"Immersion factor for the RAMSES series of hyperspectral underwater radiometers","volume":"8","author":"Zibordi","year":"2006","journal-title":"J. Opt. Pure Appl. Opt."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"13237","DOI":"10.1029\/95JC00458","article-title":"The lognormal-distribution as a model for bio-optical variability in the sea","volume":"100","author":"Campbell","year":"1995","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_41","unstructured":"Doerffer, R., and Schiller, H. (2008). MERIS Regional Coastal and Lake Case 2 Water Project Atmospheric Correction ATBD, GKSS Research Center."},{"key":"ref_42","first-page":"509","article-title":"Algorithms for the remote sensing of the Baltic ecosystem (DESAMBEM). Part 2: Empirical validation","volume":"50","author":"Darecki","year":"2008","journal-title":"Oceanologia"},{"key":"ref_43","first-page":"451","article-title":"Algorithms for the remote sensing of the Baltic ecosystem (DESAMBEM). Part 1: Mathematical apparatus","volume":"50","author":"Darecki","year":"2008","journal-title":"Oceanologia"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Wo\u017aniak, M., Bradtke, K.M., and Kr\u0119\u017cel, A. (2014). Comparison of satellite chlorophyll a algorithms for the Baltic Sea. J. Appl. Remote Sens., 8.","DOI":"10.1117\/1.JRS.8.083605"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Campbell, J.W., Anotine, D., Armstrong, R., Arrigo, K., Balch, W., and Barber, R. (2002). Comparison of algorithms for estimating ocean primary production from surface chlorophyll, temperature, and irradiance. Glob. Biogeochem. Cycles, 16.","DOI":"10.1029\/2001GB001444"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.jmarsys.2008.05.010","article-title":"Assessing the uncertainties of model estimates of primary productivity in the tropical Pacific Ocean","volume":"76","author":"Friedrichs","year":"2009","journal-title":"J. Mar. Syst."},{"key":"ref_47","first-page":"153","article-title":"Remote detection and seasonal patterns of phycocyanin, carotenoid, and clorophyll pigments in eutrophic waters","volume":"55","author":"Schalles","year":"2000","journal-title":"Arch. Hydrobiol."},{"key":"ref_48","unstructured":"Mishra, S. (2012). Remote Sensing of Harmful Algal Bloom. [Ph.D. Thesis, Mississippi State University]."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Barale, V., and Gade, M. (2008). Remote Sensing of the European Seas, Springer.","DOI":"10.1007\/978-1-4020-6772-3"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1080\/01431160410001720270","article-title":"Empirical relationships between Coloured Dissolved Organic Matter (CDOM) absorption and apparent optical properties in Baltic Sea waters","volume":"26","author":"Kowalczuk","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Roy, S., Llewellyn, C.A., Skarstad-Egeland, E., and Johnsen, G. (2011). Phytoplankton Pigments Characterization, Chemotaxonomy and Applications in Oceanography, Cambridge Environmental Chemistry Series.","DOI":"10.1017\/CBO9780511732263"},{"key":"ref_52","first-page":"1","article-title":"Long-term changes in Secchi depth and the role of phytoplankton in explaining light attenuation in the Baltic Sea","volume":"102\u2013103","author":"Laamanen","year":"2012","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_53","unstructured":"Hansson, M. (2005). Cyanobacterial blooms in the Baltic Sea, SMHI."},{"key":"ref_54","unstructured":"Raateoja, M., H\u00e4llfors, S., and Rantaj\u00e4rvi, E. (2004). Phytoplankton Biomass and Species Succession in the Gulf of Finland, Northern Baltic Proper and Arkona Basin in 2004, FIMR."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/3\/212\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:20:15Z","timestamp":1760210415000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/3\/212"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,3,5]]},"references-count":54,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2016,3]]}},"alternative-id":["rs8030212"],"URL":"https:\/\/doi.org\/10.3390\/rs8030212","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,3,5]]}}}