{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T23:06:52Z","timestamp":1777504012118,"version":"3.51.4"},"reference-count":38,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2013,9,26]],"date-time":"2013-09-26T00:00:00Z","timestamp":1380153600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>We evaluated the accuracy and sensitivity of six previously published reflectance based algorithms to retrieve Phycocyanin (PC) concentration in inland waters. We used field radiometric and pigment data obtained from two study sites located in the United States and Brazil. All the algorithms targeted the PC absorption feature observed in the water reflectance spectra between 600 and 625 nm. We evaluated the influence of chlorophyll-a (chl-a) absorption on the performance of these algorithms in two contrasting environments with very low and very high cyanobacteria content. All algorithms performed well in low to moderate PC concentrations and showed signs of saturation or decreased sensitivity for high PC concentration with a nonlinear trend. MM09 was found to be the most accurate algorithm overall with a RMSE of 15.675%. We also evaluated the use of these algorithms with the simulated spectral bands of two hyperspectral space borne sensors including Hyperion and Compact High-Resolution Imaging Spectrometer (CHRIS) and a hyperspectral air borne sensor, Hyperspectral Infrared Imager (HyspIRI). Results showed that the sensitivity for chl-a of PC retrieval algorithms for Hyperion simulated data were less noticable than using the spectral bands of CHRIS; HyspIRI results show that SC00 could be used for this sensor with low chl-a influence. This review of reflectance based algorithms can be used to select the optimal approach in studies involving cyanobacteria monitoring through optical remote sensing techniques.<\/jats:p>","DOI":"10.3390\/rs5104774","type":"journal-article","created":{"date-parts":[[2013,9,26]],"date-time":"2013-09-26T12:48:59Z","timestamp":1380199739000},"page":"4774-4798","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":74,"title":["A Performance Review of Reflectance Based Algorithms for Predicting Phycocyanin Concentrations in Inland Waters"],"prefix":"10.3390","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6328-0001","authenticated-orcid":false,"given":"Igor","family":"Ogashawara","sequence":"first","affiliation":[{"name":"Remote Sensing Division, National Institute for Space Research, Avenida dos Astronautas, 1758, S\u00e3o Jos\u00e9 dos Campos, SP 12227-010, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8192-7681","authenticated-orcid":false,"given":"Deepak","family":"Mishra","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Georgia, 210 Field Street, Athens, GA 30602,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sachidananda","family":"Mishra","sequence":"additional","affiliation":[{"name":"Dow Agrosciences, 9330 Zionsville Road, Indianapolis, IN 46268, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcelo","family":"Curtarelli","sequence":"additional","affiliation":[{"name":"Remote Sensing Division, National Institute for Space Research, Avenida dos Astronautas, 1758, S\u00e3o Jos\u00e9 dos Campos, SP 12227-010, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9","family":"Stech","sequence":"additional","affiliation":[{"name":"Remote Sensing Division, National Institute for Space Research, Avenida dos Astronautas, 1758, S\u00e3o Jos\u00e9 dos Campos, SP 12227-010, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2013,9,26]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Hyperspectral Remote Sensing of the Pigment C-Phycocyanin in Turbid Inland Waters, Based on Optical Classification","volume":"99","author":"Sun","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Huisman, J., Matthijs, H.C.P., and Visser, P.M. (2005). Harmful Cyanobacteria, Springer. [1st ed.]. Chapter 1.","DOI":"10.1007\/1-4020-3022-3"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Chorus, I., and Bartram, J. (1999). Toxic Cyanobacteria in Water: A Guide to Their Public Health Consequences, Monitoring and Management, UNESCO\/WHO\/UNEP. [1st ed.]. Chapter 3.","DOI":"10.4324\/9780203478073"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/S0300-483X(02)00491-2","article-title":"Human intoxication by microcystins during renal dialysis treatment in Caruaru-Brazil","volume":"181\u2013182","author":"Azevedo","year":"2002","journal-title":"Toxicology"},{"key":"ref_5","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_6","doi-asserted-by":"crossref","unstructured":"Reynolds, C.S. (2006). Ecology of Phytoplankton, Cambridge University Press. [1st ed].","DOI":"10.1017\/CBO9780511542145"},{"key":"ref_7","first-page":"38","article-title":"Current beliefs regarding dominance by blue-greens: the case for the importance of CO2 and pH","volume":"24","author":"Shapiro","year":"1990","journal-title":"Verh. Int. Ver. Limnol"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2373","DOI":"10.3390\/rs4082373","article-title":"Comparative analysis of four models to estimate chlorophyll-a concentration in Case-2 waters using moderate resolution imaging spectroradiometer (MODIS) imagery","volume":"4","author":"Chokmani","year":"2012","journal-title":"Remote Sens"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"8253","DOI":"10.1080\/01431161.2010.533210","article-title":"Remote sensing of phycocyanin pigment in highly turbid inland waters in Lake Taihu, China","volume":"32","author":"Le","year":"2011","journal-title":"Int. J. Remote Sens"},{"key":"ref_10","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_11","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_12","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.rse.2013.02.004","article-title":"Quantifying cyanobacterial phycocyanin concentration in turbid productive waters: A quasi-analytical approach","volume":"133","author":"Mishra","year":"2013","journal-title":"Remote Sens. Environ"},{"key":"ref_13","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_14","doi-asserted-by":"crossref","first-page":"2627","DOI":"10.1021\/es802977u","article-title":"Using remote sensing to aid the assessment of human health risks from blooms of potentially toxic cyanobacteria","volume":"43","author":"Hunter","year":"2009","journal-title":"Environ. Sci. Technol"},{"key":"ref_15","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_16","unstructured":"Dekker, A.G. (1993). Detection of Optical Water Quality Parameters for Eutrophic Waters by High Resolution Remote Sensing. Ph.D. Thesis, Vrije Universiteit, Amsterdam, The Netherlands."},{"key":"ref_17","first-page":"153","article-title":"Remote detection and seasonal patterns of phycocyanin, carotenoid, and chlorophyll pigments in eutrophic waters","volume":"55","author":"Schalles","year":"2000","journal-title":"Archives Hydrobiologica"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1046\/j.1440-169X.2002.00177.x","article-title":"Limnological features of Funil Reservoir (R.J., Brazil) and indicator properties of rotifers and cladocerans of the zooplankton community","volume":"7","author":"Branco","year":"2002","journal-title":"Lakes Reservoirs: Res. Manage"},{"key":"ref_19","first-page":"73","article-title":"Spatial and temporal variation of limnological features, Microcystis aeruginosa and zooplankton in a eutrophic reservoir (Funil Reservoir, Rio de Janeiro)","volume":"14","author":"Rocha","year":"2002","journal-title":"Acta Limnol. Brasil"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10641269609388577","article-title":"Ecology of channel catfish culture ponds in northwest Mississippi","volume":"4","author":"Tucker","year":"1996","journal-title":"Rev. Fisheries Sci"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7442","DOI":"10.1364\/AO.38.007442","article-title":"Estimation of the remote-sensing reflectance from above-surface measurements","volume":"38","author":"Mobley","year":"1999","journal-title":"Appl. Optics"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"L12","DOI":"10.1088\/1464-4258\/5\/3\/103","article-title":"Derivation of immersion factors for the hyperspectral TriOS radiance sensor","volume":"5","author":"Ohde","year":"2003","journal-title":"J. Optics A: Pure Appl. Optics"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Austin, R.W., and Halikas, G (1976). The Index of Refraction of Seawater, Visibility Laboratory-Scripps Institute of Oceanography.","DOI":"10.21236\/ADA024800"},{"key":"ref_24","first-page":"14","article-title":"Comparison of different methods for chlorophyll and phaeopigment determination","volume":"14","author":"Nush","year":"1980","journal-title":"Arch. Hydrobiol. Beih. Ergebn. Limnol"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"343","DOI":"10.4319\/lo.1967.12.2.0343","article-title":"Determination of chlorophyll and pheo-pigments: Spectrophotometric equations","volume":"12","author":"Lorenzen","year":"1967","journal-title":"Limnol. Oceanogr"},{"key":"ref_26","unstructured":"Arar, E.J. (1997). USEPA Method 447\u20130, US Environmental Protection Agency."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1016\/S0032-9592(98)00153-8","article-title":"Phycocyanin from Spirulina sp: Influence of processing of biomass on phycocyanin yield, analysis of efficacy of extraction methods and stability studies on phycocyanin","volume":"34","author":"Sarada","year":"1999","journal-title":"Process. Biochem"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1083\/jcb.58.2.419","article-title":"Complementary chromatic adaptation in a filamentous blue-green alga","volume":"58","author":"Bennett","year":"1973","journal-title":"J. Cell. Biol"},{"key":"ref_29","unstructured":"Mishra, S (2012). Remote Sensing of Harmful Algal Bloom. Ph.D. Thesis, Mississippi State University, Mississippi State, MS, USA."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/j.rse.2003.10.014","article-title":"Phycocyanin detection from LANDSAT TM data for mapping cyanobacterial blooms in Lake Erie","volume":"89","author":"Vincent","year":"2004","journal-title":"Remote Sens. Environ"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1364\/AO.44.000412","article-title":"Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results","volume":"44","author":"Gitelson","year":"2005","journal-title":"Appl. Optics"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1093\/plankt\/7.4.487","article-title":"Interactions between temperature and light intensity on growth and photosynthesis of the cyanobacterium Oscillatoria agardhii","volume":"7","author":"Post","year":"1985","journal-title":"J. Plankton Res"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Thenkabail, P.S., Lyon, G.J., and Huete, A. (2011). Hyperspectral. Remote Sensing of Vegetation, CRC Press-Taylor and Francis Group.","DOI":"10.1201\/b11222-41"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/j.rse.2013.08.002","article-title":"Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission","volume":"139","author":"Mariotto","year":"2013","journal-title":"Remote Sens. Environ"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1117\/12.366281","article-title":"Integration & Testing of the Compact High-Resolution Imaging Spectrometer (CHRIS)","volume":"3753","author":"Cutter","year":"1999","journal-title":"Proc. SPIE"},{"key":"ref_36","unstructured":"Barry, P.S., Mendenhall, J., Jarecke, P., Folkman, M., Pearlman, J., and Markham, B (2002, January 24\u201328). EO-1 Hyperion Hyperspectral Aggregation and Comparison with EO-1 Advanced Land Imager and Landsat 7 ETM+. Toronto, ON, Canada."},{"key":"ref_37","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_38","doi-asserted-by":"crossref","first-page":"4370","DOI":"10.3390\/rs5094370","article-title":"Similar studies should be performed in diverse inland waters representative of other geographical regions of the world where data are lacking","volume":"5","author":"Matthews","year":"2013","journal-title":"Remote Sens"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/5\/10\/4774\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:49:34Z","timestamp":1760219374000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/5\/10\/4774"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,9,26]]},"references-count":38,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2013,10]]}},"alternative-id":["rs5104774"],"URL":"https:\/\/doi.org\/10.3390\/rs5104774","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,9,26]]}}}