Passive optical remote sensing of cyanobacteria and other intense phytoplankton blooms in coastal and inland waters

References

• Ahn , Y.-H. and Shanmugam , P. 2006 . Detecting the red tide algal blooms from satellite ocean color observations in optically complex Northeast-Asia coastal waters . Remote Sensing of Environment , 103 : 419 – 437 .
   Web of Science ®Google Scholar
• Aiken , J. , Fishwick , J. R. , Lavender , S. , Barlow , R. , Moore , G. F. , Sessions , H. , Bernard , S. , Ras , J. and Hardman-Mountford , N. J. 2007 . Validation of MERIS reflectance and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters . International Journal of Remote Sensing , 30 : 497 – 516 .
   Web of Science ®Google Scholar
• Anderson , D. M. 2003 . “ Phytoplankton blooms ” . In Encyclopaedia of Ocean Sciences 2179 – 2192 . DOI:10.1006/rwos.2001.0050
   Google Scholar
• Arst , H. and Kutser , T. 1994 . On data processing and interpretation of the radiance factor measurements . Polar Research , 13 : 3 – 12 .
   Web of Science ®Google Scholar
• Arst , H , Mäekivi , S. , Kutser , T. , Reinart , A. , Blanco-Sequeiros , A. , Virta , J. and N[otilde]ges , P. 1996 . Investigation of different types of lakes in Estonia and Finland by optical methods . Lakes and Reservoirs: Research and Management , 2 : 187 – 198 .
   Google Scholar
• Astoreca , R. , Ruddick , K. , Rousseau , V. , Van Mol , B. , Parent , J.-Y. and Lancelot , C. 2006 . Variability of the inherent and apparent optical properties in a highly turbid coastal area: impact on the calibration of remote sensing algorithms . EARSeL eProceedings , 5 : 1 – 17 .
   Google Scholar
• Babin , M. , Cullen , J. J. , Roesler , C. S. , Donaghy , P. L. , Douchette , G. J. , Kahru , M. , Lewis , M. R. , Scholin , C. A. , Sierracki , M. E. and Sosik , H. M. 2005 . New approaches and technologies for observing harmful algal blooms . Oceanography , 18 : 210 – 227 .
   Google Scholar
• Backer , L. C. and McGillicuddy , D. J. 2006 . Harmful algal blooms. At the interface between coastal oceanography and human health . Oceanography , 19 : 94 – 106 .
   PubMedGoogle Scholar
• Balch , W. M. , Holligan , P. M. , Ackleson , S. G. and Voss , K. J. 1991 . Biological and optical properties of mesoscale coccolithophore blooms in the Gulf of Maine . Limnology and Oceanography , 36 : 629 – 643 .
   Web of Science ®Google Scholar
• Cannizzaro , J. P. , Carder , K. L. , Chen , F. R. , Heil , C. A. and Vargo , G. A. 2008 . A novel technique for detection of the toxic dinoflagellate, Karenia brevis, in the Gulf of Mexico from remotely sensed ocean color data , Vol. 28 , 137 – 158 . Continental Shelf Research .
   Google Scholar
• Chen , Z. , Hu , C. and Muller-Karger , F. 2007 . Monitoring turbidity in Tampa Bay using MODIS/Aqua 250-m imagery . Remote Sensing of Environment , 109 : 207 – 220 .
   Web of Science ®Google Scholar
• Cracknell , A. P. , Newcombe , S. K. , Black , A. F. and Kirby , N. E. 2001 . The ABDMAP (Algal Bloom Detection, Monitoring and Prediction) Concerted action . International Journal of Remote Sensing , 22 : 205 – 247 .
   Web of Science ®Google Scholar
• Craig , S. E. , Lohrenz , S. E. , Lee , Z. , Mahoney , K. L. , Kirkpatrick , G. J. , Schofield , O. M. and Steward , R. G. 2006 . Use of hyperspectral remote sensing reflectance for detection and assessment of the harmful alga . Karenia brevis. Applied Optics , 45 : 5414 – 5425 .
   PubMed Web of Science ®Google Scholar
• Cullen , J. J. , Ciotti , A. M. , Davis , R. F. and Lewis , M. R. 1997 . Optical detection and assessment of algal blooms . Limnology and Oceanography , 42 : 1223 – 1239 .
   Web of Science ®Google Scholar
• Cunningham , A. , Wood , P. and Jones , K. 2001 . Reflectance properties of hydrographically and optically stratified fjords (Scottish sea Lochs) during the spring diatom bloom . International Journal of Remote Sensing , 22 : 2885 – 2897 .
   Web of Science ®Google Scholar
• Dall'Olmo , G. and Gitelson , A. A. 2005 . Effect of bio-optical paramater variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results . Applied Optics , 44 : 412 – 422 .
   PubMed Web of Science ®Google Scholar
• Dall'Olmo , G. and Gitelson , A. A. 2006 . Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results . Applied Optics , 45 : 3577 – 3598 .
   PubMed Web of Science ®Google Scholar
• Darecki , M. and Stramski , D. 2004 . An evaluation of MODIS and SeaWiFS bio-optical algorithms in the Baltic Sea . Remote Sensing of Environment , 89 : 326 – 350 .
   Web of Science ®Google Scholar
• Dekker , A. G. 1993 . Detection of optical water quality parameters for eutrophic waters by high resolution remote sensing , Amsterdam, , The Netherlands : Vrije Universiteit . PhD thesis
   Google Scholar
• Dekker , A. G. , Brando , V. E. , Anstee , J. M. , Pinnel , N. , Kutser , T. , Hoogenboom , E. J. , Peters , S. , Pasterkamp , R. , Vos , R. , Olbert , C. and Malthus , T. J.M. 2001 . “ Imaging spectrometry of water ” . In Imaging Spectrometry: Basic Principles and Prospective Applications , Edited by: van der Meer , F.D and de Jong , S. M. 307 – 359 . Dordrecht : Kluwer Academic Publishers .
   Google Scholar
• Dekker , A. G. , Malthus , T. J. and Goddijn , L. M. 1992 . Monitoring cyanobacteria in eutrophic waters using airborne imaging spectroscopy and multispectral remote sensing systems . Proceedings of 6th Australasian Remote Sensing Conference, Wellington , 1 : 204 – 214 .
   Google Scholar
• Dierssen , H. M. , Kudela , R. M. , Ryan , J. P. and Zimmerman , R. C. 2006 . Red and black tides: Quantitative analysis of water-leaving radiance and perceived color for phytoplankton, colored dissolved organic matter and suspended sediments . Limnology and Oceanography , 51 : 2646 – 2659 .
   Web of Science ®Google Scholar
• Dupouy , C. , Petit , M. and Dandonneau , Y. 1988 . Satellite detected cyanobacteria bloom in the southwestern tropical Pacific. Implications for oceanic nitrogen fixation . International Journal of Remote Sensing , 9 : 389 – 396 .
   Web of Science ®Google Scholar
• Edler , L. , Fernö , S. , Lind , M. G. , Lundberg , R. and Nilsson , P. O. 1985 . Mortality of dogs associated with a bloom of the cyanobacterium . Nodularia spumigena in the Baltic Sea. Ophelia , 24 : 103 – 109 .
   Google Scholar
• Ekstrand , S . 1992 . Landsat TM based quantification of chlorophyll-a during algae blooms in coastal waters . International Journal of Remote Sensing , 13 : 1913 – 1926 .
   Web of Science ®Google Scholar
• Fischer , J. and Kronfeld , U. 1990 . Sun-stimulated chlorophyll fluorescence 1: Influence of oceanic properties . International Journal of Remote Sensing , 11 : 2125 – 2147 .
   Web of Science ®Google Scholar
• Folkestad , A. , Pettersson , L. H. and Durand , D. D. 2007 . Inter-comparison of ocean colour data products during algal blooms in the Skagerrak . International Journal of Remote Sensing , 28 : 569 – 592 .
   Web of Science ®Google Scholar
• Fraser , R. N. 1998 . Hyperspectral remote sensing of turbidity and chlorophyll a among Nebraska Sand Hills lakes . International Journal of Remote Sensing , 19 : 1579 – 1589 .
   Web of Science ®Google Scholar
• Galat , D. L. and Verdin , J. P. 1989 . Patchiness, collapse and succession of cyanobacterial bloom evaluated by synoptic sampling and remote sensing . Journal of Plankton Research , 11 : 925 – 948 .
   Web of Science ®Google Scholar
• Garver , S. A. , Siegel , D. A. and Mitchell , B. G. 1994 . Variability in near-surface particulate absorption spectra: What can a satellite ocean color imager see? . Limnology and Oceanography , 39 : 1349 – 1367 .
   Web of Science ®Google Scholar
• Gin , K. Y.-H. , Koh , S. T. and Chan , E. S. 2002 . Application of spectral signatures and colour ratios to estimate chlorophyll in Singapore's coastal waters . Estuarine, Coastal and Shelf Science , 55 : 719 – 728 .
   Web of Science ®Google Scholar
• Gitelson , A. A. 1992 . The peak near 700 nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration . International Journal of Remote Sensing , 13 : 3367 – 3373 .
   Web of Science ®Google Scholar
• Gitelson , A. , Garbuzov , G. , Szilagyi , F. , Mittenzwey , K.-H. , Karnieli , A. and Kaiser , A. 1993 . Quantitative remote sensing methods for real-time monitoring of inland waters quality . International Journal of Remote Sensing , 14 : 1269 – 1295 .
   Web of Science ®Google Scholar
• Gitelson , A. A. , Schalles , J. F. and Hladik , C. M. 2007 . Remote chlorophyll-a retrieval in turbid, productive estuaries: Chesepeake Bay case study . Remote Sensing of Environment , 109 : 464 – 472 .
   Web of Science ®Google Scholar
• Glibert , P. M. , Anderson , D. M. , Gentien , P. , Graneli , E. and Sellner , K. G. 2005a . The global, complex phenomena of harmful algal blooms . Oceanography , 18 : 136 – 147 .
   Google Scholar
• Glibert , P. M. , Seitzinger , S. , Heil , C. A. , Burkholder , J. M. , Parrow , M. W. , Codispoti , L. A. and Kelly , V. 2005b . The role of eutrophication in the global proliferation of harmful algal blooms. New perspectives and new approaches . Oceanography , 18 : 198 – 209 .
   Google Scholar
• Gons , H. J. 1999 . Optical Teledetection of chlorophyll a in turbid inland waters . Environmental Science and Technology , 33 : 1127 – 1132 .
   Web of Science ®Google Scholar
• Gons , H. J. , Rijkeboer , M. and Ruddick , K. G. 2005 . Effect of a waveband shift on chlorophyll retrieval from MERIS imagery of inland and coastal waters . Journal of Plankton Research , 27 : 125 – 127 .
   Web of Science ®Google Scholar
• Gower , J. F.R. 1994 . Red tide monitoring using AVHRR HRPT imagery from local receiver . Remote Sensing of Environment , 48 : 309 – 318 .
   Web of Science ®Google Scholar
• Gower , J. F.R. , Doerffer , R. and Borstad , G. A. 1999 . Interpretation of the 685 nm peak in water-leaving radiance spectra in terms of fluorescence, absorption and scattering and its observation by MERIS . International Journal of Remote Sensing , 20 : 1771 – 1786 .
   Web of Science ®Google Scholar
• Gower , J. and King , S. 2007 . Validation of chlorophyll fluorescence derived from MERIS on the west coast of Canada . International Journal of Remote Sensing , 30 : 625 – 635 .
   Web of Science ®Google Scholar
• Gower , J. , King , S. , Borstad , G. and Brown , L. 2005 . Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer . International Journal of Remote Sensing , 26 : 2005 – 2012 .
   Web of Science ®Google Scholar
• Håkanson , B. G. and Moberg , M. 1994 . The algal bloom in the Baltic during July and August 1991, as observed from NOAA weather satellites . International Journal of Remote Sensing , 15 : 963 – 965 .
   Web of Science ®Google Scholar
• Hallegraeff , G. M. 2003 . “ Harmful algal blooms A global review ” . In Manual on harmful marine microalgae , Edited by: Hallegraeff , G. M. , Anderson , D. M. and Cembella , A. D. 1 – 22 . Paris : UNESCO .
   Google Scholar
• Härmä , P. , Vepsäläinen , J. , Hannonen , T. , Pyhälahti , T. , Kämäri , J. , Kallio , K. , Eloheimo , K. and Koponen , S. 2001 . Detection of water quality using simulated satellite data and semi-empirical algorithms in Finland . The Science of the Total Environment , 268 : 107 – 121 .
   PubMed Web of Science ®Google Scholar
• Hoepffner , N. and Sathyendranath , S. 1991 . Effect of pigment composition on absorption properties of phytoplankton . Marine Ecology Progress Series , 73 : 11 – 23 .
   Web of Science ®Google Scholar
• Hoge , F. E. , Wright , C. W. , Lyion , P. E. , Swift , R. N. and Yungel , J. K. 1999 . Satellite retrieval of the absorption coefficient of phytoplankton phycoerythrin pigment: theory and feasibility status . Applied Optics , 38 : 7431 – 7441 .
   PubMed Web of Science ®Google Scholar
• Holligan , P. M. , Viollier , M. , Dupouy , C. and Aiken , J. 1983 . Satellite studies on the distributions of chlorophyll and dinoflagellate blooms in the western English Channel . Continental Shelf Research , 2 : 81 – 96 .
   Web of Science ®Google Scholar
• Hoogenboom , H. J. , Dekker , A. G. and de Haan , J. F. 1998a . Retrieval of chlorophyll and suspended matter from imaging spectrometer data by matrix inversion . Canadian Journal of Remote Sensing , 24 : 144 – 152 .
   Google Scholar
• Hoogenboom , H. J. , Dekker , A. G. and Althuis , I J.A. 1998b . Simulation of AVIRIS sensitivity for detecting chlorophyll over coastal and inland waters . Remote Sensing of Environment , 65 : 333 – 340 .
   Web of Science ®Google Scholar
• Horner , R. A. , Garrison , D. L. and Plumley , F. G. 1997 . Harmful algal blooms and red tide problems on the US west coast . Limnology and Oceanography , 42 : 1076 – 1088 .
   Web of Science ®Google Scholar
• Hu , C. , Luerssen , R. , Muller-Karger , F. E. , Carder , K. L. and Heil , C. A. 2008 . “ On the remote monitoring of Karenia brevis blooms of the west Florida shelf. Continental Shelf Research ” . Vol. 28 , 159 – 176 .
   Google Scholar
• Hu , C. , Muller-Karger , F. E. and Swarzenski , P. W. 2006 . Hurricanes, submarine groundwater discharge and Florida's red tides . Geophysical Research Letters , 33 : L11601
   Web of Science ®Google Scholar
• Hu , C. , Muller-Karger , F. E. , Taylor , C. , Carder , K. L. , Kelble , C. , Johns , E. and Heil , C. A. 2005 . Red tide detection and tracing using MODIS fluorescence data: A regional example in SW Florida coastal waters . Remote Sensing of Environment , 97 : 311 – 321 .
   Web of Science ®Google Scholar
• Huang , W. G. and Lou , X. L. 2003 . AVHRR detection of red tides with neural networks . International Journal of Remote Sensing , 24 : 1991 – 1996 .
   Web of Science ®Google Scholar
• Hunter , P. D. , Tyler , A. N. , Presing , M. , Kovacs , A. W. and Preston , T. 2008 . “ Spectral discrimination of phytoplankton colour groups: The effect of suspended particulate matter and sensor spectral resolution ” . In Remote Sensing of Environment Vol. 112 , 1527 – 1544 .
   Google Scholar
• Jeffrey , S. W. and Vesk , M. 1997 . “ Introduction to marine phytoplankton and their pigment signatures ” . In Phytoplankton Pigments in Oceanography: Guidelines to Modern Methods , Edited by: Jeffrey , S. W. , Mantoura , R. F.C. and Wright , S. W. 37 – 84 . Paris : UNESCO .
   Google Scholar
• Johnsen , G. and Sakshaug , E. 1993 . Bio-optical characteristics and photoadaptive responses in the toxic and bloom-forming dinoflagellates Gyrodinium aureolum, Gymnodinium galtheanum and two strains of Prorocentrum minimum . Journal of Phycology , 29 : 627 – 642 .
   Web of Science ®Google Scholar
• Johnsen , G. , Samset , O. , Granskog , L. and Sakshaug , E. 1994 . In vivo absorption characteristics in 10 classes of bloom-forming phytoplankton: taxonomic characteristics and responses to photoadaptation by means of discriminant and HPLC analysis . Marine Environment Progress Series , 105 : 149 – 157 .
   Web of Science ®Google Scholar
• Joint , I. and Groom , S. B. 2000 . Estimation of phytoplankton production from space: current status and future potential of satellite remote sensing . Journal of Experimental Marine Biology and Ecology , 25 : 233 – 255 .
   Web of Science ®Google Scholar
• Jupp , D. L.B. , Kirk , J. T.O. and Harris , G. P. 1994 . Detection, identification and mapping of cyanobacteria – using remote sensing to measure the optical quality of turbid inland waters . Australian Journal of Marine and Freshwater Research , 45 : 801 – 828 .
   Web of Science ®Google Scholar
• Kahru , M. and Brown , C. W. 1997 . Monitoring Algal Blooms: new techniques for detecting large-scale environmental change , Berlin : Springer–Verlag .
   Google Scholar
• Kahru , M. , Leppänen , J.-M. and Rud , O. 1993 . Cyanobacterial blooms cause heating of the sea surface . Marine Ecology Progress Series , 101 : 1 – 7 .
   Web of Science ®Google Scholar
• Kahru , M. , Leppänen , J.-M. , Rud , O. and Savchuk , O. P. 2000 . Cyanobacteria blooms in the Gulf of Finland triggered by saltwater inflow into the Baltic sea . Marine Ecology Progress Series , 207 : 13 – 18 .
   Web of Science ®Google Scholar
• Kahru , M. and Mitchell , B. G. 1998 . Spectral reflectance and absorption of a massive red tide off southern California . Journal of Geophysical Research , 103 : 21 601 – 21 609 .
   Web of Science ®Google Scholar
• Kahru , M. , Mitchell , B. G. , Diaz , A. and Miura , M. 2004 . MODIS detects a Devastating Algal bloom in Paracas Bay, Peru . Eos , 85 : 465 – 472 .
   Google Scholar
• Kahru , M. , Savchuk , O. P. and Elmgren , R. 2007 . Satellite measurements of cyanobacterial bloom frequency in the Baltic Sea: interannual and spatial variability . Marine Ecology Progress Series , 343 : 15 – 23 .
   Web of Science ®Google Scholar
• Kallio , K. , Koponen , S. and Pulliainen , J. 2003 . Feasibility of airborne imaging spectrometry for lake monitoring – a case study of spatial chlorophyll a distribution on two meso-eutrophic lakes . International Journal of Remote Sensing , 24 : 3771 – 3790 .
   Web of Science ®Google Scholar
• Kallio , K. , Kutser , T. , Hannonen , T. , Koponen , S. , Pulliainen , J. , Vepsäläinen , J. and Pyhälahti , T. 2001 . Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons . The Science of the Total Environment , 268 : 59 – 77 .
   PubMed Web of Science ®Google Scholar
• Kirkpatrick , G. J. , Millie , D. F. , Moline , M. A. and Schofield , O. 2000 . Optical discrimination of a phytoplankton species in natural mixed populations . Limnology and Oceanography , 45 : 467 – 471 .
   Web of Science ®Google Scholar
• Koponen , S. , Attila , J. , Pulliainen , J. , Kallio , K. , Pyhälahti , T. , Lindfors , A. , Rasmus , K. and Hallikainen , M. 2007 . A case study of airborne and satellite remote sensing of a spring bloom event in the Gulf of Finland . Continental Shelf Research , 27 : 228 – 244 .
   Web of Science ®Google Scholar
• Koponen , S. , Pulliainen , J. , Kallio , K. and Hallikainen , M. 2002 . Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data . Remote Sensing of Environment , 79 : 51 – 59 .
   Web of Science ®Google Scholar
• Kuchler , D. A. and Jupp , D. L.B. 1988 . Shuttle photograph captures massive phytoplankton bloom in the Great Barrier Reef . International Journal of Remote Sensing , 9 : 1299 – 1301 .
   Web of Science ®Google Scholar
• Kutser , T. 1997 . Estimation of water quality in turbid inland and coastal waters by passive optical remote sensing , Vol. 8 , Dissertationes Geophysicales Universitas Tartuensis . Tartu University Press
   Google Scholar
• Kutser , T. 2004 . Quantitative detection of chlorophyll in cyanobacterial blooms by the satellite remote sensing . Limnology and Oceanography , 49 : 2179 – 2189 .
   Web of Science ®Google Scholar
• Kutser , T. and Arst , H. 1994 . Remote sensing reflectance model of optically active components of turbid waters . SPIE Proceedings , 2319 : 85 – 91 .
   Google Scholar
• Kutser , T. , Arst , H. , Miller , T. , Käärmann , L. and Milius , A. 1995 . Telespectrometrical estimation of water transparency, chlorophyll a and total phosphorus concentrations on Lake Peipsi . International Journal of Remote Sensing , 16 : 3069 – 3085 .
   Web of Science ®Google Scholar
• Kutser , T. , Arst , H. , Mäekivi , S. and Blanco-Sequeiros , A. 1997a . Optical inverse problem in turbid waters . SPIE Proceedings , 2963 : 477 – 482 .
   Google Scholar
• Kutser , T. , Arst , H. , Mäekivi , S. and Kallaste , K. 1998a . Estimation of the water quality of the Baltic Sea and some lakes in Estonia and Finland by passive optical remote sensing measurements on board a vessel . Lakes and Reservoirs; Research and Management , 3 : 53 – 66 .
   Google Scholar
• Kutser , T. , Arst , H. , Mäekivi , S. , Leppänen , J.-M. and Blanco , A. 1997b . “ Monitoring algae blooms by optical remote sensing ” . In Remote Sensing '96 , Edited by: Spiteri , A. 161 – 166 . Rotterdam : Balkema .
   Google Scholar
• Kutser , T. , Dekker , A. G. and Skirving , W. 2003 . Modelling spectral discrimination of Great Barrier Reef benthic communities by remote sensing instruments . Limnology and Oceanography , 48 : 497 – 510 .
   Web of Science ®Google Scholar
• Kutser , T. , Eloheimo , K. , Hannonen , T. , Härmä , P. , Kirkkala , T. , Koponen , S. , Pulliainen , J. and Pyhälahti , T. 1998b . “ Monitoring of coastal waters of the Baltic Sea by airborne imaging spectrometer AISA ” . In Environmental Coastal Regions , Edited by: Brebbia , C. A. 123 – 134 . Southampton : WIT press .
   Google Scholar
• Kutser , T. , Herlevi , A. , Kallio , K. and Arst , H. 2001 . A hyperspectral model for interpretation of passive optical remote sensing data from turbid lakes . The Science of the Total Environment , 268 : 47 – 58 .
   PubMed Web of Science ®Google Scholar
• Kutser , T. , Kallio , K. , Eloheimo , K. , Hannonen , T. , Pyhälahti , T. , Koponen , S. and Pulliainen , J. 1999 . Quantitative monitoring of water properties by airborne imaging spectrometer AISA . Proceedings of the Estonian Academy of Sciences. Biology.Ecology , 48 : 25 – 36 .
   Google Scholar
• Kutser , T. , Metsamaa , L. and Dekker , A. G. 2008 . Influence of vertical distribution of cyanobacteria in water column on the remote sensing signal . Estuarine, Coastal and Shelf Science , 78 : 649 – 654 .
   Web of Science ®Google Scholar
• Kutser , T. , Metsamaa , L. , Strömbeck , N. and Vahtmäe , E. 2006a . Monitoring cyanobacterial blooms by satellite remote sensing . Estuarine Coastal and Shelf Science , 67 : 303 – 312 .
   Web of Science ®Google Scholar
• Kutser , T. , Metsamaa , L. , Vahtmäe , E. and Aps , R. 2007 . Operative Monitoring of the Extent of Dredging Plumes in Coastal Ecosystems Using MODIS Satellite Imagery . Journal of Coastal Research , SI50 : 180 – 184 .
   Google Scholar
• Kutser , T. , Metsamaa , L. , Vahtmäe , E. and Strömbeck , N. 2006b . On suitability of MODIS 250 m resolution band data for quantitative mapping cyanobacterial blooms . Proceedings of the Estonian Academy of Sciences. Biology-Ecology , 55 : 318 – 328 .
   Google Scholar
• Kutser , T. , Miller , I. and Jupp , D. L.B. 2006c . Mapping coral reef benthic substrates using hyperspectral space-borne images and spectral libraries . Estuarine Coastal and Shelf Science , 70 : 449 – 460 .
   Web of Science ®Google Scholar
• Kutser , T. , Pierson , D. C. , Kallio , K. , Reinart , A. and Sobek , S. 2005 . Mapping lake CDOM by satellite remote sensing . Remote Sensing of Environment , 94 : 535 – 540 .
   Web of Science ®Google Scholar
• Kutser , T. , Vahtmäe , E. and Martin , G. 2006d . Assessing suitability of multispectral satellites for mapping benthic macroalgal cover in turbid coastal waters by means of model simulations . Estuarine Coastal and Shelf Science , 67 : 521 – 529 .
   Web of Science ®Google Scholar
• Lampert , L. , Queguiner , B. , Labasque , T. , Pichon , A. and Lebreton , N. 2002 . Spatial variability of phytoplankton composition and biomass on the eastern continental shelf of Bay of Biscay (nort-east Atlantic Ocean). Evidence for a bloom of . Emiliania hyxley (Prymnesiophyceae) in Spring 1998. Continental Shelf Research , 22 : 1225 – 1247 .
   Google Scholar
• Landsberg , J. 2002 . Effects of algal blooms on aquatic organisms . Reviews in Fisheries Science , 10 : 113 – 190 .
   Web of Science ®Google Scholar
• Lavender , S. J. and Groom , S. B. 2001 . The detection and mapping of algal blooms from space . International Journal of Remote Sensing , 22 : 197 – 201 .
   Web of Science ®Google Scholar
• Lee , Z. and Carder , K. L. 2004 . Absorption spectrum of phytoplankton pigments derived from hyperspectral remote-sensing reflectance . Remote Sensing of Environment , 89 : 361 – 368 .
   Web of Science ®Google Scholar
• Leong , S. C.Y. and Taguchi , S. 2006 . Detecting the bloom-forming dinoflagellate Alexandrum tamarense using the absorption signature . Hydrobiologia , 568 : 299 – 308 .
   Web of Science ®Google Scholar
• Leppänen , J.-M. , Rantajärvi , E. , Hällförs , S. , Kruskopf , M. and Laine , V. 1995 . Unattended monitoring of potentially toxic phytoplankton species in the Baltic Sea in 1993 . Journal of Plankton Research , 17 : 891 – 902 .
   Web of Science ®Google Scholar
• Letelier , R. M. and Abbott , M. R. 1996 . An analysis of chlorophyll fluorescence algorithms for the Moderate Resolution Imaging Spectrometer (MODIS) . Remote Sensing of Environment , 58 : 215 – 223 .
   Web of Science ®Google Scholar
• Lin , Q. , Zhang , Y. , Nie , Y. and Guan , Y. 2003 . Detection of harmful algal blooms over the Gulf of Bohai sea in China at visible and near infrared (NIR) wavelengths of remote sensing . Journal of Electromagnetic Waves and Applications , 17 : 861 – 871 .
   Web of Science ®Google Scholar
• Malthus , T. J. and Dekker , A. G. 1995 . First derivative indices for the remote sensing of inland water quality using high spectral resolution reflectance . Environment International , 21 : 221 – 232 .
   Web of Science ®Google Scholar
• Malthus , T. J. , Grieve , L. and Harwar , M. D. 1997 . “ Spectral modeling for the identification and quantification of algal blooms: A test of approach ” . In Fourth International Conference on Remote Sensing for Marine and Coastal Environments , 223 – 232 . Orlando : Ann Arbor: Environmental Research Institute of Michigan .
   Google Scholar
• McKee , D. , Cunningham , A. , Wright , D. and Hay , L. 2007 . Potential impact of nonalgal materials on water-leaving Sun induced chlorophyll fluorescence signals in coastal waters . Applied Optics , 46 : 7720 – 7729 .
   PubMed Web of Science ®Google Scholar
• Metsamaa , L. , Kutser , T. and Strömbeck , N. 2006 . Recognising cyanobacterial blooms based on their optical signature: a modelling study . Boreal Environment Research , 11 : 493 – 506 .
   Web of Science ®Google Scholar
• Miller , P. I. , Shutler , J. D. , Moore , G. F. and Groom , S. B. 2006 . SeaWiFS discrimination of harmful algal bloom evolution . International Journal of Remote Sensing , 27 : 2287 – 2301 .
   Web of Science ®Google Scholar
• Millie , D. F. , Backer , M. C. , Tucker , C. S. , Vinyard , B. T. and Dionigi , C. P. 1992 . High-resolution airborne remote sensing of bloom-forming phytoplankton . Journal of Phycology , 28 : 281 – 290 .
   Web of Science ®Google Scholar
• Millie , D. F. , Kirkpatrick , G. J. and Vinyard , B. T. 1995 . Relating photosynthetic pigments and in vivo optical density spectra to irradiance for the Florida red-tide dinoflagellate . Gymnodinium breve. Marine Ecology Progress Series , 120 : 65 – 75 .
   Web of Science ®Google Scholar
• Millie , D. F. , Schofield , O. M. , Kirkpatrik , G. J. , Johnsen , G. and Evens , T. J. 2002 . Using absorbance and fluorescence spectra to discriminate microalgae . European Journal of Phycology , 37 : 313 – 322 .
   Web of Science ®Google Scholar
• Millie , D. F. , Schofield , O. M. , Kirkpatrik , G. J. , Johnsen , G. , Tester , P. A. and Vinyard , B. T. 1997 . Detection of harmful algal blooms using photopigments and absorption signatures: A case study of the Florida red tide dinoflagellate . Gymnodinium breve. Limnology and Oceanography , 42 : 1240 – 1251 .
   Web of Science ®Google Scholar
• Neville , R. A. and Gower , J. F.R. 1977 . Passive remote sensing of phytoplankton via chlorophyll a fluorescence . Journal of Geophysical research , 82 : 3487 – 3493 .
   Web of Science ®Google Scholar
• Oki , K. and Yasuoka , Y. 2002 . Estimation of chlorophyll concentration in lakes and inland seas with a field spectroradiometer above the water surface . Applied Optics , 41 : 6463 – 6469 .
   PubMed Web of Science ®Google Scholar
• Öström , B. 1976 . Fertilization of the Baltic by nitrogen fixation in the blue-green alga . Nodularia spumigena. Remote Sensing of Environment , 4 : 305 – 310 .
   Google Scholar
• Pena-Matinez , R. , Domingues-Gomez , A. , de Hoyos , C. and Ruiz-Verdu , A . 2003 . “ Mapping of photosynthetic pigments in Spanish reservoirs ” . In Proceedings of the MERIS User Workshop , 00 – 01 . Frascati, , Italy : Frascati: ESA .
   Google Scholar
• Pozdnyakov , D. , Shuchman , R. , Korosov , A. and Hatt , C. 2005 . Operational algorithm for the retrieval of water quality in the Great Lakes . Remote Sensing of Environment , 97 : 352 – 370 .
   Web of Science ®Google Scholar
• Quibell , G. 1992 . Estimating chlorophyll concentrations using upwelling radiance from different freshwater algal genera . International Journal of Remote Sensing , 13 : 2611 – 2621 .
   Web of Science ®Google Scholar
• Raateoja , M. , Seppälä , J. and Ylöstalo , P. 2004 . Fast repetition rate fluorometry is not applicable to studies of filamentous cyanobacteria from the Baltic Sea . Limnology and Oceanography , 49 : 1006 – 1012 .
   Web of Science ®Google Scholar
• Ramos , A. G. , Martel , A. , Codd , G. A. , Soler , E. , Coca , J. , Redondo , A. , Morrison , L. F. , Metcalf , J. S. , Ojeda , A. , Suarez , S. and Petit , M. 2005 . Bloom of the marine diazotrophic cyanobacterium Trichodesmium erytraeum in the Northwest African Upwelling . Marine Ecology Progress Series , 301 : 303 – 305 .
   Web of Science ®Google Scholar
• Reinart , A. and Kutser , T. 2006 . Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea . Remote Sensing of Environment , 102 : 74 – 85 .
   Web of Science ®Google Scholar
• Richardson , L. L. 1996 . Remote sensing of algal bloom dynamics . BioScience , 46 : 492 – 501 .
   Web of Science ®Google Scholar
• Richardson , L. L. , Bulsson , D. , Liu , C. J. and Ambrosia , V. 1994 . The detection of algal photosynthetic accessory pigments using airborne visible-infrared imaging spectrometer (AVIRIS) spectral data . Marine Technology Society Journal , 28 : 10 – 21 .
   Web of Science ®Google Scholar
• Richardson , L. L. and Kruse , F. A. 2000 . “ Use of hyperspectral (AVIRIS) data to classify and map mixed phytoplankton blooms in coastal waters ” . In Sixth International Conference on Remote Sensing for Marine and Coastal Environments , 39 – 46 . Charleston : Ann Arbor: Environmental Research Institute of Michigan .
   Google Scholar
• Ruiz-Verdu , A. , Dominguez-Gomez , J-A. and Pena-Martinez , R. 2005 . “ Use of chris for monitoring water quality in rosarito reservoir. In Proceedings of the 3rd ESA CHRIS/Proba Workshop, 21–23 March, ESRIN ” . 00 – 01 . Frascati, , Italy Frascati: ESA)
   Google Scholar
• Rundquist , D. C. , Han , L. , Schalles , J. F. and Peake , J. S. 1996 . Remote measurement of algal chlorophyll in surface waters: the case for the first derivative of reflectance near 690 nm . Photogrammetric Engineering and Remote Sensing , 62 : 195 – 200 .
   Web of Science ®Google Scholar
• Sackmann , B and Perry , M. J. 2006 . Ocean color observations of a surface water transport event: Implications for Pseudo-nitzchia on the Washington coast . Harmful Algae , 5 : 608 – 619 .
   Web of Science ®Google Scholar
• Santoleri , R. , Banzon , V. , Marullo , S. , Napolitano , E. and D'Ortenzio , F. D. 2003 . Year-to-year variability of the phytoplankton bloom in the southern Adriatic Sea (1998–2000): Sea-viewing Wide Field-of-view Sensor observations and modeling study . Journal of Geophysical Research , 108 DOI: 10.1029/2002JC001636
   PubMed Web of Science ®Google Scholar
• Sarangi , R. K. , Chauhan , P. , Nayak , S. R. and Shreedhar , U. 2005 . Remote sensing of Trichodesmium blooms in the coastal waters off Gujarat, India using IRS–P4 OCM . International Journal of Remote Sensing , 9 : 1777 – 1780 .
   Web of Science ®Google Scholar
• Sasamal , S. K. , Panigrahy , R. C. and Misra , S. 2005 . Asterionella blooms in the northwestern Bay of Bengal during 2004 . International Journal of Remote Sensing , 26 : 3853 – 3858 .
   Web of Science ®Google Scholar
• Sathyendranath , S. , Cota , G. , Stuart , V. , Maass , H. and Platt , T. 2001 . Remote sensing of phytoplankton pigments: a comparison of empirical and theoretical approaches . International Journal of Remote Sensing , 22 : 249 – 273 .
   Web of Science ®Google Scholar
• Sathyendranath , S. , Rao , D. V.S. , Chen , Z. , Stuart , V. , Platt , T. , Bugden , G. L. , Jones , W. and Vass , P. 1997 . Aircraft remote sensing of toxic phytoplankton blooms: A case study from Cardigan River, Prince Edward Island . Canadian Journal of Remote Sensing , 23 : 15 – 23 .
   Google Scholar
• Schalles , J. F. , Gitelson , A. A. , Yacobi , Y. Z. and Kroenke , A. E. 1998 . Estimation of chlorophyll a from time series measurements of high spectral resolution reflectance in an eutrophic lake . Journal of Phycology , 34 : 383 – 390 .
   Web of Science ®Google Scholar
• Schalles , J. F. and Yacobi , Y. Z. 2000 . Remote detection and seasonal patterns of phycocyanin, carotenoid and chlorophyll pigments in eutrophic waters . Archivfur Hydrobiologie Special Issues Advances in Limnology , 55 : 153 – 168 .
   Google Scholar
• Schiller , H. and Doerffer , R. 1999 . Neural network for emulation of an inverse model – operational derivation of Case II water properties from MERIS data . International Journal of Remote Sensing , 20 : 1735 – 1746 .
   Web of Science ®Google Scholar
• Schofield , O. , Grzymski , J. , Bisset , W. P. , Kirkpatrick , G. J. , Millie , D. F. , Moline , M. and Roesler , C. S. 1999 . Optical monitoring and forecasting systems for harmful algal blooms: possibility or pipe dream? . Journal of Phycology , 35 : 1477 – 1496 .
   Web of Science ®Google Scholar
• Schofield , O. , Kerfoot , J. , Mahoney , K. , Moline , M. , Oliver , M. , Lohrenz , S. and Kirkpatrick , G. 2006 . Vertical migration of the toxic dinoflagellate Karenia brevis and the impact on ocean optical properties . Journal of Geophysical Research , 111 DOI: 10.1029/2005JC003115
   PubMed Web of Science ®Google Scholar
• Schwarz , J. N. , Weeks , A. R. , Ediger , D. , Kaczmarek , S. and Raine , R. 2002 . “ Detection of algal pigments from in situ data ” . In Ocean Optics XVI Santa Fe, , USA Halifax: Lewis Conference Services International)CD-ROM
   Google Scholar
• Sellner , K. G. , Douchette , G. J. and Kirkpatrick , G. J. 2003 . Harmful algal blooms: causes, impacts and detection . Journal of Indian Microbiology and Biotechnology , 30 : 383 – 406 .
   PubMed Web of Science ®Google Scholar
• Seppälä , J. , Ylöstalo , P. , Kaitala , S. , Hällfors , S. , Raateoja , M. and Maunula , P. 2007 . Estuarine, Coastal and Shelf Science , 73 : 489 – 500 . Ship-of-opportunity based phycocyanin fluorescence monitoring of the filamentous bloom dynamics in the Baltic Sea
   Web of Science ®Google Scholar
• Siegel , H. and Gerth , M. 2000 . “ Remote-sensing studies of the exceptional summer of 1997 in the Baltic Sea: the warmest August of the century, the Oder flood and phytoplankton blooms ” . In Satellites, Oceanography and Society , Edited by: Halpern , D. 239 – 255 . Elsevier Science . Amsterdam
   Google Scholar
• Siegel , H. , Gerth , M. , Neumann , T. and Doerffer , R. 1999 . Case studies on phytoplankton blooms in coastal and open waters of the Baltic Sea using Coastal Zone Colour Scanner data . International Journal of Remote Sensing , 20 : 1249 – 1264 .
   Web of Science ®Google Scholar
• Siegel , H. , Ohde , T. , Gerth , M. , Lavik , G. and Leipe , T. 2007 . Identification of coccolithophore blooms in the SE Atlantic Ocean off Namibia by satellites and in-situ methods . Continental Shelf Research , 27 : 258 – 274 .
   Web of Science ®Google Scholar
• Simis , S. G.H. , Peters , S. W.M. and Gons , H. J. 2005 . Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water . Limnology and Oceanography , 50 : 237 – 245 .
   Web of Science ®Google Scholar
• Simis , S. G.H. , Ruiz-Verdu , A. , Dominguez-Gomez , J. A. , Pena-Martinez , R. , Peters , S. W.M. and Gons , H. J. 2007 . Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass . Remote Sensing of Environment , 106 : 414 – 427 .
   Web of Science ®Google Scholar
• Smayda , T. J. 1997a . Harmful algal blooms: Their ecophysiology and general relevance to phytoplankton blooms in the sea . Limnology and Oceanography , 42 : 1137 – 1153 .
   Web of Science ®Google Scholar
• Smayda , T. J. 1997b . What is a bloom? A commentary . Limnology and Oceanography , 42 : 1132 – 1136 .
   Web of Science ®Google Scholar
• Smith , R. C. and Baker , K. S. 1981 . Optical properties of the clearest natural waters (200–800 nm) . Applied Optics , 20 : 177 – 184 .
   PubMed Web of Science ®Google Scholar
• Spitzer , D. and Dirks , R. W.J. 1986 . Chlorophyll fluorescence effects in the red part of reflectance spectra of natural waters . Continental Shelf Research , 6 : 385 – 395 .
   Web of Science ®Google Scholar
• Strömbeck , N. and Pierson , D. C. 2001 . The effects of variability in the inherent optical properties on estimations of chlorophyll a by remote sensing in Swedish freshwaters . The Science of the Total Environment , 268 : 123 – 137 .
   PubMed Web of Science ®Google Scholar
• Stumpf , R. P. 2001 . Applications of satellite ocean color sensors for monitoring and predicting harmful algal blooms . Human and Ecological Risk Assessment , 5 : 1363 – 1368 .
   Web of Science ®Google Scholar
• Stumpf , R. P. , Arnone , R. A. , Gould , R. W. , Martinolich , P. , Ransibrahmanakul , V. , Tester , P. A. , Steward , R. G. , Subramaniam , A. , Culver , M. E. and Pennock , J. R. 2000 . “ SEAWIFS ocean color data for US Southeast coastal waters ” . In Proceedings of 6^th International Conference on Remote Sensing for Marine and Coastal Environments 25 – 27 . Ann Arbor, , USA Ann Arbor: Environmental Research Institute of Michigan
   Google Scholar
• Stumpf , R. P. , Culver , M. E. , Tester , P. A. , Tomlinson , M. , Kirkpatrick , G. J. , Pederson , B. A. , Truby , E. , Ransibrahmanakul , V. and Soracco , M. 2003 . Monitoring Karenia brevis blooms in the Gulf of Mexico using satellite ocean color imagery and other data . Harmful Algae , 2 : 147 – 160 .
   Web of Science ®Google Scholar
• Stumpf , R. P. , Litaker , R. W. , Lanerolle , L. and Tester , P. A. 2008 . Hydrodynamic accumulation of Karenia off the west coast of Florida . Continental Shelf Research , 28 : 189 – 213 .
   Web of Science ®Google Scholar
• Stumpf , R. P. and Tomlinson , M. C. 2005 . “ Remote sensing of harmful algal blooms ” . In Remote Sensing of Coastal Aquatic Environments , Edited by: Miller , R. L. , Del Castillo , C. E. and McKee , B. A. 277 – 296 . Dordrecht : Springer .
   Google Scholar
• Stumpf , R. P. and Tyler , M. A. 1988 . Satellite detection of bloom and pigment distributions in Estuaries . Remote Sensing of Environment , 24 : 385 – 404 .
   Web of Science ®Google Scholar
• Subramaniam , A. , Brown , C. W. , Hood , R. R. , Carpenter , E. J. and Capone , D. G. 2002 . Detecting Trichodesmium blooms in SeaWiFS imagery . Deep-Sea Research II , 49 : 107 – 121 .
   Web of Science ®Google Scholar
• Subramaniam , A. and Carpenter , E. J. 1994 . An empirically derived protocol for the detection of blooms of the marine cyanobacterium Trichodesmium using CZCS imagery . International Journal of Remote Sensing , 15 : 1559 – 1569 .
   Web of Science ®Google Scholar
• Subramaniam , A. , Carpenter , E. and Falkowski , P. G. 1999a . Bio-optical properties of the marine diazotrophic cyanobacteria Trichodesmium spp. II. A reflectance model for remote sensing . Limnology and Oceanography , 44 : 618 – 627 .
   Web of Science ®Google Scholar
• Subramaniam , A. , Carpenter , E. J. , Karentz , D. and Falkowski , P. G. 1999b . Bio-optical properties of the marine diazotrophic cyanobacteria Trichodesmium spp I. Absorption and photosynthetic action spectra . Limnology and Oceanography , 44 : 608 – 617 .
   Web of Science ®Google Scholar
• Svejkovsky , J. and Shandley , J. 2001 . Detection of offshore plankton blooms with AVHRR and SAR imagery . International Journal of Remote Sensing , 22 : 471 – 485 .
   Web of Science ®Google Scholar
• Tandeau de Marsac , N. and Houmard , J. 1988 . Complementary chromatic adaptation: physiological conditions and action spectra . Methods in enzymology , 167 : 318 – 328 .
   Web of Science ®Google Scholar
• Tang , D. L. , Di , B. P. , Wei , G. , Ni , I.-H.. , Oh , I. S. and Wang , S. F. 2006a . Spatial, seasonal and species variations of harmful algal blooms in the South Yellow Sea and East China Sea . Hydrobiologia , 568 : 245 – 253 .
   Web of Science ®Google Scholar
• Tang , D. L. , Kawamura , H. , Doan-Nhu , H. and Takahashi , W. 2004 . Remote sensing oceanography of a harmful algal bloom off the coast of southern Vietnam . Journal of Geophysical Research , 109 DOI: 10.1029/2003JC002045
   Web of Science ®Google Scholar
• Tang , D. L. , Kawamura , H. , Oh , I. S. and Baker , J. 2006b . Satellite evidence of harmful algal blooms and related oceanographic features in the Bohai Sea during autumn 1998 . Advances in Space Research , 37 : 681 – 689 .
   Web of Science ®Google Scholar
• Tassan , S. 1995 . SeaWiFS potential for remote sensing of marine Trichodesmium at sub-bloom concentration . International Journal of Remote Sensing , 16 : 3619 – 3627 .
   Web of Science ®Google Scholar
• Tomlinson , M. C. , Stumpf , R. P. , Ransibrahmanakul , V. , Truby , E. W. , Kirkpatrick , G. J , Pederson , B. A. , Vargo , G. A. and Heil , C. A. 2004 . Evaluation of the use of SeaWiFS imagery for detecting Karenia brevis harmful algal blooms in the eastern Gulf of Mexico . Remote Sensing of Environment , 91 : 293 – 303 .
   Web of Science ®Google Scholar
• Vahtera , E. , Conley , D. J. , Gustafsson , B. G. , Kuosa , H. , Pitkänen , H. , Savchuk , O. P. , Tamminen , T. , Viitasalo , M. , Voss , M. , Wasmund , N. and Wulff , F. 2007 . Internal ecosystem feedbacks enchance nitrogen-fixing cyanobacteria blooms and complicate management in the Baltic Sea . Ambio , 36 : 186 – 194 .
   PubMed Web of Science ®Google Scholar
• Vahtmäe , E. , Kutser , T. , Martin , G. and Kotta , J. 2006 . Feasibility of hyperspectral remote sensing for mapping benthic macroalgal cover in turbid coastal waters . Remote Sensing of Environment , 101 : 342 – 351 .
   Web of Science ®Google Scholar
• Vasilikov , A. and Kopelevich , O. 1982 . The reasons of maximum at about 700 nm on the radiance spectra of the sea . Oceanology , 22 : 945 – 950 .
   Google Scholar
• Vepsäläinen , J. , Pyhälahti , T. , Rantajärvi , E. , Kallio , K. , Pertola , S. , Stipa , T. , Kiiriki , M. , Pullianen , J. and Seppälä , J. 2005 . The combined use of optical remote sensiing data and unattended flow-through fluorometer measurements in the Baltic Sea . International Journal of Remote Sensing , 26 : 261 – 282 .
   Web of Science ®Google Scholar
• Vincent , R. K. , Qin , X. , McKay , R. M.L. , Miner , J. , Czajkowski , K. , Savino , J. and Bridgeman , T. 2004 . Phycocyanin detection from LANDSAT TM data for mapping cyanobacterial blooms in Lake Erie . Remote Sensing of Environment , 89 : 381 – 392 .
   Web of Science ®Google Scholar
• Wasmund , N. , Nausch , G. , Scneider , B. , Nagel , K. and Voss , M. 2005 . Comparison of nitrogen fixation rates determined with different methods: a study in the Baltic Proper . Marine Ecology Progress Series , 297 : 23 – 31 .
   Web of Science ®Google Scholar
• Westberry , T. K. , Siegel , D. A. and Subramaniam , A. 2005 . An improved bio-optical model for the remote sensing of Tricodesmium spp. blooms . Journal of Geophysical Research , 110 DOI: 10.1029/2004JC002517
   Web of Science ®Google Scholar
• Wrigley , R. C. and Horne , A. J. 1974 . Remote sensing and lake eutrophication . Nature , 250 : 213 – 214 .
   Web of Science ®Google Scholar
• Wynne , T. T. , Stumpf , R. P. , Tomlinson , M. C. , Ransibrahmanakul , V. and Villareal , T. R. 2005 . Detecting Karenia brevis blooms and algal resuspension in the western Gulf of Mexico with satellite ocean colour imagery . Harmful Algae , 4 : 992 – 1003 .
   Web of Science ®Google Scholar
• Yacobi , Y. Z. , Gitelson , A. and Mayo , M. 1995 . Remote sensing of chlorophyll in Lake Kinnert using high-spectral-resolution radiometer and Landsat TM: spectral features of reflectance and algorithm development . Journal of Plankton Research , 17 : 2155 – 2173 .
   Web of Science ®Google Scholar
• Yang , D. and Pan , D. 2006 . Hyperspectral retrieval model of phycocyanin in Case II waters . Chinese Science Bulletin , 51 : 149 – 153 .
   Google Scholar
• Zimba , P. V. and Gitelson , A. 2006 . Remote estimation of chlorophyll concentration in hyper-eutrophic aquatic systems: Model tuning and accuracy optimization . Aquaculture , 256 : 272 – 286 .
   Web of Science ®Google Scholar