Remote sensing of algal blooms: An overview with case studies

Journal of Coastal Research

Volumn 28, Issue 1 A, 2012, Pages 34-43

  Klemas, Victor ^a  

^a UNIVERSITY OF DELAWARE   (United States)

Author keywords

eutrophication; Harmful algal blooms; phytoplankton blooms; remote sensing

Indexed keywords

AGRICULTURAL PRACTICE; ALGAL BLOOM; AQUATIC PLANT; CONCENTRATION (COMPOSITION); EUTROPHIC ENVIRONMENT; EUTROPHICATION; FREQUENCY ANALYSIS; MAGNITUDE; NUTRIENT CYCLING; OXYGEN; PIGMENT; REMOTE SENSING; RUNOFF; SATELLITE IMAGERY; SPECTRAL REFLECTANCE; TOXIN; UPWELLING;

ALGAE; ANIMALIA;

EID: 84855393296     PISSN: 07490208     EISSN: 15515036     Source Type: Journal    
DOI: 10.2112/JCOASTRES-D-11-00051.1     Document Type: Review

References (97)

1. Anderson, D.M., 1994. Red tides. Scientific American, August 1994, pp. 52-58.
2. Anderson, D.M.; Hoagland, P.; Kaoru,Y., and White, A.W., 2000. Estimated annual economic impacts from harmful algal blooms (HAB's) in the United States. Woods Hole Oceanographic Institute Technical Report, WHOI-2000-11, 97p.
3. Backer, L.C. and Mc Gillicuddy, D.J., 2005. Harmful algal blooms at the interface between coastal oceanography and human health. Oceanography, 19, 94-106.
4. Barnes, R.A.; Clark, D.K.; Esaias, W.E.; Fargion, G.S.; Feldman, G.C., and Mc Clain, C.R., 2003. Development of a consistent multi-sensor global ocean color time series. International Journal of Remote Sensing, 24, 4047-4064. (Pubitemid 37317293)
5. Bissett, W.P.; Arnone, R.A.; Davis, C.O.; Dickey, T.D.; Dye, D.; Kohler, D.D.R., and Gould, R.W., Jr., 2004. From meters to kilometers: a look at ocean-color scales of variability, spatial coherence, and the need for fine-scale remote sensing in coastal ocean optics. Oceanography, 17(2), 32-43. (Pubitemid 39000228)
6. Boesch, D.F.; Boynton, W.R.; Crowder, L.B.; Diaz, R.J.; Howarth, R.W.; Mee, L.D.; Nixon, S.W.; Rabalais, N.N.; Rosenberg, R.; Sanders, J.G.; Scavia, D., and Turner, R.E., 2009. Nutrient enrichment drives Gulf of Mexico hypoxia. AGUEOS Transactions, 90, 117-118.
7. Burkholder, J.M.; Dickey, D.A.; Kinder, C.; Reed, R.E.; Mallin, M.A.; Melia, G.; Mc Iver, M.R.; Cahoon, L.B.; Brownie, C.; Deamer, N.; Springer, J.; Glasgow, H.; Toms, D., and Smith, J., 2006. Comprehensive trend analysis of nutrients and related variables in a large eutrophic estuary: a decadal study of anthropogenic and climatic influences, Limnology and Oceanography, 51, 463-487. (Pubitemid 43259734)
8. Burkholder, J.M. and Glasgow, H.B., 1997. Pfiesteria piscicida and other Pfiesteria-like dinoflagellates: behavior, impacts and Environmental controls, Limnology and Oceanography, 42, 1052-1075.
9. Cannizzaro, J.P. and Carder, K.L., 2006. Estimating chlorophyll-a concentrations from remote sensing reflectance in optically shallow waters. Remote Sensing of Environment, 101, 13-24. (Pubitemid 43290231)
10. Chang, C.; Mahoney, K.; Briggs-Whitmire, A.; Kohler, D.D.R.; Mobley, C.D.; Lewis, M.; Moline, M.A.; Boss, E.; Kim, M.; Philpot, D., and Dickey, T.D., 2004. The new age of hyperspectral oceanography. Oceanography, 17, 16-23. (Pubitemid 39000226)
11. Cullen, J.J.; Ciotti, A.M.; Davis, A.F., and Lewis, M.R., 1997. Optical detection and assessment of algal blooms. Limnology and Ocean-ography, 42(5, part 2), 1223-1229.
12. Dzwonkowski, B. and Yan, X.-H., 2005. Tracking ofa Chesapeake Bay estuarine outflow plume with satellite-based ocean color data. Continental Shelf Research, 25, 1942-1958. (Pubitemid 41414618)
13. Franz, B.A.; Werdell, P.J.; Meister, G.; Bailey, S.W.; Eplee, R.E., Jr.; Feldman, G.C.; Kwiatkowska, E.; Mc Clain, C.R.; Patt, F.S., and Thomas, D., 2005. The continuity of ocean color measurements from Sea Wi FS to MODIS. In: Butler, J.J. (ed.), Earth Observing Systems X (August 22, 2005, SPIE), Volume 5882, pp. 1-14.
14. 2 and temperature effects on sympatric Heterosigma akashiwo and Prorocentrum minimum. Harmful Algae, 7, 76-90. (Pubitemid 350088633)
15. Glibert, P.M. and Burkholder, J.M., 2006. The complex relationships between increasing fertilization of the earth, coastal eutrophication and proliferation of harmful algal blooms. In: E. Granéli and J. Turner, Editors, Ecology of Harmful Algae, Springer, pp. 341-354.
16. Glibert, P.M.; Magnien, R.; Lomas, M.W.; Alexander, J.; Fan, C.; Haramoto, E.; Trice, M., and Kana, T.M., 2001. Harmful algal blooms in the Chesapeake and Coastal Bays of Maryland, USA: comparisons of 1997,1998, and 1999 events. Estuaries, 24, 875-883.
17. Glibert, P.M.; Seitzinger, S.; Heil, C.A.; Burkholder, J.M.; Parrow, M.W.; Codispoti, L.A., and Kelly, V., 2005. The role ofeutrophica-tion in the global proliferation of harmful algal blooms, Oceanog-raphy, 18, 198-209. (Pubitemid 40881914)
18. Gilerson, A.A.; Gitelson, A.A.; Zhou, J.; Gurlin, D.; Moses, W.J.; Ioannou, I., and Ahmed, S.A., 2010. Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near-infrared bands. Optics Express, 18, 24109-24125.
19. Gitelson, A., 1993. Quantitative remote sensing methods for real-time monitoring of inland water quality. International Journal of Remote Sensing, 14, 1269-1295.
20. Gitelson, A.A. and Kondratyev, K.Y., 1991. Remote chlorophyll-a retrieval in turbid, productive estuaries: Chesapeake Bay case study. Remote Sensing of Environment, 109, 464-472.
21. Gitelson, A.A.; Yacobi, Y.Z.; Schalles, J.F.; Rundquist, D.C.; Han, L.; Stark, R., and Etzion, D., 2000. Remote estimation ofphytoplank-ton density in productive waters. Archive of Hydrobiology, Special issue on Advanced Limnology, 55, 121-136.
22. Gobler, C.J.; Lonsdale, D.J., and Boyer, G.L., 2005. A synthesis and review of causes and impact ofharmful brown tide blooms caused by the alga, Aureococcus anophagefferens, Estuaries, 28, 726-749.
23. Gons, H.; Hakvoort, H.; Steef, P., and Simis, S., 2005. Optical detection of cyanobacterial blooms: shipboard observation and remote sensing. In: Huisman, J.; Matthijs, H.C.P., and Visser, P.M. (eds.), Harmful Cyanobacteria, Aquatic Ecology Series volume 3. Dordrecht, the Netherlands: Springer, pp. 177-199.
24. Gower, J.F.R., 2004. Sea Wi FS global composite images show significant features of Canadian waters for 1997-2001. The Canadian Journal of Remote Sensing, 30, 26-35.
25. Gower, J.F.R.; Brown, L., and Borstad, G.A., 2004. Observation of chlorophyll fluorescence in west coast waters of Canada using the MODIS satellite sensor. The Canadian Journal of Remote Sensing, 30, 17-25.
26. Hallegraeff, G.M., 1993. A review of harmful algal blooms and their apparent global increase. Phycologia, 32, 79-99. (Pubitemid 24410302)
27. Hick, P. and Jernakoff, P., 1994. Algal bloom research using CASI data in Western Australia. In: Proceedings of the 7th Australasian Conference on Remote Sensing (Melbourne, Australia), pp. 736-744.
28. Hick, P.; Ong, C.; Smith, R.C.G., and Honey, F.R., 1994. Vegetation assessment and monitoring using airborne digital multispectral videography: implications for geobotanical prospecting and quan-titative pre- and post-mining measurement. In: Proceedings of the 19th Environmental Workshop of the Australian Mining Industry Council (city, state/country), pp. 178-195.
29. Hojerslev, N.K., 1980. Water color and its relation to primary production. Boundary-Layer Meteorology, 18, 203-220.
30. Hooker, S.B. and Esaias, W.E., 1993. An overview of the Sea Wi FS project. AGU EOS Transactions, 74, 241-246.
31. Jensen, J.R., 2007. Remote Sensing of the Environment: An Earth Resource Perspective. Upper Saddle River, New Jersey: Prentice Hall.
32. Jernakoff, P.; Hick, P.; Ong, C.; Hosja, W., and Grigo, S., 1996. Mapping algal blooms using airborne digital multispectral video and the importance of bloom dynamics in the collection of in-water data. Marine Technology Society Journal, 30, 36-45. (Pubitemid 27411654)
33. Jochens, T.T.; Malone, T.C.; Stumpf, R.P.; Hickey, B.M.; Carter, M.; Morrison, R.; Dyble, J.; Jones, B., and Trainer, V.L., 2010. Integrated ocean observing system in support of forecasting harmful algal blooms. Marine Technology Society Journal, 44, 99-121.
34. Kabbara, N.; Benkhelil, J.; Awad, M., and Barale, V., 2008. Monitoring water quality in the coastal area of Tripoli (Lebanon) using high-resolution satellite data. ISPRS Journal of Photogram-metry and Remote Sensing, 63, 488-495.
35. Kahru, M. and Mitchell, B.G., 2008. Ocean color reveals increased blooms in various parts of the world. AGU EOS Transactions, 89,170.
36. Kahru, M.; Savchuk, O.P., and Elmgren, R., 2007. Satellite measure-ments of cyanobacterial bloom frequency in the Baltic Sea: interannual and spatial variability. Marine Ecology Progress Series, 343, 15-23. (Pubitemid 47359779)
37. Keafer, B.A. and Anderson, D.M., 1993. Use of remotely-sensed sea surface temperatures in studies of Alexandrium tamarense bloom dynamics. In: Smayda, T.M. and Shimizu, Y. (eds.), Toxic Phytoplankton Blooms in the Sea. Proceedings of the 5th Interna-tional Conference on Toxic Marine Phytoplankton. Amsterdam: Elsevier, pp. 763-768.
38. Keith, D.J., 2010. Estimating chlorophyll conditions in southern New England coastal waters from hyperspectral remote sensing. In: Wang, Y. (ed.), Remote Sensing of Coastal Environments. Boca Raton, Florida: CRC Press, pp. 151-172.
39. Kirk, J.T.O., 2000. Light and Photosynthesis in Aquatic Ecosystems. Cambridge, England: Cambridge University Press, 509p.
40. Klemas, V., 2009. Sensors and techniques for observing coastal ecosystems. In: Yang, X. (ed.), Remote Sensing and Geospatial Technologies for Coastal Ecosystem Assessment and Management. Berlin: Springer-Verlag, pp. 17-44.
41. Klemas, V., 2011a. Remote sensing techniques for studying coastal ecosystems. Journal of Coastal Research, 27, 1-16.
42. Klemas, V., 2011b. Remote sensing ofcoastal plumes and ocean fronts: overview and case study. Journal of Coastal Research. In press.
43. Klemas, V. and Philpot, W., 1981. Drift and dispersion studies of ocean-dumped waste using Landsat imagery and current drogues. Photogrammetric Engineering and Remote Sensing, 47, 533-542. (Pubitemid 11500892)
44. Kutser, T., 2004. Quantitative detection of chlorophyll in cyanobac- terial blooms by satellite remote sensing. Limnology and Oceanography, 49, 2179-2189. (Pubitemid 39547891)
45. Kutser, T., 2009. Passive optical remote sensing of cyanobacteria blooms in coastal and inland waters. International Journal of Remote Sensing, 30, 3069-3085.
46. Landsberg J.H., 2002. The effects ofharmful algal blooms on aquatic organisms. Reviews in Fisheries Science 10, 113-390. (Pubitemid 41478755)
47. 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. (Pubitemid 32161285)
48. Longhurst, A.; Sathyendranat, S.; Platt, T., and Caverhill, C., 1995. An estimate ofglobal primary production in the ocean from satellite radiometer data. Journal of Plankton Research, 17, 1245-1271. (Pubitemid 26437016)
49. Lyon, R.J.P.; Honey, F.R., and Hick, P.T., 1994. Second generation airborne digital multispectral video: evaluation of a DMSV for environmental and vegetation assessment. In: Proceedings of the First International Airborne Remote Sensing Conference (Stras- bourg, France), pp. 105-116.
50. Martin, S., 2004. An Introduction to Remote Sensing. Cambridge, England: Cambridge University Press.
51. Mc Clain, C.; Hooker, S.; Feldman, G., and Bontempi, P., 2006. Satellite data for ocean biology, biogeochemistry, and climate research. AGU EOS Transactions, 87, 337-343.
52. Miller, P.I.; Shutler, J.D.; Moore, G.F., and Groom, S.B., 2006. Sea Wi FS discrimination of harmful algal bloom evolution. International Journal of Remote Sensing, 27, 2287-2301.
53. Moita, M.T.; Oliveria, P.B.; Mendes, J.C., and Palma, A.S., 2003.Distribution of chlorophyll-a and Gymnodinium catenatum associated with coastal upwelling plumes off central Portugal. International Journal of Ecology, 24, S125-S132. (Pubitemid 36726203)
54. Montes-Hugo, M.A.; Carder, K.; Foy, R.J.; Cannizzaro, J.; Brown, E., and Pegau, S., 2005. Estimating phytoplankton biomass in coastal waters of Alaska using airborne remote sensing. Remote Sensing of the Environment, 98, 481-493. (Pubitemid 41484105)
55. Morel, A., and Gordon, H.R., 1980. Report of the working group on water color. Boundary-Layer Meteorology, 18, 343-355.
56. Morel, A. and Prieur, L., 1997. Analysis of variation in ocean color. Limnology and Oceanography, 22, 709-722.
57. Namin, K.S.; Risk, M.J.; Hoeksema, B.W.; Zohari, Z., and Rezai, H., 2010. Coral mortality and serpulid infestations associated with red tide in the Persian Gulf. Coral Reefs, 29, 509.
58. NOAA (National Oceanic and Atmospheric Administration), 2006. Monitoring harmful algae. http://www.csc.noaa.gov/crs/rs-apps/ issues/seawifs-hab.htm (accessed April 20, 2007).
59. Paerl, H.W. and Huisman, J., 2008. Blooms like it hot. Science, 320, 57-58.
60. Philpot, W., 2007. Estimating atmospheric transmission and surface reflectance from a glint-contaminated spectral image. IEEE Transactions on Geoscience and Remote Sensing, 45, 448-457. (Pubitemid 46183040)
61. Pinet, P.R., 2009. Invitation to Oceanography, 5th edition. Sudbury, Massassachusetts: Jones and Bartlett.
62. Pitcher, G.C.; Boyd, A.D.; Horstman, D.A., and Mitchell-Innes, B.A., 1998. Subsurface dinoflagellate populations, frontalblooms and the formation of red tide in the southern Benguela upwelling system. Marine Ecology Progress Series, 172, 253-264. (Pubitemid 28504233)
63. Purkis, S. and Klemas, V., 2011. Remote Sensing and Global Environmental Change. Oxford: Wiley-Blackwell.
64. Reinart, A. and Kutser, T., 2006. Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea. Remote Sensing of the Environment, 102, 74-85.
65. Robinson, I.S., 2004. Measuring the Ocean from Space: The Principles and Methods of Satellite Oceanography. Berlin: Springer-Verlag.
66. Roelfsema, C.M.; Phinn, S.R.; Dennison, W.C.; Decker, A.G., and Brando, V.E., 2006. Monitoring toxic cyanobacteria Lyngbya majuscule (Gomont) in Moreton Bay, Australia by integrating satellite image data and field mapping. Harmful Algae, 5, 45-56. (Pubitemid 41814798)
67. Ruddick, K.G., 2001. Optical remote sensing of chlorophyll-a in case 2 waters by use of an adaptive two-band algorithm with optimal error properties. Applied Optics, 40, 3575-3585.
68. Schalles, J.F.; Gitelson, A.A.; Yacoby, Y.Z., and Kroenke, A.E., 1998. Estimation of chlorophyll-a from time series measurements ofhigh spectral resolution reflectance in an eutrophic lake. Journal of Phycology, 34, 383-390. (Pubitemid 28209524)
69. Schofield, O.; Arnone, R.A.; Bissett, W.P.; Dickey, T.D.; Davis, C.O.; Finkel, Z.; Oliver, M., and Moline, M.A., 2003. Watercolors in the coastal zone: what can we see? Oceanography, 17, 24-31.
70. Schofield, O.; Gryzmski, J.; Bissett, P.; Kirkpatrick, G.; Millie, D.F.; Moline, M.A., and Roesler, C., 1999. Optical monitoring and forecasting systems for harmful algal blooms: possibility or pipe dream? Journal of Phycology, 35, 125-145.
71. Service, R.F., 2004. New dead zone off Oregon coast hints at sea change in currents. Science, 305, 1099. (Pubitemid 39100299)
72. Shields, E. and Weidman, C., 2008. A quantitative approach to characterizing hypoxic events. Journal of Coastal Research, 55, 50-58.
73. Shumway, S.E., 1990. A review of the effects of algal blooms on shellfish and aquaculture. Journal of the World Aquaculture Society, 21, 65-104.
74. 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. (Pubitemid 40199043)
75. Smith, V.H., 2006. Responses of estuarine and coastal marine phytoplankton to nitrogen and phosphorus enrichment. Limnology and Oceanography, 51, 377-384. (Pubitemid 43259728)
76. Springer, J.J.; Burkholder, J.M.; Glasgow, H.B.; Glibert, P.M., and Reed, R.E., 2005. Use of a real-time monitoring network (RTRM) and shipboard sampling to characterize a dinoflagellate bloom in the Neuse Estuary, North Carolina, U.S.A., Harmful Algae, 4, 553-574.
77. Stramski, D. and Reynolds, R.A., 1993. Diel variations in the optical properties of a marine diatom. Limnology and Oceanography, 38, 1347-1364.
78. Stumpf, R.P., 2001. Applications of satellite ocean color sensors for monitoring and predicting harmful algal blooms. Human and Ecological Risk Assessment, 7, 1363-1368.
79. Stumpf, R.P.; Culver, M.E.; Tester, P.A.; Kirkpatrick, G.J.; Pederson, B.; Tomlinson, M.C.; Truby, E.; Ransibrahmanakul, V.; Hughes, K., and Soracco, M., 2003. Use of satellite imagery and other data for monitoring Karenia brevis blooms in the Gulf of Mexico. Harmful Algae, 2, 147-160. (Pubitemid 37379199)
80. Stumpf, R.P. and Tomlinson, M.C., 2005. Remote sensing ofharmful algal blooms. In: Miller, R.; del Castillo, C., and Mc Kee, B. (eds.), Remote Sensing of Coastal Aquatic Environments: Technologies, Techniques and Applications. Dordrecht, the Netherlands: Kluwer Academic Publishers, pp. 277-292.
81. Stumpf, R.P.; Tomlinson, M.C.; Calkins, J.A.; Kirkpatrick, B.; Nierenberg, K.; Currier, R., and Wynne, T.T., 2009. Skill Assessment for an operational algal bloom forecast system. Journal of Marine Systems, Special issue on Skill Assessment of Ecological Oceanographic Models, 76, 151-161.
82. Szekielda, K.H.; Bowles, J.H.; Gillis, D.B., and Miller, W.D., 2009. Interpretation of absorption bands in airborne hyperspectral radiance data. Sensors, 9, 2907-2925.
83. Szekielda, K.-H.; Bowles, J.H.; Gillis, D.B.; Snyder, W., and Miller, W.D., 2010. Patch recognition of algal blooms and macroalgae. In: Hou, W. and Arnone, R.A., (eds), Ocean Sensing and Monitoring II, SPIE, Volume 7678, pp. 1-9.
84. Szekielda, K.-H.; Gobler, C.; Gross, B.; Moshary, F., and Ahmed, S., 2003. Spectral reflectance measurements of estuarine waters. Ocean Dynamics, 53, 98-102. (Pubitemid 36770245)
85. Tester, P.A.; Stumpf, R.P.; Vukovich, F.M.; Fowler, P.K., and Turner, J.F., 1991. An expatriate red tide bloom: transport, distribution and persistence. Limnology and Oceanography, 36, 1053-1061. (Pubitemid 23395308)
86. Tester, P.A. and Stumpf, R.P., 1998. Phytoplankton blooms and remote sensing: what is the potential for early warning? Journal of Shellfish Research, 17, 1469-1471. (Pubitemid 29221165)
87. Thomas, A.C. and Weatherbee, R.A., 2006. Satellite-measured temporal variability of the Columbia River plume. Remote Sensing ofthe Environment, 100, 167-178. (Pubitemid 43083567)
88. 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 Sea Wi FS imagery for detecting Karenia brevis harmful algal blooms in the eastern Gulf of Mexico. Remote Sensing of the Environment, 91, 293-303. (Pubitemid 38791549)
89. Tomlinson, M.C.; Stumpf, R.P., and Wynne, T.T., 2009. An evaluation of remote sensing techniques for enhanced detection of the toxic dinoflagellate, Karenia brevis, in the Gulf of Mexico. Remote Sensing of the Environment, 113, 598-609.
90. Turner, R.E. and Rabalais, N.N., 1994. Coastal eutrophication near the Mississippi river delta. Nature, 368, 619-621. (Pubitemid 24154380)
91. Wang, M., 2007. Remote sensing of the ocean contributions from ultraviolet to near-infrared using the shortwave infrared bands: simulations. Applied Optics, 46, 1535-1547. (Pubitemid 46659391)
92. Wang, M. and Shi, W., 2008. Satellite-observed algae blooms in China's Lake Taihu. AGU EOS Transactions, 89, 201-202.
93. Wang, S.; Tang, D.; He, F.; Fukuyo, Y., and Azanza, R.V., 2008. Occurrences ofharmful algal blooms (HABs) associated with ocean environments in the South China Sea. Hydrobiology, 596, 79-93.
94. Wang, Y., 2010. Remote Sensing of Coastal Environments. Boca Raton, Florida: CRC Press.
95. Wynne, T.T.; Stumpf, R.P.; Tomlinson, M.C., and Dyble, J., 2010. Characterizing a cyanobacterial bloom in western Lake Erie using satellite imagery and meteorological data. Limnology and Ocean- ography, 55, 2025-2036.
96. Yang, X., 2009. Remote Sensing and Geospatial Technologies for Coastal Ecosystem Assessmentand Management. Berlin: Springer-Verlag.
97. Zibordi, G.; Parmiggiani, F., and Alberotanza, L., 1990. Application of aircraft multispectral scanner data to algae mapping over the Venice Lagoon. Remote Sensing of the Environment, 34, 49-54.