From Cells to the Ocean: Satellite Ocean Color

  • M. R. Lewis
  • J. J. Cullen
Part of the NATO ASI Series book series (volume 27)


Variations in the color of the ocean as seen from space are principally due to variations in the concentration and optical properties of biogenic materials, dissolved and particulate, in the upper ocean. From 1978 to 1986 the NIMBUS-7 Coastal Zone Color Scanner observed these variations over the global ocean; the wealth of data that has resulted is just now being appreciated. The resultant ability to observe the ocean from a biological perspective over synoptic scales revolutionized the field.

The satellite observations require algorithms to interpret the received signal in terms of meaningful geophysical quantities or processes. Most of the signal results from the atmosphere and corrections to permit analysis of the ocean signal is non-trivial. Assuming that this can be done with acceptable accuracy, it is still necessary to relate the observations of radiance leaving the surface of the ocean to more useful variables such as the concentration of chlorophyll in the sea surface or the primary productivity of the ocean. The link between the observations and the desired retrieval are the so-called bio-optical algorithms.

The relationship between water-leaving radiance and chlorophyll in the water column is not simple because most of the chlorophyll is contained within phytoplankton particles of varying dimension and with varying internal concentration of chlorophyll. The presence of ancillary and detrital pigments, in addition to chlorophyll, and the presence of non-chlorophyllous particles further complicate the issue. Two approaches to the bio-optical algorithms have been taken to resolve these problems. The first attempts to describe empirically the variability in particle size and composition in terms of coefficients of statistical relationships between water-leaving radiance and chlorophyll concentration. Primary production is described in a similar fashion. The second, not mutually exclusive, relies on first principles of radiative transfer and the physiology of phytoplankton coupled with a detailed understanding of the nature and size distribution of the particle population and their optical properties. One of the challenges of the latter path is to reproduce the water-leaving signal given the solar input and detailed knowledge of the particle population from analysis of individual cells. The inverse problem, infering the individual cell characteristics from the water-leaving radiance signal, is equally or more challenging.

Here, the bases for the remote measurement of ocean color from space, and the algorithms used in the estimation of chlorophyll concentration and primary productivity from these remote measurements will be discussed with a view towards interpretation based on the characteristics of the ensemble of individual particles in the upper ocean.


Attenuation Coefficient Dissolve Organic Matter Chlorophyll Concentration Ocean Color Remote Measurement 
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  1. Ackleson S, Balch WM, Holligan PM (1988) White waters of the Gulf of Maine. Oceangr 1:18–22Google Scholar
  2. Ackleson SG, Spinrad RW (1988) Size and refractive index of individual marine particulates: a flow cytometric approach Appl Optics 27:1270–1277CrossRefGoogle Scholar
  3. Ackleson SG, Spinrad RW, Yentsch CM, Brown J, Korjeff-Bellows W (1988) Phytoplankton optical properties: flow cytometric examinations of dilution-induced effects. Appl Optics 27:1262–1269CrossRefGoogle Scholar
  4. André JM, Morel A (1989) Simulated effects of barometric pressure and ozone content upon the estimate of marine phytoplankton from space. J Geophys Res 94:1029–1037CrossRefGoogle Scholar
  5. Austin RW, Petzold TJ (1981) Remote sensing of the diffuse attenuation coefficient of sea water using the coastal zone color scanner, in Oceangraphy from Space, JRF Gower (ed.) pp 239–256. Plenum NYGoogle Scholar
  6. Balch WM, Abbott MR, Eppley RW (1989) Remote sensing of primary production-I. A comparison of empirical and semi-analytical algorithms. Deep Sea Res 36:281–295CrossRefGoogle Scholar
  7. Baker K, Smith RC (1979) quasi-inherent characteristics of the diffuse attenuation coefficient for irradiance. SPIE 208:60–63.Google Scholar
  8. Bricaud A, Morel A (1986) Light attenuation and scattering by phytoplanktonic cells: a theoretical modeling. Applied Optics 25:571–580CrossRefGoogle Scholar
  9. Bricaud A, Morel A, Prieur L (1983) Optical efficiency factors of some phytoplankters. Limnol and Oceanogr 28:816–832CrossRefGoogle Scholar
  10. Bricaud A, Morel A (1987) Atmospheric corrections and interpretation of marine radiances in CZCS imagery: Use of a reflectance model. Oceanol Acta 7:33–50Google Scholar
  11. Brown OB, Evans RH, Brown JW, Gordon HR, Smith RC, Baker KS. Phytoplankton blooming off the U.S. East Coast: A satellite description. Science 229:163–167Google Scholar
  12. Denman KL (1973) A time-dependent model of the upper ocean. J Phys Oceangr 3:173–184.CrossRefGoogle Scholar
  13. Eppley RW, Stewart E, Abbott MR, Heyman U (1985) Estimating ocean primary production from satellite chlorophyll. Introduction to regional differences and statisitics for the Southern California Bight. J Plankton Res 7:57–70.CrossRefGoogle Scholar
  14. Gordon HR (1978) Removal of atmospheric effects from satellite imagery of the oceans. Appl Opt 17:1631–1636.CrossRefGoogle Scholar
  15. Gordon HR (1986) Ocean color remote sensing: Influence of the particle phase function and the solar zenith angle. EOS Trans AGU 14:1055Google Scholar
  16. Gordon HR (1988) Ocean color remote sensing systems: Radiometric requirements. SPIE 924:151–167.Google Scholar
  17. Gordon HR, Morel AY (1983) Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery: A Review. Springer-Verlag, NY 114 ppGoogle Scholar
  18. Gordon HR, Brown J, Evans RH (1988) Exact Rayleigh scattering calculations for use with the Nimbus-7 Coastal Zone Color Scanner. Appl Opt 27:862–871CrossRefGoogle Scholar
  19. Gordon HR, Brown OB, Jacobs MM (1975) Computed relationships between the inherent and apparent optical properties of a flat homogeneous ocean. Appl Opt 14:417–427CrossRefGoogle Scholar
  20. Gordon HR, Clark DK, Mueller JL, Hovis WA (1980) Phytoplankton pigments derived from the Nimbus 7 CZCS: Initial comparisons with surface measurements. Science 210:63–66CrossRefGoogle Scholar
  21. Gordon HR, Brown OB, Evans RH, Brown JW, Smith RC, Baker KS, Clark DK (1988) A semianalytic radiance model of ocean color. J Geophys Res 93:10909–10924CrossRefGoogle Scholar
  22. Gower JFR, Borstad G (1981) Use of the in-vivo fluorescence line at 685 nm for remote sensing surveys of surface chlorophyll a. In, J.F.R. Gower (ed.) Oceanography from Space. Plenum Press, NY pp 281–294Google Scholar
  23. Kirk JTO (1983) Light and photosynthesis in aquatic ecosystems. Cambridge University Press, NY 401pp.Google Scholar
  24. Kitchen JC, Zaneveld JRV (1990) On the noncorrelation of the vertical structure of light scattering and chlorophyll a in Case I waters. J Geophys Res 95:20237–20246CrossRefGoogle Scholar
  25. Kuring N, Lewis MR, Platt T, O’Reilly JF (1990) Satellite-derived estimates of primary production in the Northwestern Atlantic. Cont Shelf Res 10:461–484CrossRefGoogle Scholar
  26. Lewis MR, Cullen JJ, Platt T. Phytoplankton and thermal structure in the upper ocean: consequences of nonuniformity in chlorophyll profile. J Geophys Res 88:2565–2570Google Scholar
  27. Lewis MR (1987) Phytoplankton and thermal structure in the tropical ocean. Oceanol Acta SP:91–95.Google Scholar
  28. Lewis MR, Carr ME, Feldman GC, Esaias W, McClain C (1990) Influence of penetrating solar radiation on the heat budget of the equatorial Pacific Ocean. Nature 347:543–545CrossRefGoogle Scholar
  29. Morel A (1980) In water and remote measurement of ocean color. Boundary Layer Meteorol 18:177–201CrossRefGoogle Scholar
  30. Morel A (1987) Chlorophyll-specific scattering coefficient of phytoplankton. A simplified theoretical approach. Deep Sea Res 34:1093–1105CrossRefGoogle Scholar
  31. Morel A (1988) Optical modeling of the upper ocean in relations to its biogenous matter content (Case I waters. J Geophys Res 93:10747–10768CrossRefGoogle Scholar
  32. Morel A, Prieur L (1977) Analysis of variations in ocean color. Limnol Oceangr 22:709–722.CrossRefGoogle Scholar
  33. Platt T (1986) Primary production of the ocean water column as a function of surface light intensity: algorithms for remote sensing. Deep-Sea Res 33:149–163CrossRefGoogle Scholar
  34. Platt T, Lewis MR (1987) Estimation of phytoplankton production by remote sensing. Adv Space Res 7:131–135CrossRefGoogle Scholar
  35. Platt T, Sathyendranath S, Caverhill CM, Lewis MR (1988) Ocean primary production and available light: further algorithms for remote sensing. Deep Sea Res 35:855–879CrossRefGoogle Scholar
  36. Prieur L, Sathyendranath S (1981) An optical classification of coastal and oceanic waters based on the specific absorption curves of phytoplankton pigments, dissolved organic matter and other particulate materials. Limnol Oceangr 26:671–689CrossRefGoogle Scholar
  37. Sathyendranath S (1981) Influence des substances en solution et en suspension dans les eaux de mer sur l’absorption et la reflectance. Modelisation et applications a la teledetection. PhD Thesis, 3rd cycle Univ Pierre et Marie Curie, Paris 123 ppGoogle Scholar
  38. Yentsch CS (1962) Measurement of visible light absorption by particulate matter in the ocean. Limnol Oceangr 7:207–217CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • M. R. Lewis
    • 1
  • J. J. Cullen
    • 2
  1. 1.Department of OceanographyDalhousie UniversityHalifaxCanada
  2. 2.Bigelow LaboratoryWest Boothbay HarborUSA

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