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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 6, Iss. 8 — Aug. 26, 2011

Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS

Ioannis Ioannou, Alexander Gilerson, Barry Gross, Fred Moshary, and Samir Ahmed  »View Author Affiliations


Applied Optics, Vol. 50, Issue 19, pp. 3168-3186 (2011)
http://dx.doi.org/10.1364/AO.50.003168


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Abstract

Retrieving the inherent optical properties of water from remote sensing multispectral reflectance measurements is difficult due to both the complex nature of the forward modeling and the inherent nonlinearity of the inverse problem. In such cases, neural network (NN) techniques have a long history in inverting complex nonlinear systems. The process we adopt utilizes two NNs in parallel. The first NN is used to relate the remote sensing reflectance at available MODIS-visible wavelengths (except the 678 nm fluorescence channel) to the absorption and backscatter coefficients at 442 nm (peak of chlorophyll absorption). The second NN separates algal and nonalgal absorption components, outputting the ratio of algal-to-nonalgal absorption. The resulting synthetically trained algorithm is tested using both the NASA Bio-Optical Marine Algorithm Data Set (NOMAD), as well as our own field datasets from the Chesapeake Bay and Long Island Sound, New York. Very good agreement is obtained, with R 2 values of 93.75%, 90.67%, and 86.43% for the total, algal, and nonalgal absorption, respectively, for the NOMAD. For our field data, which cover absorbing waters up to about 6 m 1 , R 2 is 91.87% for the total measured absorption.

© 2011 Optical Society of America

OCIS Codes
(010.4450) Atmospheric and oceanic optics : Oceanic optics
(280.0280) Remote sensing and sensors : Remote sensing and sensors
(010.4455) Atmospheric and oceanic optics : Oceanic propagation
(010.4458) Atmospheric and oceanic optics : Oceanic scattering
(010.5620) Atmospheric and oceanic optics : Radiative transfer
(010.0280) Atmospheric and oceanic optics : Remote sensing and sensors

ToC Category:
Atmospheric and Oceanic Optics

History
Original Manuscript: December 3, 2010
Revised Manuscript: February 10, 2011
Manuscript Accepted: March 19, 2011
Published: June 23, 2011

Virtual Issues
Vol. 6, Iss. 8 Virtual Journal for Biomedical Optics

Citation
Ioannis Ioannou, Alexander Gilerson, Barry Gross, Fred Moshary, and Samir Ahmed, "Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS," Appl. Opt. 50, 3168-3186 (2011)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ao-50-19-3168


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References

  1. H. R. Gordon and A. Morel, “Remote assessment of ocean color for interpretation of satellite visible imagery: a review,” R.T.Barber, C.N. K.Mooers, M.J.Bowman, and B.Zeitzschel, eds. (Springer-Verlag, 1983).
  2. J. E. Tyler and R. W. Preisendorfer, The Sea, Vol. 2, M.N.Hill, ed. (Interscience, 1962).
  3. R. W. Preisendorfer, “Hydrologic optics” (U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, 1976).
  4. A. Morel and L. Prieur, “Analysis of variations in ocean color,” Limnol. Oceanogr. 22, 709–722 (1977). [CrossRef]
  5. R. W. Austin and T. J. Petzold, “The determination of the diffuse attenuation coefficient of sea water using the coastal zone color scanner,” in Oceanography from Space, J.F. R.Gower, ed. (Plenum, 1981). [CrossRef]
  6. H. R. Gordon, D. K. Clark, J. W. Brown, O. B. Brown, R. H. Evans, and W. W. Broenkow, “Phytoplankton pigment concentrations in the Middle Atlantic Bight: comparison of ship determinations and CZCS estimates,” Appl. Opt. 22, 20–36(1983). [CrossRef] [PubMed]
  7. Z. P. Lee, K. L. Carder, R. G. Steward, T. G. Peacock, C. O. Davis, and J. S. Patch, “An empirical algorithm for light absorption by ocean water based on color,” J. Geophys. Res. 103, 27967–27978 (1998). [CrossRef]
  8. S. Sathyendranath, F. E. Hoge, T. Platt, and R. N. Swift, “Detection of phytoplankton pigments from ocean color: improved algorithms,” Appl. Opt. 33, 1081–1089 (1994). [CrossRef] [PubMed]
  9. J. O’Reilly, S. Maritorena, B. G. Mitchell, D. Siegel, K. L. Carder, S. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. 103, 24937–24953 (1998). [CrossRef]
  10. H. Loisel, D. Stramski, B. G. Mitchell, F. Fell, V. Fournier-Sicre, B. Lemasle, and M. Babin, “Comparison of the ocean inherent optical properties obtained from measurements and inverse modeling,” Appl. Opt. 40, 2384–2397 (2001). [CrossRef]
  11. M. Sydor, R. Arnone, R. W. Gould, G. E. Terrie, S. D. Ladner, and C. G. Wood, “Remote-sensing technique for determination of the volume absorption coefficient of turbid water,” Appl. Opt. 37, 4944–4950 (1998). [CrossRef]
  12. C. S. Roesler and M. J. Perry, “In situ phytoplankton absorption, fluorescence emission, and particulate backscattering spectra determined from reflectance,” J. Geophys. Res. 100, 13279–13294 (1995). [CrossRef]
  13. F. E. Hoge and P. E. Lyon, “Satellite retrieval of inherent optical properties by linear matrix inversion of oceanic radiance models: an analysis of model and radiance measurement errors,” J. Geophys. Res. 101, 16631–16648 (1996). [CrossRef]
  14. A. H. Garver and D. A. Siegel, “Inherent optical property inversion of ocean color spectra and its biogeochemical interpretation. 1. time series from the Sargasso Sea,” J. Geophys. Res. 102, 18607–18625 (1997). [CrossRef]
  15. K. L. Carder, F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski, “Semianalytic moderate-resolution imaging spectrometer algorithms for chlorophyll-a and absorption with bio-optical domains based on nitrate-depletion temperatures,” J. Geophys. Res. 104, 5403–5421 (1999). [CrossRef]
  16. P. Wang, E. S. Boss, and C. Roesler, “Uncertainties of inherent optical properties obtained from semianalytical inversions of ocean color,” Appl. Opt. 44, 4074–4085 (2005). [CrossRef] [PubMed]
  17. Z. P. Lee, K. L. Carder, and R. A. Armone, “Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters,” Appl. Opt. 41, 5755–5772 (2002). [CrossRef] [PubMed]
  18. Z. P. Lee and K. L. Carder, “Absorption spectrum of phytoplankton pigments derived from hyperspectral remote-sensing reflectance,” Remote Sens. Environ. 89, 361–368 (2004). [CrossRef]
  19. Z. P. Lee, http://www.ioccg.org/groups/Software_OCA/QAA_v5.pdf.
  20. F. Aires, C. Prigent, W. B. Rossow, and M. Rothstein, “A neural network approach including first guess for retrieval of atmospheric water vapor, cloud liquid water path, surface temperature, and emissivities over land from satellite microwave observations,” J. Geophys. Res. 106, 14887–14907 (2001). [CrossRef]
  21. F. Aires, C. Prigent, and W. B. Rossow, “Neural network uncertainty assessment using Bayesian statistics: a remote sensing application,” Neural Comput. 16, 2415–2458 (2004). [CrossRef] [PubMed]
  22. H. Schiller and R. Doerffer, “Neural network for emulation of an inverse mode-operational derivation of case II water properties from MERIS data,” Int. J. Remote Sens. 20, 1735–1746(1999). [CrossRef]
  23. L. Gross, S. Thiria, and R. Frouin, “Applying artificial neural network methodology to ocean color remote sensing,” Eco. Model. 120, 237–246 (1999). [CrossRef]
  24. A. Tanaka, M. Kishino, R. Doerffer, H. Schiller, T. Oishi, and T. Kubota, “Development of a neural network algorithm for retrieving concentrations of chlorophyll, suspended matter and yellow substance from radiance data of the ocean color and temperature scanner,” J. Oceanogr. 60, 519–530 (2004). [CrossRef]
  25. P. J. Werdell and S. W. Bailey, “An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation,” Remote Sens. Environ. 98, 122–140(2005). [CrossRef]
  26. A. Gitelson, J. F. Schalles, and C. M. Hladik, “Remote chlorophyll-a retrieval in turbid, productive estuaries: Chesapeake Bay case study,” Remote Sens. Environ. 109, 464–472 (2007). [CrossRef]
  27. J. Zhou, A. Gilerson, I. Ioannou, S. Hlaing, J. Schalles, B. Gross, F. Moshary, and S. Ahmed, “Retrieving quantum yield of sun-induced chlorophyll fluorescence near surface from hyperspectral in-situ measurement in productive water,” Opt. Express 16, 17468–17483 (2008). [CrossRef] [PubMed]
  28. A. Morel, “Optical modeling of the upper ocean in relation to its biogenous matter content (case I waters),” J. Geophys. Res. 93, 10749–10768 (1988). [CrossRef]
  29. H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semi-analytic radiance model of ocean color,” J. Geophys. Res. 93, 10909–10924(1988). [CrossRef]
  30. A. Morel and S. Maritorena, “Bio-optical properties of oceanic waters: a reappraisal,” J. Geophys. Res. 106, 7163–7180(2001). [CrossRef]
  31. Z. P. Lee, http://www.ioccg.org/groups/lee_data.pdf.
  32. A. Bricaud, M. Babin, A. Morel, and H. Claustre, “Variability in the chlorophyll-specific absorption coefficients of natural phytoplankton: analysis and parameterization,” J. Geophys. Res. 100, 13321–13332 (1995). [CrossRef]
  33. Z. P. Lee, K. L. Carder, C. D. Mobley, R. G. Steward, and J. S. Patch, “Hyperspectral remote sensing for shallow waters: 2. deriving bottom depths and water properties by optimization,” Appl. Opt. 38, 3831–3843 (1999). [CrossRef]
  34. R. P. Bukata, J. H. Jerome, K. Y. Kondratyev, and D. V. Pozdnyakov, Optical Properties and Remote Sensing of Inland and Coastal Waters (CRC Press, 1995).
  35. D. Stramski, A. Bricaud, and A. Morel, “Modeling the inherent optical properties of the ocean based on the detailed composition of the planktonic community,” Appl. Opt. 40, 2929–2945(2001). [CrossRef]
  36. R. Pope and E. Fry, “Absorption spectrum 380–700 nm of pure waters: II. integrating cavity measurements,” Appl. Opt. 36, 8710–8723 (1997). [CrossRef]
  37. A. Morel, “Optical properties of pure water and pure sea water,” in Optical Aspects of Oceanography, N.G.Jerlov and E.S.Nielsen, eds. (Academic, 1974), pp. 1–24.
  38. A. M. Ciotti, M. R. Lewis, and J. J. Cullen, “Assessment of the relationships between dominant cell size in natural phytoplankton communities and the spectral shape of the absorption coefficient,” Limnol. Oceanogr. 47, 404–417 (2002). [CrossRef]
  39. T. Oishi, Y. Takahashi, A. Tanaka, M. Kishino, and A. Tsuchiya, “Relation between the backward as well as total scattering coefficients and the volume scattering functions by cultured phytoplankton,” J. School Mar. Sci. Technol. Tokai Univ. 53, 1–15 (2002).
  40. M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211–3231 (2003). [CrossRef]
  41. C. D. Mobley, Light and Water: Radiative Transfer in Natural Waters (Academic, 1994).
  42. C. D. Mobley and L. K. Sundman, HydroLight 5 (Sequoia Scientific, 2008).
  43. A. Morel, B. Gentili, H. Claustre, M. Babin, A. Bricaud, J. Ras, and F. Tièche, “Optical properties of the “clearest” natural waters,” Limnol. Oceanogr. 52, 217–229 (2007). [CrossRef]
  44. IOCCG Report 5 “Remote sensing of inherent optical properties: fundamentals, tests of algorithms, and applications,” Z.-P.Lee, ed. (2006), pp. 17, 57–62.
  45. M. Babin, A. Morel, V. Fournier-Sicre, F. Fell, and D. Stramski, “Light scattering properties of marine particles in coastal and oceanic waters as related to the particle mass concentration,” Limnol. Oceanogr. 48, 843–859 (2003). [CrossRef]
  46. J. W. Campbell, “The lognormal distribution as a model for bio-optical variability in the sea,” J. Geophys. Res. 100, 13237–13254 (1995). [CrossRef]
  47. http://oceancolor.gsfc.nasa.gov/DOCS/RSR/Aqua_detdep_RSRs.txt.
  48. K. Horrnik, M. Stinchcombe, and H. White, “multilayer feedforward networks are universal approximators,” Neural Netw. 2, 359–366 (1989). [CrossRef]
  49. G. Cybenko, “Approximation by superpositions of a sigmoidal function,” Math. Control Signals Syst. 2, 303–314 (1989). [CrossRef]
  50. K. Levenberg, “A method for the solution of certain non-linear problems in least squares,” Q. Appl. Math. 2, 164–168(1944).
  51. D. W. Marquardt, “An algorithm for the least-squares estimation of nonlinear parameters,” SIAM J. Appl. Math. 11, 431–441 (1963). [CrossRef]
  52. D. J. C. MacKay, “Bayesian interpolation,” Neural Comput. 4, 415–447 (1992). [CrossRef]
  53. F. D. Foresee and M. T. Hagan, “Gauss-Newton approximation to Bayesian regularization,” in Proceedings of the 1997 International Joint Conference on Neural Networks (IEEE, 1997), pp. 1930–1935.
  54. MathWorks, MATLAB 7.6.0, R2008a (2008).
  55. D.S.Livingstone, ed., Artificial Neural Networks: Methods and Applications (Humana, 2009).
  56. S. B. Hooker, G. Lazin, G. Zibordi, and S. McLean, “An evaluation of above- and in-water methods for determining water-leaving radiances,” J. Atmos. Ocean. Technol. 19, 486–515(2002). [CrossRef]
  57. A. Albert and C. D. Mobley, “An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters,” Opt. Express 11, 2873–2890(2003). [CrossRef] [PubMed]
  58. A. Morel, “Light and marine photosynthesis: a spectral model with geochemical and climatological implications,” Progr. Oceanogr. 26, 263–306 (1991). [CrossRef]

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