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Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 52, Iss. 4 — Feb. 1, 2013
  • pp: 795–817

Estimation of hyperspectral inherent optical properties from in-water radiometry: error analysis and application to in situ data

Eric Rehm and Curtis D. Mobley  »View Author Affiliations

Applied Optics, Vol. 52, Issue 4, pp. 795-817 (2013)

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An inverse algorithm is developed to retrieve hyperspectral absorption and backscattering coefficients from measurements of hyperspectral upwelling radiance and downwelling irradiance in vertically homogeneous waters. The forward model is the azimuthally averaged radiative transfer equation, efficiently solved by the EcoLight radiative transfer model, which includes the effects of inelastic scattering. Although this inversion problem is ill posed (the solution is ambiguous for retrieval of total scattering coefficients), unique and stable solutions can be found for absorption and backscattering coefficients. The inversion uses the attenuation coefficient at one wavelength to constrain the inversion, increasing the algorithm’s stability and accuracy. Two complementary methods, Monte Carlo simulation and first-order error propagation, are used to develop uncertainty estimates for the retrieved absorption and backscattering coefficients. The algorithm is tested using both simulated light fields from a chlorophyll-based case I bio-optical model and radiometric field data from the 2008 North Atlantic Bloom Experiment. The influence of uncertainty in the radiometric quantities and additional model parameters on the inverse solution for absorption and backscattering is studied using a Monte Carlo approach, and an uncertainty budget is developed for retrievals. All of the required radiometric and inherent optical property measurements can be made from power-limited autonomous platforms. We conclude that hyperspectral measurements of downwelling irradiance and upwelling radiance, with a single-wavelength measurement of attenuation, can be used to estimate hyperspectral absorption to an accuracy of ± 0.01 m 1 and hyperspectral backscattering to an accuracy of ± 0.0005 m 1 from 350 to 575 nm.

© 2013 Optical Society of America

OCIS Codes
(010.0010) Atmospheric and oceanic optics : Atmospheric and oceanic optics
(010.4450) Atmospheric and oceanic optics : Oceanic optics
(030.5620) Coherence and statistical optics : Radiative transfer
(100.3190) Image processing : Inverse problems
(160.4760) Materials : Optical properties
(280.0280) Remote sensing and sensors : Remote sensing and sensors

ToC Category:
Atmospheric and Oceanic Optics

Original Manuscript: September 25, 2012
Revised Manuscript: November 12, 2012
Manuscript Accepted: December 1, 2012
Published: February 1, 2013

Virtual Issues
Vol. 8, Iss. 3 Virtual Journal for Biomedical Optics

Eric Rehm and Curtis D. Mobley, "Estimation of hyperspectral inherent optical properties from in-water radiometry: error analysis and application to in situ data," Appl. Opt. 52, 795-817 (2013)

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  1. K. S. Johnson, W. M. Berelson, E. S. Boss, Z. Chase, H. Claustre, S. R. Emerson, N. Gruber, A. Kortzinger, M. J. Perry, and S. C. Riser, “Observing biogeochemical cycles at global scales with profiling floats and gliders: prospects for a global array,” Oceanography 22, 216–225 (2009). [CrossRef]
  2. D. Rudnick and M. Perry, eds., “ALPS: autonomous and Lagrangian platforms and sensors,” worskshop report (2003), http://www.geo-prose.com/ALPS/ .
  3. C. A. Brown, Y. Huot, M. J. Purcell, J. J. Cullen, and M. R. Lewis, “Mapping coastal optical and biogeochemical variability using an autonomous underwater vehicle and a new bio-optical inversion algorithm,” Limnol. Oceanogr. Methods 2, 262–281 (2004). [CrossRef]
  4. H. Claustre, J. Bishop, E. Boss, B. Stewart, J. Berthon, C. Coatanoan, K. Johnson, A. Lotiker, O. Ulloa, and M. Perry, “Bio-optical profiling floats as new observational tools for biogeochemical and ecosystem studies,” in Proceedings of the OceanObs ’09: Sustained Ocean Observations and Information for Society Conference, J. Hall, D. E. Harrison, and D. Stammer, eds. (ESA, 2010), ESA publication WPP-306, pp. 1–7.
  5. International Ocean Colour-Coordinating Group, “Bio-optical sensors on Argo floats,” in Reports of the International Ocean-Colour Coordinating Group, IOCCG Report 11, H. Claustre, ed. (IOCCG, 2011).
  6. B. Mitchell, M. Kahru, and J. Sherman, “Autonomous temperature-irradiance profiler resolves the spring bloom in the Sea of Japan,” presented at Proceedings of Ocean Optics XV, Monaco, 16–20 October 2000.
  7. E. Boss, D. Swift, L. Taylor, P. Brickley, R. Zaneveld, S. Riser, M. Perry, and P. Strutton, “Observations of pigment and particle distributions in the western North Atlantic from an autonomous float and ocean color satellite,” Limnol. Oceanogr. 53, 2112–2122 (2008). [CrossRef]
  8. W. J. Bagniewski, K. Fennel, M. J. Perry, and E. A. D’Asaro, “Optimizing models of the North Atlantic spring bloom using physical, chemical and bio-optical observations from a Lagrangian float,” Biogeosciences 8, 1291–1307 (2011). [CrossRef]
  9. I. Cetinić, M. J. Perry, N. T. Briggs, E. Kallin, E. A. D’Asaro, and C. M. Lee, “Particulate organic carbon and inherent optical properties during 2008 North Atlantic Bloom Experiment,” J. Geophys. Res. 117, C06028 (2012). [CrossRef]
  10. X. Xing, A. Morel, H. Claustre, D. Antoine, F. D’Ortenzio, A. Poteau, and A. Mignot, “Combined processing and mutual interpretation of radiometry and fluorimetry from autonomous profiling Bio-Argo floats: chlorophyll a retrieval,” J. Geophys. Res. 116, C06020 (2011). [CrossRef]
  11. M. Alkire, E. D’Asaro, C. Lee, M. Jane Perry, A. Gray, I. Cetinić, N. Briggs, E. Rehm, E. Kallin, J. Kaiser, and A. González-Posada, “Estimates of net community production and export using high-resolution, Lagrangian measurements of O2, NO3−, and POC through the evolution of a spring diatom bloom in the North Atlantic,” Deep Sea Res. I 64, 157–174 (2012). [CrossRef]
  12. X. Xing, A. Morel, H. Claustre, F. D’Ortenzio, and A. Poteau, “Combined processing and mutual interpretation of radiometry and fluorometry from autonomous profiling Bio-Argo floats: 2. Colored dissolved organic matter absorption retrieval,” J. Geophys. Res. 117, C04022 (2012). [CrossRef]
  13. International Ocean Colour-Coordinating Group, “Remote sensing of inherent optical properties: fundamentals, tests of algorithms, and applications,” in Reports of the International Ocean-Colour Coordinating Group, IOCCG Report 5, Z. P. Lee, ed. (IOCCG, 2006).
  14. H. Lavigne, F. D’Ortenzio, H. Claustre, and A. Poteau, “Towards a merged satellite and in situ fluorescence ocean chlorophyll product,” Biogeosciences 9, 2111–2125 (2012). [CrossRef]
  15. 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]
  16. 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]
  17. R. J. Geider, H. L. MacIntyre, and T. M. Kana, “A dynamic model of photoadaptation in phytoplankton,” Limnol. Oceanogr. 41, 1–15 (1996). [CrossRef]
  18. D. Stramski, E. Boss, D. Bogucki, and K. J. Voss, “The role of seawater constituents in light backscattering in the ocean,” Prog. Oceanogr. 61, 27–56 (2004). [CrossRef]
  19. A. L. Whitmire, W. S. Pegau, L. Karp-Boss, E. Boss, and T. J. Cowles, “Spectral backscattering properties of marine phytoplankton cultures,” Opt. Express 18, 15073–15093 (2010). [CrossRef]
  20. W. Zhou, G. Wang, Z. Sun, W. Cao, Z. Xu, S. Hu, and J. Zhao, “Variations in the optical scattering properties of phytoplankton cultures,” Opt. Express 20, 11189–11206 (2012). [CrossRef]
  21. H. R. Gordon, M. R. Lewis, S. D. McLean, M. S. Twardowski, S. A. Freeman, K. J. Voss, and G. C. Boynton, “Spectra of particulate backscattering in natural waters,” Opt. Express 17, 16192–16208 (2009). [CrossRef]
  22. C. D. Mobley, Light and Water: Radiative Transfer in Natural Waters (Academic, 1994).
  23. N. J. McCormick, “Inverse radiative transfer problems: a review,” Nucl. Sci. Eng. 112, 185–198 (1992).
  24. H. R. Gordon, “Inverse methods in hydrologic optics,” Oceanologia 44, 9–58 (2002).
  25. A. H. Barnard, J. R. V. Zaneveld, and W. S. Pegau, “In situ determination of the remotely sensed reflectance and the absorption coefficient: closure and inversion,” Appl. Opt. 38, 5108–5117 (1999). [CrossRef]
  26. M. Stramska, D. Stramski, B. G. Mitchell, and C. D. Mobley, “Estimation of the absorption and backscattering coefficients from in-water radiometric measurements,” Limnol. Oceanogr. 45, 628–641 (2000). [CrossRef]
  27. H. Loisel and D. Stramski, “Estimation of the inherent optical properties of natural waters from the irradiance attenuation coefficient and reflectance in the presence of Raman scattering,” Appl. Opt. 39, 3001–3011 (2000). [CrossRef]
  28. Z. Lee, K. L. Carder, and R. A. Arnone, “Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters,” Appl. Opt. 41, 5755–5772 (2002). [CrossRef]
  29. D. McKee, A. Cunningham, and S. Craig, “Estimation of absorption and backscattering coefficients from in situ radiometric measurements: theory and validation in case II waters,” Appl. Opt. 42, 2804–2810 (2003). [CrossRef]
  30. V. Garg and I. Chaubey, “A computationally efficient inverse modelling approach of inherent optical properties for a remote sensing model,” Int. J. Remote Sens. 31, 4349–4371(2010). [CrossRef]
  31. E. Rehm, and N. J. McCormick, “Inherent optical property estimation in deep waters,” Opt. Express 19, 24986–25005(2011). [CrossRef]
  32. H. R. Gordon, O. B. Brown, and M. M. Jacobs, “Computed relationships between the inherent and apparent optical properties of a flat homogeneous ocean,” Appl. Opt. 14, 417–427 (1975). [CrossRef]
  33. Z. Lee, R. Arnone, C. Hu, P. J. Werdell, and B. Lubac, “Uncertainties of optical parameters and their propagations in an analytical ocean color inversion algorithm,” Appl. Opt. 49, 369–381 (2010). [CrossRef]
  34. A. Morel, H. Claustre, D. Antoine, and B. Gentili, “Natural variability of bio-optical properties in Case 1 waters: attenuation and reflectance within the visible and near-UV spectral domains, as observed in South Pacific and Mediterranean waters,” Biogeosciences 4, 913–925 (2007). [CrossRef]
  35. S. A. 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]
  36. S. Maritorena and D. A. Siegel, “Consistent merging of satellite ocean color data sets using a bio-optical model,” Remote Sens. Environ. 94, 429–440 (2005). [CrossRef]
  37. S. Maritorena, O. H. F. d’Andon, A. Mangin, and D. A. Siegel, “Merged satellite ocean color data products using a bio-optical model: characteristics, benefits and issues,” Remote Sens. Environ. 114, 1791–1804 (2010). [CrossRef]
  38. Z. Tao, N. J. McCormick, and R. Sanchez, “Ocean source and optical property estimation from explicit and implicit algorithms,” Appl. Opt. 33, 3265–3275 (1994). [CrossRef]
  39. H. R. Gordon and G. C. Boynton, “Radiance-irradiance inversion algorithm for estimating the absorption and backscattering coefficients of natural waters: homogeneous waters,” Appl. Opt. 36, 2636–2641 (1997). [CrossRef]
  40. G. C. Boynton and H. R. Gordon, “Irradiance inversion algorithm for estimating the absorption and backscattering coefficients of natural waters: Raman-scattering effects,” Appl. Opt. 39, 3012–3022 (2000). [CrossRef]
  41. H. R. Gordon and G. C. Boynton, “Radiance–irradiance inversion algorithm for estimating the absorption and backscattering coefficients of natural waters: vertically stratified water bodies,” Appl. Opt. 37, 3886–3896 (1998). [CrossRef]
  42. R. Spurr, K. Stamnes, H. Eide, W. Li, K. Zhang, and J. Stamnes, “Simultaneous retrieval of aerosols and ocean properties: a classic inverse modeling approach. I. Analytic Jacobians from the linearized CAO-DISORT model,” J. Quant. Spectrosc. Radiat. Transfer 104, 428–449 (2007). [CrossRef]
  43. C. D. Rodgers, Inverse Methods for Atmospheric Sounding: Theory and Practice, Series on Atmospheric, Oceanic and Planetary Physics (World Scientific, 2000).
  44. W. Li, K. Stamnes, R. Spurr, and J. Stamnes, “Simultaneous retrieval of aerosol and ocean properties by optimal estimation: SeaWiFS case studies for the Santa Barbara Channel,” Int. J. Remote Sens. 29, 5689–5698 (2008). [CrossRef]
  45. R. Spurr, K. Stamnes, H. Eide, W. Li, K. Zhang, and J. Stamnes, “Error analysis for simultaneous retrieval of marine and aerosol properties from SeaWiFS,” presented at Proceedings of Ocean Optics XVIII, Montreal, Canada, 9–13 October 2006.
  46. C. D. Mobley, L. K. Sundman, C. O. Davis, J. H. Bowles, T. V. Downes, R. A. Leathers, M. J. Montes, W. P. Bissett, D. D. R. Kohler, and R. P. Reid, “Interpretation of hyperspectral remote-sensing imagery by spectrum matching and look-up tables,” Appl. Opt. 44, 3576–3592 (2005). [CrossRef]
  47. G. Chang, K. Mahoney, A. Briggs-Whitmire, D. Kohler, C. Mobley, M. Lewis, M. A. Moline, E. Boss, M. Kim, and W. Philpot, “The new age of hyperspectral oceanography,” Oceanography 17, 22–29 (2004). [CrossRef]
  48. C. D. Mobley, “Fast light calculations for ocean ecosystem and inverse models,” Opt. Express 19, 18927–18944 (2011). [CrossRef]
  49. E. A. D’Asaro, C. Lee, M. Perry, K. Fennel, E. Rehm, A. Gray, N. Briggs, and K. Gudmundsson, “The 2008 North Atlantic Spring Bloom Experiment I: overview and strategy,” EOS89(53), Fall Meeting Supplement, abstract OS24A-08 (2008).
  50. R. A. Leathers, and N. J. McCormick, “Ocean inherent optical property estimation from irradiances,” Appl. Opt. 36, 8685–8698 (1997). [CrossRef]
  51. 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]
  52. J. H. Smart, “World-Wide Ocean Optics Database (WOOD),” Oceanography 13, 70–74 (2000). [CrossRef]
  53. P. J. Werdell, G. S. Fargion, C. R. McClain, and S. W. Bailey, “The SeaWiFS bio-optical archive and storage system (SeaBASS): current architecture and implementation,” NASA/TM-2002-211617 (NASA Goddard Space Flight Center, 2002).
  54. 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]
  55. A. Mahadevan, E. D’Asaro, C. Lee, and M. J. Perry, “Eddy-driven stratification initiates North Atlantic spring phytoplankton blooms,” Science 337, 54–58 (2012). [CrossRef]
  56. G. R. Fournier, and J. L. Forand, “Analytic phase function for ocean water,” Proc. SPIE 2258, 194–201 (1994). [CrossRef]
  57. C. D. Mobley, L. K. Sundman, and E. Boss, “Phase function effects on oceanic light fields,” Appl. Opt. 41, 1035–1050 (2002). [CrossRef]
  58. S. B. Hooker, C. R. McClain, A. Mannino, and G. S. F. Center, “NASA strategic planning document: a comprehensive plan for the long-term calibration and validation of oceanic biogeochemical satellite data” (NASA Goddard Space Flight Center, 2007).
  59. J. L. Mueller, C. Pietras, S. B. Hooker, R. W. Austin, M. Miller, K. D. Knobelspiesse, R. Frouin, B. Holben, and K. Voss, “Ocean optics protocols for satellite ocean color sensor validation, Revision 4, Volume II: instrument specifications, characterization and calibration,” NASA Tech. Memo. NASA/TM-2003-21621 (NASA, 2003).
  60. K. J. Voss, S. McLean, M. Lewis, C. Johnson, S. Flora, M. Feinholz, M. Yarbrough, C. Trees, M. Twardowski, and D. Clark, “An example crossover experiment for testing new vicarious calibration techniques for satellite ocean color radiometry,” J. Atmos. Oceanic Technol. 27, 1747–1759 (2010). [CrossRef]
  61. MATLAB Optimization Toolbox 5 User’s Guide (The MathWorks, Inc., 2010).
  62. The HydroLight/EcoLight software, as supplied by Sequioa Scientific, Inc., includes FORTRAN source code. Using the MATLAB MEX gateway ( http://www.mathworks.com/help/matlab/matlab_external/fortran-source-mex-files.html ), EcoLight software was modified to create a shared library that allows EcoLight to run from a MATLAB script or command line and return results as a MATLAB structure.
  63. R. C. Aster, B. Borchers, and C. H. Thurber, Parameter Estimation and Inverse Problems, 2nd ed. (Academic, 2012).
  64. P. Diehl, and H. Haardt, “Measurement of the spectral attenuation to support biological research in a ‘plankton tube’ experiment,” Oceanol. Acta 3, 89–96 (1980).
  65. E. Boss, M. S. Twardowski, and S. Herring, “Shape of the particulate beam attenuation spectrum and its inversion to obtain the shape of the particulate size distribution,” Appl. Opt. 40, 4885–4893 (2001). [CrossRef]
  66. A. Gelb, Applied Optimal Estimation (Analytic Science Corporation, MIT, 1974).
  67. J. Worden, S. S. Kulawik, M. W. Shephard, S. A. Clough, H. Worden, K. Bowman, and A. Goldman, “Predicted errors of tropospheric emission spectrometer nadir retrievals from spectral window selection,” J. Geophys. Res. 109, D09308 (2004). [CrossRef]
  68. R. A. Johnson and D. W. Wichern, Applied Multivariate Statistical Analysis, 6th ed. (Prentice-Hall, 2006).
  69. N. R. Draper and H. Smith, Applied Regression Analysis(Wiley, 1998).
  70. B. N. Taylor and C. E. Kuyatt, “Guidelines for evaluating and expressing the uncertainty of NIST measurement results” (National Institute of Standards and Technology, 2009), retrieved 20 October 2012, http://www.nist.gov/pml/pubs/tn1297/index.cfm .
  71. S. W. Brown, S. J. Flora, M. E. Feinholz, M. A. Yarbrough, T. Houlihan, D. Peters, Y. S. Kim, J. L. Mueller, B. C. Johnson, and D. K. Clark, “The marine optical buoy (MOBY) radiometric calibration and uncertainty budget for ocean color satellite sensor vicarious calibration,” Proc. SPIE 6744, 67441M (2007). [CrossRef]
  72. H. W. Coleman and W. G. Steele, Experimentation, Validation, and Uncertainty Analysis for Engineers (Wiley, 2009).
  73. J. H. Zar, Biostatistical Analysis, 4th ed. (Prentice-Hall, 1999).
  74. J. C. Clarke, “Modelling uncertainty: A primer,” Tech. Rep. 2161, (University of Oxford Department of Engineering Science, 1998), pp. 1–21.
  75. L. Li, H. Fukushima, R. Frouin, B. G. Mitchell, M.-X. He, I. Uno, T. Takamura, and S. Ohta, “Influence of submicron absorptive aerosol on Sea-Viewing Wide Field-of-View Sensor (SeaWiFS)-derived marine reflectance during Aerosol Characterization Experiment (ACE)-Asia,” J. Geophys. Res.108, 4472 (2003). [CrossRef]
  76. C. D. Mobley and L. K. Sundman, HydroLight 5.0, EcoLight 5.0 Technical Documentation (Sequoia Scientific, 2008).
  77. W. W. Gregg and K. L. Carder, “A simple spectral solar irradiance model for cloudless maritime atmospheres,” Limnol. Oceanogr. 35, 1657–1675 (1990). [CrossRef]
  78. M. Bücker, G. Corliss, P. Hovland, U. Naumann, and B. Norris, eds., Automatic Differentiation: Applications, Theory and Implementations, Lecture Notes in Computational Science and Engineering (Springer-Verlag, 2006), Vol. 50.
  79. J. Hadamard, “Sur les problemes aux dérivées partielles et leur signification physique,” Princeton Univ. Bull. 13, 49–52 (1902).
  80. R. W. Preisendorfer, Hydrologic Optics, NTIS PB-259 793/8ST (NOAA Pacific Marine Environment Laboratories, 1976).
  81. M. Sydor, R. W. Gould, R. A. Arnone, V. I. Haltrin, and W. Goode, “Uniqueness in remote sensing of the inherent optical properties of ocean water,” Appl. Opt. 43, 2156–2162 (2004). [CrossRef]
  82. M. Defoin-Platel and M. Chami, “How ambiguous is the inverse problem of ocean color in coastal waters?,” J. Geophys. Res. 112, C03004 (2007). [CrossRef]
  83. D. Creanor and A. Cunningham, “Origins of ambiguity in the inversion of remote sensing reflectance signals by spectral matching in optically complex shelf seas,” JEOS RP 5, 10081S (2010). [CrossRef]
  84. C. D. Mobley, B. Gentili, H. R. Gordon, Z. Jin, G. W. Kattawar, A. Morel, P. Reinersman, K. Stamnes, and R. H. Stavn, “Comparison of numerical models for computing underwater light fields,” Appl. Opt. 32, 7484–7504 (1993). [CrossRef]
  85. M. Williams and M. Eaton, “A probabilistic study of the influence of parameter uncertainty on solutions of the radiative transfer equation,” J. Quant. Spectrosc. Radiat. Transfer 111, 696–707 (2010). [CrossRef]
  86. Z. Li, M. Cribb, F. Chang, and A. Trishchenko, “Validation of MODIS-retrieved cloud fractions using whole sky imager measurements at the three ARM sites,” presented at Proceedings of the 14th Atmospheric Radiation Measurement (ARM) Science Team Meeting, Albuquerque, New Mexico, 22–26 March 2004.
  87. B. A. Baum and S. Platnick, “Introduction to MODIS cloud products,” in Earth Science Satellite Remote Sensing, J. J. Qu, W. Gao, M. Kafatos, R. E. Murphy, and V. Salomonson, eds. Vol. 1, Science and Instruments (Springer-Verlag, 2006), pp. 74–91.
  88. W. S. Pegau, D. Gray, and J. R. V. Zaneveld, “Absorption and attenuation of visible and near-infrared light in water: dependence on temperature and salinity,” Appl. Opt. 36, 6035–6046 (1997). [CrossRef]
  89. J. R. V. Zaneveld, J. C. Kitchen, and C. C. Moore, “Scattering error correction of reflecting-tube absorption meters,” Proc. SPIE 2258, 44–55 (1994). [CrossRef]
  90. N. Briggs, “The 2008 North Atlantic Bloom Experiment calibration report #7: intercalibration of the backscatter sensors,” (Biological and Chemical Oceanography Data Management Office, 2011), retrieved 21 July 2012, http://data.bco-dmo.org/NAB08/Backscatter_Calibration-NAB08.pdf .
  91. E. Kallin, I. Cetinić, M. J. Perry, and M. Sauer, “Laboratory_analysis_report-NAB08,” (Biological and Chemical Oceanography Data Management Office, 2011), retrieved 21 July 2012, http://osprey.bcodmo.org/dataset.cfm?id=13820&flag=view .
  92. W. Menke, Geophysical Data Analysis: Discrete Inverse Theory, International Geophysics Series (Academic, 1989).

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