Chairman:

Dr. ZhongPing Lee
Naval Research Laboratory
Code 7333
Stennis Space Center
MS 39529, USA
Email: zplee@nrclssc.navy.mil

This working group was proposed at the 8th IOCCG Meeting in Florence, Italy (February 2003), although a preliminary meeting was held in Santa Fe, November 2002, prior to the Ocean Optics Meeting.

The objectives of the group were to perform algorithm cross comparisons, to make recommendations on specific algorithms and to report on the progress of algorithm development.

The group assembled a database from in situ measurements and also developed a synthesized dataset based on known relationships, in order to perform algorithm cross-comparisons and evaluations. The synthesized datasets, as well as the software for the various algorithms, are available on the IOCCG webpage (see links to the right in red). The final product of this working group was the publication of IOCCG Report 5 entitled “Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms, and Applications”, edited by Dr. ZhongPing Lee.

Terms of Reference

  • Synthesize a database of inherent (IOP) and apparent optical properties (AOP), and assemble a database of in situ measurements.
  • Perform cross-comparisons and evaluations on existing ocean-colour inversion algorithms.
  • Make recommendations on specific algorithms.
  • Report on the progress of algorithm development.
Synthesized Dataset from IOCCG Report 5

This synthesized dataset contains both inherent optical properties (IOPs) and apparent optical properties (AOPs) for testing and comparing ocean colour algorithms. See PDF file for details of the dataset and IOCCG Report 5 for further information about the algorithms.

Please cite IOCCG Report 5 as follows if you use this dataset:

IOCCG (2006). Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms, and Applications. Lee, Z.-P. (ed.), Reports of the International Ocean-Colour Coordinating Group, No. 5, IOCCG, Dartmouth, Canada.

Software for Ocean-Colour Algorithms

The software for the various algorithms discussed in IOCCG Report 5 can be found below. Please remember to check the relevant weblinks, or contact the authors for algorithm updates.

  • Inversion of IOP based on Rrs and Remotely Retrieved Kd (Chapter 5: Inversion of IOP based on Rrs and Remotely Retrieved Kd by Hubert Loisel and Antoine Poteau). The Fortran program for the IOP inversion algorithm, as well as three look-up tables can be downloaded below.Fortran Program: IOP_inversion.f [Posted 26 February 2007]
    Look-up tables: LUT_AWLUT_KD and LUT_RRS [Posted 26 February 2007]
  • Over Constrained Linear Matrix Inversion (Chapter 8: Over Constrained Linear Matrix Inversion with Statistical Selection by Emmanuel Boss and Collin Roesler). The updated code files can be found on the University of Maine, In-situ Sound & Color Lab website, or they can be downloaded below:
    In situ data inversion [Posted 31 October 2006]
    Synthetic data inversion [Posted 31 October 2006]
  • Quasi-Analytical Algorithm (Chapter 10: Quasi-Analytical Algorithm by ZhongPing Lee, Kendall Carder and Robert Arnone)
    This IOP algorithm was updated in March 2009 and November 2014. See QAA_v5.pdf and  QAA_v6.pdf for a full description of updates.
    Quasi-Analytical Algorithm (QAA) Excel file [Version 6: updated 4 May 2015].
  • Garver, Siegel, Maritorena Model (GSM-01) (Chapter 11: The GSM Semi-Analytical Bio-Optical Model by Stéphane Maritorena and Dave Siegel). The updated IDL code files for this model can be downloaded from http://www.icess.ucsb.edu/OCisD/or they can be downloaded below:
    GSM 01 IDL code files [Posted 25 October 2006]
  • PML algorithm by Smyth, Moore, Hirata and Aiken (2006).The PML algorithm is an IOP algorithm developed by Smyth et al. (2006) at the Plymouth Marine Laboratory, which was not available for evaluation when the IOCCG working group was convened.  PML algorithm software . [Posted 23 February 2007]
    The PML IOP model is an analytical approach for determining the spectral inherent optical properties of the ocean which uses spectral slopes, derived from field measurements, at the central wavelengths of 490 and 510 nm (or 531 for MODIS). Once the absorption and backscatter are known at these wavelengths, based on the assertion of Morel (1980), then the absorption and backscatter across the spectrum can be determined if you assume a spectral shape for backscatter.Once the primary inherent optical properties of total absorption and backscatter have been determined the bio-geochemical parameters can be determined using standard relationships and slopes for CDOM and phytoplankton. The reference for the model, together with its validation using the NOMAD dataset can be found in:

    Smyth T. J., G. F. Moore, T. Hirata and J. Aiken (2006) Semianalytical model for the derivation of ocean color inherent optical properties: description, implementation, and performance assessment. Applied Optics, 45, 8116-8131.

Members:

  • Yu-Hwan, Ahn Korea Ocean Research and Development Institute, Korea
  • Robert Arnone, Stennis Space Center, USA
  • Marcel Babin, Universite Pierre et Marie Curie, France
  • Emmanuel Boss, Oregon State University, USA
  • Aurea Maria, Ciotti Instituto Oceanográfico da Universidade de Sao Paulo
  • Kendall Carder, University of South Florida
  • Arnold Dekker, C.S. Christian Laboratory, Australia
  • Roland Doerffer, Max-Planck Institut, Germany
  • Robert Frouin, Scripps Institution of Oceanography, USA
  • MingXia He, University of Qingdao, China
  • Chuanmin Hu, University of South Florida
  • Joji Ishizaka, Nagasaki University, Japan
  • M. Kahru, Scripps Institution of Oceanography, USA

Members:

  • Oleg V. Kopelevich, Russian Academy of Sciences, Russia
  • ZhongPing Lee, Stennis Space Center, USA
  • Hubert Loisel, Université du Littoral Côte d’Opale, France
  • Merv Lynch, Curtin University of Technology, Australia
  • Paul Lyon, Naval Research Lab, USA
  • Stephane Maritorena, Institute for Computational Earth System Science, USA
  • B. Greg Mitchell, Scripps Institution of Oceanography
  • Collin Roesler Bigelow, Laboratory for Ocean Sciences, USA
  • Shubha Sathyendranath, Bedford Institute of Oceanography, Canada
  • JunWu Tang, National Satellite Ocean Application Service, China
  • Ron Zaneveld, Oregon State University, USA

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