Accuracy Assessment of Bio-optical Models to Retrieve Backscattering Coefficients in Case 1 Waters of the Bay of Bengal

  • Nikhil Kumar BaranvalEmail author
  • P. V. Nagamani
  • P. Rama Rao
  • S. B. Choudhury
Research Article


The backscattering coefficient (bb) has been obtained either in situ observations/measurements or semi-analytical/analytical and empirical algorithms that depend on the relationship between ‘bb’ and the remote sensing reflectance (Rrs). Several models were developed to estimate backscattering coefficient from the satellite imagery. The present study aims to assess the accuracy of bio-optical models and infer the best suitable model for Ocean Colour Monitoring (OCM-2) and for the upcoming OCM-3 sensors of Indian Space Research Organization. For this purpose, the bio-optical algorithms/models such as quasi-analytical algorithm (QAA), QAA version 5, Generalized Inherent Optical Properties (GIOP) and optimization of semi-analytical models in case 1 waters of the Bay of Bengal (BoB) were considered. For this analysis, three satellite sensors Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua, Visible Infrared Imaging Radiometer Suite (VIIRS), and OCM-2 datasets has been used to assess the model’s accuracy. The results showed that the optimization technique performs better (bias = 0.002, 0.179 and root-mean-square error (RMSE) = 8%, 20%) for MODIS-A and OCM-2, respectively, whereas GIOP performs better (bias = 0.08, RMSE = 14%) for VIIRS in case 1 waters of the BoB. From the statistical analysis of each model for all stations, it is recommended to use the optimization technique rather than GIOP technique for estimation of satellite based ‘bb’ in Indian waters.


Backscattering coefficient QAA QAA_v5 GIOP Optimization Case 1 waters 



We thank Dr. V.K. Dhadwal, former Director, NRSC, Dr. Santanu Chowdhury, Director, NRSC and Dr. M. V. R. Sesha Sai, Deputy Director, ECSA and Program Director, NICES for their consistent support and encouragement to carry out this work. The authors would like to express their sincere thanks to Dr. Harish Kumar, Chief Scientist, NPOL, Kochi, for providing the opportunity to participate in this cruise, Navy Officers onboard and the respective collaborators for participating in the cruise for collecting the data support and co-operation to carry out this work in a big way.


  1. Boss, E., & Pegau, W. S. (2001). Relationship of light scattering at an angle in the backward direction to the backscattering coefficient. Applied Optics, 40(30), 5503–5507.CrossRefGoogle Scholar
  2. Bricaud, A., Babin, M., Morel, A., & Claustre, H. (1995). Variability in the chlorophyll-specific absorption coefficients of natural phytoplankton: Analysis and parameterization. Journal of Geophysical Research. Scholar
  3. Carder, K. L., Hawes, S. K., Baker, K. A., Smith, R. C., Steward, R. G., & Mitchell, B. G. (1991). Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products. Journal Geophysical Research, 96, 20599–20611.CrossRefGoogle Scholar
  4. Carder, K. L., Steward, R. G., Harvey, G. R., & Ortner, P. B. (1989). Marine humic and fulvic acids: Their effects on remote sensing of ocean chlorophyll. Limnology and Oceanography, 34, 68–81.CrossRefGoogle Scholar
  5. Doxaran, D., Cherukuru, R. C. N., & Lavender, S. J. (2006). Inherent and apparent optical properties of turbid estuarine waters: Measurements, modelling and application to remote sensing. Applied Optics, 45, 2310–2324.CrossRefGoogle Scholar
  6. Gordon, H. R., Brown, O. B., Evans, R. H., Brown, J. W., Smith, R. C., Baker, K. S., et al. (1988). A semi-analytical radiance model of ocean colour. Journal Geophysical Research, 93, 10909–10924.CrossRefGoogle Scholar
  7. Hoge, F. E., & Lyon, P. E. (1996). Satellite retrieval of inherent optical properties by linear matrix inversion of oceanic radiance models: An analysis of model and radiance measurement errors. Journal Geophysical Research, 101, 16631–16648.CrossRefGoogle Scholar
  8. IOCCG. (2006). Remote sensing of inherent optical properties: fundamentals, tests of algorithms, and applications. In Z. P. Lee (Ed.), Reports of the International Ocean-Colour Coordinating Group (No. 5, pp. 126). Dartmouth, Canada: IOCCG.Google Scholar
  9. Lee, Z. P., Carder, K. L., & Arnone, R. A. (2002). Deriving inherent optical properties from water colour: A multiband quasi-analytical algorithm for optically deep waters. Applied Optics, 41(27), 5755–5772.CrossRefGoogle Scholar
  10. Lee, Z. P., Carder, K. L., Chen, R. F., & Peacock, T. G. (2001). Properties of the water column and bottom derived from AVIRIS data. Journal Geophysical Research, 106, 11639–11652.CrossRefGoogle Scholar
  11. Lee, Z. P., Carder, K. L., Hawes, H. K., Steward, R. G., Peacock, T. G., & Davis, C. O. (1994). Model for the interpretation of hyperspectral remote-sensing reflectance. Applied Optics, 33(24), 5721–5732.CrossRefGoogle Scholar
  12. Lee, Z. P., Carder, K. L., Mobley, C. D., Steward, R. G., & Patch, J. S. (1999). Hyperspectral remote sensing for shallow waters: 2. Deriving bottom depths and water properties by optimization. Applied Optics, 38, 3831–3843.CrossRefGoogle Scholar
  13. Lee, Z. P., Darecki, M., Carder, K. L., Davis, C. O., Stramski, D., & Rhea, W. J. (2005). Diffuse attenuation coefficient of down-welling irradiance: An evaluation of remote sensing methods. Journal of Geophysical Research. Scholar
  14. Lee, Z. P., Lubac, B., Werdell, P. J., & Arnone, R. (2009). An update of the quasi-analytical algorithm (QAA_v5). Technical report: International Ocean Colour Coordinating Group (IOCCG).
  15. Lee, Z. P., Weidemann, A., Kindle, J., Arnone, R. A., Carder, K. L., & Davis, C. (2007). Euphotic zone depth: Its derivation and implication to ocean colour remote sensing. Journal Geophysical Research. Scholar
  16. Marshall, B. R., & Smith, R. C. (1990). Raman scattering and in-water ocean optical properties. Applied Optics, 29(1), 71–84.CrossRefGoogle Scholar
  17. McKee, D., Chami, M., Brown, I., Calzado, V. S., Doxaran, D., & Cunningham, A. (2009). Role of measurement uncertainties in observed variability in the spectral backscattering ratio: A case study in mineral-rich coastal waters. Applied Optics, 48, 4663–4675.CrossRefGoogle Scholar
  18. Mobley, C. D. (1994). Light and Water. Academic, San Diego, Calif: Radiative Transfer in Natural Waters.Google Scholar
  19. Morel, A. (1974). Optical properties of pure water and pure seawater. In N. G. Jerlov & N. E. Steemann (Eds.), Optical aspects of oceanography (pp. 1–24). New York: Academic.Google Scholar
  20. Morel, A., & Gentili, B. (1993). Diffuse reflectance of oceanic waters, 2, bi-directional aspects. Applied Optics, 32, 6864–6879.CrossRefGoogle Scholar
  21. Pope, R. M., & Fry, E. S. (1997). Absorption spectrum 380–700 nm of pure water. II. Integrating cavity measurements. Applied Optics, 36, 8710–8723.CrossRefGoogle Scholar
  22. Prasad, T. D. V., Latha, T. P., Rao, K. H., Choudhury, S. B. & Nagamani P. V. (2012). Processing of oceansat-2 ocean colour monitoring data using SeaDAS. Technical report. NRSC/ECSA/AOSG/OSD/Dec2012/TR-488.Google Scholar
  23. Preisendorfer, R. W. (1976). Introduction, Vol. 1 of Hydrologic Optics. Nat. 327 Tech. Inf. Service, Springfield, VA, USA. NTIS PB-259 793_8ST.Google Scholar
  24. Sun, D., Li, Y., Wang, Q., Gao, J., Lv, H., Le, C., et al. (2009). Light scattering properties and their relation to the biogeochemical composition of turbid productive waters: A case study of Lake Taihu. Applied Optics, 48, 1979–1989.CrossRefGoogle Scholar
  25. Werdell, P. J., Franz, B. A., Bailey, S. W., Feldman, G. C., Boss, E., et al. (2013). Generalized ocean color inversion model for retrieving marine inherent optical properties. Applied Optics, 52, 2019–2037.CrossRefGoogle Scholar

Copyright information

© Indian Society of Remote Sensing 2019

Authors and Affiliations

  1. 1.National Remote Sensing CentreHyderabadIndia
  2. 2.Department of GeophysicsAndhra UniversityVishakhapattanamIndia

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