ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 1, pp. 42-49

Application of empirical orthogonal functions in satellite monitoring of the upper layer of sea water

G.S. Moiseenko 1 , S.D. Levashov 1 
1 Russian Federal Research Institute of Fisheries and Oceanography, Moscow, Russia
Accepted: 12.12.2019
DOI: 10.21046/2070-7401-2020-17-1-42-49
The data processing algorithms for satellite spectroradiometers that relate the in situ measured values of sea water parameters to the values of the remote sensing reflectance spectra measured by the spectroradiometer mainly use remote sensing reflectance for 2, 3, or 4 wavelengths, while the information from other spectral channels is, in fact, ignored. A statistical approach based on the empirical orthogonal functions analysis that uses the whole measured spectrum is proposed. In this case the regression equations, which connect the estimated parameters with coefficients of serial expansion for remote sensing reflectance on the basis of empirical orthogonal functions, are applied to retrieve sea water constituents. This method was used before in some studies for remote sensing data analysis. But the computations were made on a small set of data, the empirical orthogonal functions varied depending on the area of the research and the time interval when data were collected, and thus could not be applied for other datasets. The difference of the proposed approach is that to calculate the covariance matrix and, accordingly, empirical orthogonal functions, it is proposed to use annual arrays of remote sensing reflectance for the entire world ocean. As an example of application the use of computed empirical orthogonal functions for the estimation of particulate inorganic carbon concentrations during coccolithophores blooms is demonstrated.
Keywords: remote sensing reflectance, empirical orthogonal functions, remote sensing, ocean, method, satellite, coccolithophores
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References:

  1. Bagrov N. A., Analiticheskoe predstavlenie posledovatel’nosti meteorologicheskikh polei posredstvom estestvennykh ortogonal’nykh sostavlyayushchikh (Analytical presentation of the sequence of meteorological fields through natural orthogonal components), Trudy Tsentral’nogo instituta prognozov, 1959, Issue 74, pp. 3–24.
  2. Kopelevich O. V., Gushchin O. A., O statisticheskoi i fizicheskoi modelyakh svetorasseivayushchikh svoistv morskoi vody (On the statistical and physical models of the light–scattering properties of sea water), Izvestiya AN SSSR, Fizika atmosfery i okeana, 1978, Vol. 14, No. 9, pp. 967–973.
  3. Kopelevich O. V., Burenkov V. I., Gushchin O. A., Mashtakov Yu. L., Shmatko M. A., Universal’naya sistema funktsii dlya approksimatsii indikatris rasseyaniya sveta morskoi vody (Universal system of functions for approximation of scattering function of light of sea water), Izvestiya AN SSSR, Fizika atmosfery i okeana, 1975, Vol. 11, No. 7, pp. 770–773.
  4. Obukhov A. M., O statisticheski ortogonal’nykh razlozheniyakh empiricheskikh funktsii (On statistically orthogonal expansions of empirical functions), Izvestiya AN SSSR, Ser. geofizicheskaya, 1960, No. 3, pp. 432–439.
  5. Romanov A. A., Moiseenko G. S., Kuznetsov M. B., Metod vosstanovleniya skorosti privodnogo vetra po spektral’nym kharakteristikam voskhodyashchego izlucheniya (Method for reconstructing wind speed above the water surface from spectral characteristics of upwelling radiation), Trudy NPO “Planeta”, 1992, No. 41, pp. 128–135.
  6. Clark D. K., MODIS algorithm theoretical basis document. Bio-optical algorithms — case 1 waters, Version 1.2, National Oceanic and Atmospheric Administration National Environmental Satellite Service, Washington, D. C., 1997, 50 p.
  7. Craig S. E., Jones C. T., Li W. K. W., Lazin G., Horne E., Caverhill C., Cullen J. J., Deriving optical metrics of coastal phytoplankton biomass from ocean colour, Remote Sensing of Environment, 2012, Vol. 119, pp. 72–83.
  8. Doerffer R., Factor analysis in ocean color interpretation, In: Oceanography from Space, Gower J. F. R. (ed.), New York: Plenum, 1981, pp. 339–345.
  9. Gower J. F. R., Lin S., Borstad G. A., The information content of different optical spectral ranges for remote chlorophyll estimation in coastal waters, Intern. J. Remote Sensing, 1984, Vol. 5, No. 2, pp. 349–364.
  10. Kopelevich O. V., Burenkov V. I., Sheberstov S. V., Vazyulya S. V., Zavialov S. P., Bio-optical characteristics of the Russian Seas from satellite ocean color data of 1998–2010, Proc. Intern. Conf. “Current problems in Optics of Natural Waters (ONW 2011), St. Petersburg, Sept. 6–9, 2011, pp. 181–182.
  11. Mitchell C., Hu C., Bowler B., Drapeau D., Balch W. M., Estimating particulate inorganic carbon concentrations of the global ocean from ocean color measurements using a reflectance difference approach, J. Geophysical Research: Oceans, 2017, Vol. 122, DOI: 10.1002/2017JC013146.
  12. Mueller J. L., Ocean color spectra measured off the Oregon coast: Characteristic vectors, Applied Optics, 1976, Vol. 15, pp. 394–402.