Visible and Infrared Remote Sensing of the White Sea Bio-Geo-Chemistry and Hydrology

  • D. Pozdnyakov
  • A. Korosov
  • L. Pettersson

A new operational non-satellite-specific algorithm for a Simul taneous retrieval of contents of phytoplankton chlorophyll (chl), suspended minerals (sm) and dissolved organic carbon (doc) from space sensor data, was employed to monitor the surface expressions of some biotic and abiotic processes in the White Sea (WS). A special technique has been de- veloped to reconstruct the seasonal variations of the above substances in pixels occasionally masked by cloudiness. The developed software package provided a means to obtain the series of intra-annual spatial and temporal variations of chl, sm, doc and sea surface temperature throughout the WS from SeaWiFS and AVHRR, respectively. The observed variations are controlled by (a) the dynamics of water turbidity and opacity due to seasonal variations in the content of sm and doc driven by the river discharge varying influence, and (b) thermo-hydrodynamic processes encompassing water density currents, tides, upwellings, fronts, etc.


River Discharge Frontal Zone Advanced Very High Resolution Radiometer Advanced Very High Resolution Radiometer Tidal Front 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Filatov N, Pozdnyakov D, Johannessen O, Pettersson L, Bobylev L, eds (2005) White Sea: its marine environment and ecosystem dynamics influenced by global change. Springer-Praxis, ChichesterGoogle Scholar
  2. Greengerg A, Clesceri L, Eaton A, eds (1992) Standard methods for the examination of marine water and freshwater. Elsevier Pub., AmsterdamGoogle Scholar
  3. Jerome J, Bukata R, Miller J (1996) Remote sensing reflectance and its relationship to optical properties of natural water. Int. J. Rem. Sens., 17: 43-52CrossRefGoogle Scholar
  4. Kidwell KB (1997) Noaa Polar Orbiter Data Users Guide. U.S. Department of Commerce, Suitland USAGoogle Scholar
  5. Korosov AA, Pozdnyakov DV, Filatov NN, Grassl H, Mazourov AA, Loupyan EA, Ionov VV (2006) A satellite data-based study of seasonal and spatial variations of some ecoparameters in Lake Ladoga. Earth Obs. Rem Sens. 5: 76-85 (in Russian)Google Scholar
  6. Morel A, Prieur L (1977) Analysis of variations in ocean colour. Limnol. Ocean-ogr. 22: 709-722.CrossRefGoogle Scholar
  7. Pozdnyakov D, Grassl H (2003) Colour of Inland and Coastal Waters: A methodology for its Interpretation. Springer-Praxis, ChichesterGoogle Scholar
  8. Pozdnyakov D, Korosov A, Grassl H, Pettersson L (2005) An advanced algorithm for operational retrieval of water quality from satellite data in the visible. Int. J. Rem. Sens. 26: 2669-2688CrossRefGoogle Scholar
  9. Sapozhnikov V, ed (1994) Comprehensive Studies of the White Sea Ecosystem. Russian Seas Ecology Series, Publ. All-Russia Res. Inst. f Fishery and Oceanogr, Moscow (in Russian)Google Scholar

Copyright information

© Springer Science+Business Media B.V 2008

Authors and Affiliations

  • D. Pozdnyakov
    • 1
  • A. Korosov
    • 1
  • L. Pettersson
    • 2
  1. 1.Nansen International Environmental and Remote Sensing CentreRussia
  2. 2.Nansen Environmental and Remote Sensing CentreNorway

Personalised recommendations