Simultaneous retrieval of oceanic and atmospheric properties using satellite remote sensing measurements

Thomas Heinemann; Juergen Fischer

doi:10.1117/12.266385

6 February 1997 Simultaneous retrieval of oceanic and atmospheric properties using satellite remote sensing measurements

Thomas Heinemann, Juergen Fischer

Author Affiliations +

Proceedings Volume 2963, Ocean Optics XIII; (1997) https://doi.org/10.1117/12.266385
Event: Ocean Optics XIII, 1996, Halifax, Nova Scotia, Canada

Abstract

The retrieval of oceanic and atmospheric constituents from satellite measurements is usually performed separately. Near infrared radiances measured from satellite above open oceans contain only information on atmospheric parameters. Ocean color is measured in the visible. In order to perform an atmospheric correction the information on the atmosphere has to be extrapolated from the near infrared to the visible. Due to multiple scattering effects this extrapolation is subject of large errors. To overcome the problem a retrieval algorithm was developed which uses measurements in the visible as well as in the near infrared, to perform the atmospheric correction and to derive oceanic properties in one step. This algorithm is based on a neural network. The method was compared to a nonlinear regression scheme handling visible and near IR channels independently. Upward nadir radiances in the spectral bands of SeaWiFS were simulated by an ocean-atmosphere radiative transfer model for a set of open ocean waters and atmospheric conditions. The two algorithms were initialized and tested with these data in order to perform the retrieval of phytoplankton concentration and aerosol optical depth. A stability analysis has been applied to all results. Aerosol optical depth can be retrieved well by a linear regression scheme. For the phytoplankton retrieval the results for the neural network are more accurate and more stable according to randomly distributed errors. The regression method is less sensitive to correlated errors such as surface pressure changes but the higher stability according to noise still recommends the use of the neural network.

Citation Download Citation

Thomas Heinemann and Juergen Fischer "Simultaneous retrieval of oceanic and atmospheric properties using satellite remote sensing measurements", Proc. SPIE 2963, Ocean Optics XIII, (6 February 1997); https://doi.org/10.1117/12.266385

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