Use of a neuro-variational inversion to retrieve aerosol parameters and ocean constituents from ocean color imagery

The retrieval of ocean constituents (OC) from satellite ocean color measurements is very sensitive to the atmospheric correction. Improved atmospheric correction algorithms, which simultaneously estimate OC and aerosol optical properties (AP), have recently been developed. Advanced programming techniques such as Neural Network can help us in implementing improved atmospheric correction algorithms in operational satellite data processing. The method is based on the combination of MLP and classical variational inversion in the visible bands. This procedure enables to retrieve OC, specially Chl-a from visible wavelengths. It consists in inverting the direct model to retrieve OC, by minimizing the distance between the observed and MLP-calculated Top Of Atmosphere reflectance. To perform this inversion, we have modelled the oceanic and atmospheric radiative transfer equations with respect to the AP and OC by using MLP. The accuracy is better than 7%. We have focused on the influence of the information on AP for the retrieval of OC with pseudo-data for weakly absorbing aerosols. We show that Chl-a can be retrieved with an error of 19.7% if we have a perfect knowledge of three AP. Finally, results for East Coast of the United States are presented.

[1]  H. Gordon,et al.  Removal of atmospheric effects from satellite imagery of the oceans. , 1978, Applied optics.

[2]  James W. Brown,et al.  A semianalytic radiance model of ocean color , 1988 .

[3]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[4]  S. Thiria,et al.  A neural network approach for modeling nonlinear transfer functions: Application for wind retrieval from spaceborne scatterometer data , 1993 .

[5]  Menghua Wang,et al.  Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: a preliminary algorithm. , 1994, Applied optics.

[6]  H. Gordon.  Atmospheric correction of ocean color imagery in the Earth Observing System era , 1997 .

[7]  H. Gordon,et al.  Remote sensing of ocean color and aerosol properties: resolving the issue of aerosol absorption. , 1997, Applied optics.

[8]  M. Kahru,et al.  Ocean Color Chlorophyll Algorithms for SEAWIFS , 1998 .

[9]  H. Gordon,et al.  Atmospheric correction of ocean color imagery: use of the junge power-law aerosol size distribution with variable refractive index to handle aerosol absorption. , 1998, Applied optics.

[10]  R. Chomko.  Atmospheric correction of ocean color imagery: Use of Junge power-law size distribution , 1999 .

[11]  S. Maritorena,et al.  Atmospheric correction of satellite ocean color imagery: the black pixel assumption. , 2000, Applied optics.

[12]  H. Gordon,et al.  Atmospheric Correction of Ocean Color Imagery: Test of the Spectral Optimization Algorithm with the Sea-Viewing Wide Field-of-View Sensor. , 2001, Applied optics.