Empirical nonlinear determination of the diffuse attenuation coefficient Kd(490) in coastal waters from ocean color images

Cédric Jamet; Hubert Loisel; David Dessailly

doi:10.1117/12.869730

3 November 2010 Empirical nonlinear determination of the diffuse attenuation coefficient Kd(490) in coastal waters from ocean color images

Cédric Jamet, Hubert Loisel, David Dessailly

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Proceedings Volume 7858, Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment; 785806 (2010) https://doi.org/10.1117/12.869730
Event: SPIE Asia-Pacific Remote Sensing, 2010, Incheon, Korea, Republic of

Abstract

The fine-scale study of the diffuse attenuation coefficient, K_d(λ), of the spectral solar downward irradiance is only feasible by ocean color remote sensing. Several empirical and semi-analytical methods exist. However, most of tthese models are generally applicable for clear open ocean waters. They show limitations when applied to coastal waters. A new empirical method based on neural networks has been developed using a relationship between the remote-sensing reflectances between 412 and 670 nm and K_d(490), for the SeaWiFS ocean color remote sensor. The architecture of the neural network has been defined using synthetical and in situ dataset and the optimal design is a tow hidden layer neural network with 4 neurons of the first layer and three on the second layer. The comparison with the SeaWiFS empirical algorithms shows similar retrievals accuracies for low values of K_d(490) (i.e. <0.20 m^-1) and better estimates for greater values of and K_d(490). The new model is suitable for open water but also for turbid waters and does not show the limitations of the empirical method. The new model is more general that the empirical methods.

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Cédric Jamet, Hubert Loisel, and David Dessailly "Empirical nonlinear determination of the diffuse attenuation coefficient Kd(490) in coastal waters from ocean color images", Proc. SPIE 7858, Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment, 785806 (3 November 2010); https://doi.org/10.1117/12.869730

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