Fields of nonlinear regression models for ocean color remote sensing from space

Bruno Pelletier; Robert J. Frouin

doi:10.1117/12.576499

20 January 2005 Fields of nonlinear regression models for ocean color remote sensing from space

Bruno Pelletier, Robert J. Frouin

Proceedings Volume 5656, Active and Passive Remote Sensing of the Oceans; (2005) https://doi.org/10.1117/12.576499
Event: Fourth International Asia-Pacific Environmental Remote Sensing Symposium 2004: Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2004, Honolulu, Hawai'i, United States

Abstract

The remote sensing of ocean color, a problem that consists in retrieving one or several oceanic variables from top-of-atmosphere spectral reflectance, is considered as a collection of similar inverse problems continuously indexed by the angular variables influencing the observation process. A general solution is proposed in the form of a field of non-linear regression models over the set T of permitted values for the angular variables, i.e., as a map from T to some function space. Each value of the field is a regression model that performs a direct mapping from the top-of-atmosphere reflectance to the geophysical variable(s) of interest. A methodology based on ridge functions is developed to approximate this solution to an arbitrary accuracy, and is applied to the retrieval of the marine reflectance. The developed models are evaluated on synthetic data as well as on actual data originating from the SeaWiFS instrument. The retrievals are achieved with a good performance in terms of accuracy, robustness, and generalization capabilities, suggesting that the methodology might improve the inversion quality over existing techniques.

Citation Download Citation

Bruno Pelletier and Robert J. Frouin "Fields of nonlinear regression models for ocean color remote sensing from space", Proc. SPIE 5656, Active and Passive Remote Sensing of the Oceans, (20 January 2005); https://doi.org/10.1117/12.576499

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