Paper
20 November 2006 A stochastic technique for remote sensing of ocean color
Author Affiliations +
Proceedings Volume 6406, Remote Sensing of the Marine Environment; 640602 (2006) https://doi.org/10.1117/12.697869
Event: SPIE Asia-Pacific Remote Sensing, 2006, Goa, India
Abstract
Remote sensing of ocean color from space aims at retrieving from a noisy top-of-atmosphere radiance the values taken by some relevant quantities like the chlorophyll-a concentration or the marine reflectance. From a mathematical perspective, it is an ill-posed inverse problem with a highly nonlinear operator. Few techniques are available in the case of a nonlinear inverse problem; even its theoretical study is far from easy, yet some techniques may be used in a practical setting when the noise distribution is known. However in the case of ocean color remote sensing, the noise encompasses several types of error owing to the forward operator approximation (radiative transfer model) as well as to calibration and pure measurement noise. Hence the noise distribution is unknown. In this work, a stochastic technique is proposed to first infer a noise distribution, which is next used to retrieve the marine reflectance in a least-square prediction setting by a regression model. The methodology is illustrated on actual data originating from the SeaWiFS sensor.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert Frouin and Bruno Pelletier "A stochastic technique for remote sensing of ocean color", Proc. SPIE 6406, Remote Sensing of the Marine Environment, 640602 (20 November 2006); https://doi.org/10.1117/12.697869
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KEYWORDS
Reflectivity

Data modeling

Atmospheric modeling

Coastal modeling

Oceanography

Aerosols

Inverse problems

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