Neural network method to correct bidirectional effects in water-leaving radiance

Applied Optics
Yongzhen FanKnut Stamnes

Abstract

Ocean color algorithms that rely on "atmospherically corrected" nadir water-leaving radiances to infer information about marine constituents such as the chlorophyll concentration depend on a reliable method to convert the angle-dependent measured radiances from the observation direction to the nadir direction. It is also important to convert the measured radiances to the nadir direction when comparing and merging products from different satellite missions. The standard correction method developed by Morel and coworkers requires knowledge of the chlorophyll concentration. Also, the standard method was developed based on the Case 1 (open ocean) assumption, which makes it unsuitable for Case 2 situations such as turbid coastal waters. We introduce a neural network method to convert the angle-dependent water-leaving radiance (or the corresponding remote sensing reflectance) from the observation direction to the nadir direction. This method relies on neither an "atmospheric correction" nor prior knowledge of the water constituents or the inherent optical properties. It directly converts the remote sensing reflectance from an arbitrary slanted viewing direction to the nadir direction by using a trained neural network. This method is ...Continue Reading

References

Mar 20, 2002·Applied Optics·Curtis D MobleyEmmanuel Boss
May 30, 2005·Optics Express·Kenneth Voss, Albert Chapin
Nov 20, 1993·Applied Optics·A Morel, B Gentili
Mar 29, 2012·Optics Express·Arthur C R GleasonZhong-Ping Lee

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