Barry M. Gross

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The polarization discrimination technique we recently developed, shows that it is possible to separate the elastic scattering and the chlorophyll fluorescence signal from the water-leaving radiance by making use of the fact that the elastically scattered components are partially polarized, while the fluorescence signal is unpolarized. The technique has been(More)
Measurements of the underwater polarized light field were performed at different stations, atmospheric conditions and water compositions using a newly developed hyperspectral and multiangular polarimeter during a recent cruise in the coastal areas of New York Harbor - Sandy Hook, NJ region (USA). Results are presented for waters with chlorophyll(More)
2 = 0.85, while for the regional method, we apply results in τ MODIS = 1.02 τ AERONET + 0.04, R 2 = 0.92. This improved performance is maintained even for high-resolution retrieval down to 1.5 km with a regression of τ MODIS = 0.96 τ AERONET + 0.02, R 2 = 0.88. In addition, we show that this method can be extended to other urban scenes such as Mexico City(More)
Karenia brevis (K. brevis) blooms are of great interest and have been commonly reported throughout the Gulf of Mexico. In this study we propose a detection technique for blooms with low backscatter characteristics, which we name the Red Band Difference (RBD) technique, coupled with a selective K. brevis bloom classification technique, which we name the K.(More)
Retrieving the inherent optical properties of water from remote sensing multispectral reflectance measurements is difficult due to both the complex nature of the forward modeling and the inherent nonlinearity of the inverse problem. In such cases, neural network (NN) techniques have a long history in inverting complex nonlinear systems. The process we adopt(More)
The recently developed short wave infrared (SWIR) atmospheric correction algorithm for ocean color retrieval uses long wavelength channels to retrieve atmospheric parameters to avoid bright pixel contamination. However, this retrieval is highly sensitive to errors in the aerosol model, which is magnified by the higher variability of aerosols observed over(More)