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Bayesian Estimation of Optical Properties of Nearshore Estuarine Waters: A Gibbs Sampling Approach
By: Bagheri, S.; Michalopoulou, Z.-H.; Axe, L.;
2010 / IEEE
Description
This item was taken from the IEEE Periodical ' Bayesian Estimation of Optical Properties of Nearshore Estuarine Waters: A Gibbs Sampling Approach ' A novel approach is developed for the retrieval of inherent optical properties of coastal water, from which water-quality constituent concentrations can be obtained. The technique combines an analytical bio-optical model with statistical modeling for the formulation of posterior probability distributions of phytoplankton absorption, backscattering, and colored dissolved organic matter absorption; a Gibbs Sampler is employed for optimization. In contrast to other methods that typically provide point estimates of the unknown parameters, the proposed method estimates posterior distributions of the parameters, quantifying the uncertainty present in the problem and revealing correlation patterns. The method is tested successfully on synthetic reflectance data and real data measured in situ in the Hudson/Raritan Estuary of New York-New Jersey.
Related Topics
Bayes Methods
Light Absorption
Light Scattering
Microorganisms
Ocean Chemistry
Oceanographic Techniques
Organic Compounds
Sampling Methods
Underwater Optics
Usa
Bayesian Estimation
Nearshore Estuarine Water Optical Properties
Gibbs Sampling
Coastal Water Optical Properties
Water Quality Constituent Concentrations
Statistical Modeling
Posterior Probability Distribution
Phytoplankton Absorption
Phytoplankton Backscattering
Colored Dissolved Organic Matter Absorption
Hudson-raritan Estuary
New York
New Jersey
Bayesian Methods
Water
Sampling Methods
Biomedical Optical Imaging
Absorption
Sea Measurements
Analytical Models
Probability Distribution
Backscatter
Testing
Optical Water-quality Parameters
Backscattering
Bayesian Modeling
Water Quality
Signal Processing And Analysis
Geoscience
Engineering
Analytical Bio-optical Model