TY - JOUR
T1 - Bayesian estimation of optical properties of nearshore estuarine waters
T2 - A gibbs sampling approach
AU - Michalopoulou, Zoi Heleni
AU - Bagheri, Sima
AU - Axe, Lisa
N1 - Funding Information:
The authors would like to thank the NSF MRI program for the computing support.
Funding Information:
Manuscript received November 19, 2008; revised May 29, 2009 and July 13, 2009. First published September 29, 2009; current version published February 24, 2010. This work was supported by the National Science Foundation under Grant SBE 0547427.
PY - 2010
Y1 - 2010
N2 - A novel approach is developed for the retrieval of inherent optical properties of coastal water, from which waterquality 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 datameasured in situ in the Hudson/Raritan Estuary of New York-New Jersey.
AB - A novel approach is developed for the retrieval of inherent optical properties of coastal water, from which waterquality 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 datameasured in situ in the Hudson/Raritan Estuary of New York-New Jersey.
KW - Backscattering
KW - Bayesian modeling
KW - Optical water-quality parameters
UR - http://www.scopus.com/inward/record.url?scp=79957662477&partnerID=8YFLogxK
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U2 - 10.1109/TGRS.2009.2028689
DO - 10.1109/TGRS.2009.2028689
M3 - Article
AN - SCOPUS:79957662477
SN - 0196-2892
VL - 48
SP - 1579
EP - 1587
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 3 PART2
M1 - 2028689
ER -