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1.
Guang Pu Xue Yu Guang Pu Fen Xi ; 31(7): 1912-6, 2011 Jul.
Article in Chinese | MEDLINE | ID: mdl-21942050

ABSTRACT

Water column correction has been a substantial challenge for remote sensing. In order to improve the accuracy of coastal ocean monitoring where optical properties are complex, optical property of shallow water at Sanya Bay and the suitable water column correction algorithms were studies in the present paper. The authors extracted the bottom reflectance without water column effects by using a water column correction algorithm which is based on the simulation of the underwater light field in idealized water. And we compared the results which were calculated by the model and Christian's model respectively. Based on a detailed analysis, we concluded that: Because the optical properties of Sanya Bay are complex and vary greatly with location, Christian's model lost its advantage in the area. Conversely, the bottom reflectance calculating by the algorithm based on the simulation of the underwater light field in idealized water agreed well with in situ measured bottom reflectance, although the reflectance was lower than in situ measured reflectance value between 400 and 500 nm. So, it is reasonable to extract bottom information by using the water column correction algorithm in local bay area where optical properties are complex.

2.
Guang Pu Xue Yu Guang Pu Fen Xi ; 29(1): 201-6, 2009 Jan.
Article in Chinese | MEDLINE | ID: mdl-19385239

ABSTRACT

A model for estimating the contributions of phytoplankton and nonalgal particles to the total particulate absorption coefficient was developed based on their separate spectral relationships, and a constrained nonlinear optimization code was used to realize the spectral decomposition. The spectral absorption of total particulate matter including phytoplankton and nonalgal particles was measured using the filter-pad method during two cruises in autumn in Northern South China Sea. Using the dataset collected in 2004, the spectral relationships of particle absorption coefficients were examined and the results showed that the phytoplankton absorption coefficients at various wavebands could be well expressed by aph (443) as the second-order quadratic equations; and the nonalgal particle absorption (aNAP(lambda)) could be successfully modeled with the simple exponential function. Based on these spectral relationships, we developed this partition model. The model was tested using the independently measured absorption by phytoplankton and nonalgal materials which were obtained in 2005 from the same area. The test results showed that the computed spectral absorption coefficients of phytoplankton and nonalgal particles were consistent with in situ measurement. Good correlations were fo und between the comput ed phytoplankton absorption coefficient and the measured value,with the determination coefficients (r2) being higher than 0.97 and slopes being around 1.0; and the RMSE values could be controlled within 17% over the main absorption wavebands such as 443, 490 and 683 nm. Compared with the other two existing models from Bricaud et al. and Oubelkheir et al., this method shows many advantages for local applications. Moreover, this model does not need any information about pigment concentrations and the selected spectral bands are consistent with the ocean color satellite sensor. This method could also be used in the total absorption coefficient decomposition which provides much insight into the phytoplankton absorption retrieval from in situ measurement and ocean color remote sensing data.

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