An optimal algorithm for the retrieval of chlorophyll, suspended sediments and gelbstoff of case Ⅱ waters in the Pearl River estuary was established with the optical parameters derived from the in-situ data obtained ...An optimal algorithm for the retrieval of chlorophyll, suspended sediments and gelbstoff of case Ⅱ waters in the Pearl River estuary was established with the optical parameters derived from the in-situ data obtained in Jan. 2003 in the same area. And then, the chlorophyll, suspended sediments and gelbstoff of the SeaWiFS pixels on Jan. 29, 2003 corresponding to the in-situ sites of Jan. 25 and 26, 2003 were synchronously retrieved, with average relative errors of 14.9%, 12.1% and 13.6% for chlorophyll, suspended sediments and gelbstoff, respectively. The research results indicated that the optimal retrieval algorithm established here was relatively fit for the retrieval of the chlorophyll, suspended sediments and gelbstoff of case Ⅱ waters in the Pearl River estuary, and had quite good retrieval accuracy.展开更多
In the present paper, a method is proposed to improve the performance of Artificial Neural Network (ANN) based algorithms for the retrieval of oceanic constituents in Case Ⅱ waters. The ANN-based algorithms have been...In the present paper, a method is proposed to improve the performance of Artificial Neural Network (ANN) based algorithms for the retrieval of oceanic constituents in Case Ⅱ waters. The ANN-based algorithms have been developed based on a constraint condition, which represents, to a certain degree, the correlation between suspended particulate matter (SPM) and pigment (CHL), coloured dissolved organic matter (CDOM) and CHL, as well as CDOM and SPM, found in Case Ⅱ waters. Compared with the ANN-based algorithm developed without a constraint condition, the performance of ANN-based algorithms developed with a constraint conditions is much better for the retrieval of CHL and CDOM, especially in the case of high noise levels; however, there is not significant improvement for the retrieval of SPM.展开更多
Phycocyanin, a functional protein found in blue-green algae, with characteristic absorption peak around 620 nm, can be used to detect the quantity of blue-green algae in waters. Spectral characteristics of phycocyanin...Phycocyanin, a functional protein found in blue-green algae, with characteristic absorption peak around 620 nm, can be used to detect the quantity of blue-green algae in waters. Spectral characteristics of phycocyanin were studied by measuring hyperspectral water leaving radiance and absorption curve, and the results showed that the absorption peak of phycocyanin around 620 nm was evident in the curve of water leaving radiance. Bio-optical model of phycocyanin was set up with analytical methods and calibrated with error analysis. Linear relationship between phycocyanin concentration measured and that retrieved with calibrated bio-optical model (R = 0.755) was better than that retrieved with the band ratio of 709 nm/620 nm (R = 0.729), which proved that the calibration was neces-sary for improving the accuracy of phycocyanin concentration.展开更多
文摘An optimal algorithm for the retrieval of chlorophyll, suspended sediments and gelbstoff of case Ⅱ waters in the Pearl River estuary was established with the optical parameters derived from the in-situ data obtained in Jan. 2003 in the same area. And then, the chlorophyll, suspended sediments and gelbstoff of the SeaWiFS pixels on Jan. 29, 2003 corresponding to the in-situ sites of Jan. 25 and 26, 2003 were synchronously retrieved, with average relative errors of 14.9%, 12.1% and 13.6% for chlorophyll, suspended sediments and gelbstoff, respectively. The research results indicated that the optimal retrieval algorithm established here was relatively fit for the retrieval of the chlorophyll, suspended sediments and gelbstoff of case Ⅱ waters in the Pearl River estuary, and had quite good retrieval accuracy.
文摘In the present paper, a method is proposed to improve the performance of Artificial Neural Network (ANN) based algorithms for the retrieval of oceanic constituents in Case Ⅱ waters. The ANN-based algorithms have been developed based on a constraint condition, which represents, to a certain degree, the correlation between suspended particulate matter (SPM) and pigment (CHL), coloured dissolved organic matter (CDOM) and CHL, as well as CDOM and SPM, found in Case Ⅱ waters. Compared with the ANN-based algorithm developed without a constraint condition, the performance of ANN-based algorithms developed with a constraint conditions is much better for the retrieval of CHL and CDOM, especially in the case of high noise levels; however, there is not significant improvement for the retrieval of SPM.
基金Acknowledgements The authors would like to thank Dr. Zhang Ytmlin for measuring absorption of blue-green algae, and Zhang Xiaoyu, Zhang Xiaofeng, Liu Tao for field measurements. This work was supported by the National Natural Science Foundation of China （Grant No. 40576078）, and Natural Science Foundation of Guangdong Province （Grant No. 5003685）.
文摘Phycocyanin, a functional protein found in blue-green algae, with characteristic absorption peak around 620 nm, can be used to detect the quantity of blue-green algae in waters. Spectral characteristics of phycocyanin were studied by measuring hyperspectral water leaving radiance and absorption curve, and the results showed that the absorption peak of phycocyanin around 620 nm was evident in the curve of water leaving radiance. Bio-optical model of phycocyanin was set up with analytical methods and calibrated with error analysis. Linear relationship between phycocyanin concentration measured and that retrieved with calibrated bio-optical model (R = 0.755) was better than that retrieved with the band ratio of 709 nm/620 nm (R = 0.729), which proved that the calibration was neces-sary for improving the accuracy of phycocyanin concentration.
