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
A practical algorithm of atmospheric correction for turbid coastal and inland waters is provided. The presentalgorithm uses the property that the water-leaving radiance at 412 nm increases very little with the increas...A practical algorithm of atmospheric correction for turbid coastal and inland waters is provided. The presentalgorithm uses the property that the water-leaving radiance at 412 nm increases very little with the increasing of waterturbidity. Thus, in very turbid coastal and inland waters, the radiance at 412 nm can be used to estimate the aerosolscattering radiance at 865 nm. The performance of the new algorithm is validated with simulation for several cases. Itis found that the retrieved remotely sensed reflectance is usually with error less than 10% for the first six bands ofSeaWiFS. This new algorithm is also tested under various atmospheric conditions in the Changjiang River Estuaryand the Hangzhou Bay where the sediment concentration is very high and the standard SeaWiFS atmosphericcorrection algorithm creates a mask due to atmospheric correction failure. The result proves the efficiency of thissimple algorithm in reducing the errors of the water-leaving radiance retrieving using SeaWiFS satellite data.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This study was supported by the National“863”Project of China under contract No.2002AA639490 and No.2002AA639220.
文摘A practical algorithm of atmospheric correction for turbid coastal and inland waters is provided. The presentalgorithm uses the property that the water-leaving radiance at 412 nm increases very little with the increasing of waterturbidity. Thus, in very turbid coastal and inland waters, the radiance at 412 nm can be used to estimate the aerosolscattering radiance at 865 nm. The performance of the new algorithm is validated with simulation for several cases. Itis found that the retrieved remotely sensed reflectance is usually with error less than 10% for the first six bands ofSeaWiFS. This new algorithm is also tested under various atmospheric conditions in the Changjiang River Estuaryand the Hangzhou Bay where the sediment concentration is very high and the standard SeaWiFS atmosphericcorrection algorithm creates a mask due to atmospheric correction failure. The result proves the efficiency of thissimple algorithm in reducing the errors of the water-leaving radiance retrieving using SeaWiFS satellite data.
