Wang Gui-Fen, Cao Wen-Xi, Yang Ding-Tian, Zhao Jun
LED Laboratory, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2009 Jan;29(1):201-6.
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.
基于浮游植物和非藻类颗粒各自的光谱关系,建立了一个估算它们对总颗粒吸收系数贡献的模型,并使用约束非线性优化代码实现光谱分解。在南海北部秋季的两次航次中,采用滤垫法测量了包括浮游植物和非藻类颗粒在内的总颗粒物的光谱吸收。利用2004年收集的数据集,研究了颗粒吸收系数的光谱关系,结果表明,各波段浮游植物吸收系数可用aph(443)的二阶二次方程很好地表示;非藻类颗粒吸收(aNAP(λ))可用简单指数函数成功建模。基于这些光谱关系,我们开发了这个划分模型。该模型使用2005年从同一区域获得的浮游植物和非藻类物质的独立测量吸收值进行测试。测试结果表明,计算得到的浮游植物和非藻类颗粒的光谱吸收系数与原位测量值一致。计算得到的浮游植物吸收系数与测量值之间具有良好的相关性,决定系数(r2)高于0.97,斜率约为1.0;在443、490和683nm等主要吸收波段,RMSE值可控制在17%以内。与Bricaud等人和Oubelkheir等人现有的另外两个模型相比,该方法在本地应用中具有许多优势。此外,该模型不需要任何关于色素浓度的信息,所选光谱波段与海洋颜色卫星传感器一致。该方法还可用于总吸收系数分解,为从原位测量和海洋颜色遥感数据中反演浮游植物吸收提供了很多见解。