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Effect of Bio-Optical Parameter Variability and Uncertainties in Reflectance Measurements on the Remote Estimation of Chlorophyll-a Concentration in Turbid Productive Waters: Modeling Results

机译:生物光学参数变异性和反射率测量不确定度对浊水生产水中叶绿素a浓度远程估算的影响:模拟结果

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摘要

Most algorithms for retrieving chlorophyll-a concentration (Chla) from reflectance spectra assume that bio-optical parameters such as the phytoplankton specific absorption coefficient (aφ*) or the chlorophyll-a fluorescence quantum yield (η) are constant. Yet there exist experimental data showing large ranges of variability for these quantities. The main objective of this study was to analyze the sensitivity of two Chla algorithms to variations in bio-optical parameters and to uncertainties in reflectance measurements. These algorithms are specifically designed for turbid productive waters and are based on red and near-infrared reflectances. By means of simulated data, it is shown that the spectral regions where the algorithms are maximally sensitive to Chla overlap those of maximal sensitivity to variations in the above bio-optical parameters. Thus, to increase the accuracy of Chla retrieval, we suggest using spectral regions where the algorithms are less sensitive to Chla, but also less sensitive to these interferences. aφ* appeared to be one of the most important sources of error for retrieving Chla. However, when the phytoplankton backscattering coefficient (bb,φ) dominates the total backscattering, as is likely during algal blooms, variations in the specific (bb,φ) may introduce large systematic uncertainties in Chla estimation. Also, uncertainties in reflectance measurements, which are due to incomplete atmospheric correction or reflected skylight removal, seem to affect considerably the accuracy of Chla estimation. Instead, variations in other bio-optical parameters, such as η or the specific backscattering coefficient of total suspended particles, appear to have minor importance. Suggestions regarding the optimal band locations to be used in the above algorithms are finally provided.
机译:从反射光谱中检索叶绿素a浓度(Chla)的大多数算法都假定生物光学参数(例如浮游植物比吸收系数(aφ*)或叶绿素a荧光量子产率(η))是恒定的。然而,已有实验数据显示这些量的大范围可变性。这项研究的主要目的是分析两种Chla算法对生物光学参数变化和反射率测量不确定度的敏感性。这些算法是专门为混浊的生产水设计的,并且基于红色和近红外反射率。通过模拟数据显示,算法对Chla最大敏感的光谱区域与对上述生物光学参数变化最大敏感的光谱区域重叠。因此,为了提高Chla检索的准确性,我们建议使用频谱区域,在这些区域中算法对Chla的敏感性较低,但对这些干扰的敏感性较低。 aφ*似乎是检索Chla的最重要错误来源之一。但是,当浮游植物的背向散射系数(bb,φ)占总背向散射的主要部分时(如藻华期间),比值(bb,φ)的变化可能会在Chla估计中引入较大的系统不确定性。同样,由于大气校正不完全或反射的天窗去除而导致的反射率测量不确定性似乎会显着影响Chla估算的准确性。取而代之的是,其他生物光学参数(例如η或总悬浮颗粒的特定反向散射系数)的变化似乎没有那么重要。最后提供了有关在上述算法中使用的最佳频带位置的建议。

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