首页> 外文期刊>Journal of great lakes research >An optical tool for quantitative assessment of phycocyanin pigment concentration in cyanobacterial blooms within inland and marine environments
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An optical tool for quantitative assessment of phycocyanin pigment concentration in cyanobacterial blooms within inland and marine environments

机译:用于定量评估内陆和海洋环境中蓝藻水华中藻蓝蛋白色素浓度的光学工具

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Quantitative assessment of the pigment phycocyanin (PC) in cyanobacterial blooms is essential to assess their abundance and distribution and consequently aid their management in many recreational waters within inland and coastal environments. In contrast to the open-ocean waters, these water bodies are very complex with a pronounced heterogeneity of their optical properties, and hence accurate retrieval of the water-leaving radiances and PC concentration from satellite observations is notoriously difficult with existing algorithms. In the present study, a new inversion algorithm is developed as a rapid cyanobacteria bloom assessment method and its retrievals of PC are compared with in-situ and satellite observations and those from a previously reported inversion algorithm. The new algorithm estimates PC concentration on the basis of the unique absorption feature of phycocyanin at 620 nm which is isolated from the total pigment absorption by taking advantage of the well recognized absorption and reflectance features in the red and near-infrared (NIR) wavelengths (less impacted by the influences of the overlapping absorption signatures of the mixture constituents and pigment packaging). The by-products of this work include chl-a concentration and predictions from reflectance data to monitor the cyanobacterial component and non-cyanobacterial component of the phytoplankton assemblage and to evaluate PC:Chl-a pigment weight ratios for specific water types. Initial validation of the algorithm was performed using in-situ field data in turbid productive waters dominated by phycocyanin and other pigments, yielding coefficients of determination and slope close to unity and mean errors less than a few percent. These results suggest that the algorithm could be used as a rapid assessment tool for the remote-sensing assessment of the spatial distribution and relative abundance of cyanobacterial blooms in many regional water bodies. (C) 2016 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.
机译:蓝藻花中色素藻蓝蛋白(PC)的定量评估对于评估其含量和分布至关重要,因此有助于在内陆和沿海环境中许多休闲水域中对其进行管理。与开阔海洋水域相比,这些水体非常复杂,其光学特性具有明显的异质性,因此,使用现有算法很难准确地从卫星观测结果中准确获取出水辐射率和PC浓度。在本研究中,开发了一种新的反演算法,作为快速的蓝藻水华评估方法,并将其PC检索与实地和卫星观测以及先前报道的反演算法进行了比较。新算法根据藻蓝蛋白在620 nm处的独特吸收特征估算PC浓度,该特征通过利用在红色和近红外(NIR)波长下公认的吸收和反射特征而与总色素吸收隔离开来(较少受混合物成分和颜料包装的重叠吸收特征的影响。这项工作的副产品包括chl-a浓度和反射率数据的预测,以监测浮游植物组合中的蓝细菌成分和非蓝细菌成分,并评估特定水类型的PC:Chl-a颜料重量比。该算法的初始验证是在以藻蓝蛋白和其他色素为主的混浊生产水中使用现场数据进行的,确定系数和斜率接近于1,平均误差小于百分之几。这些结果表明,该算法可以用作对许多区域水体中蓝藻水华的空间分布和相对丰度进行遥感评估的快速评估工具。 (C)2016年国际大湖研究协会。由Elsevier B.V.发布。保留所有权利。

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