An optical tool for quantitative assessment of phycocyanin pigment concentration in cyanobacterial blooms within inland and marine environments

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• 作者：Theenathayalan Varunan ; Palanisamy Shanmugam ; ^{pshanmugam@iitm.ac.in}
• 关键词：Inland and marine environments ; Remote sensing ; Modeling ; Phycocyanin ; Optical assessment tool
• 刊名：Journal of Great Lakes Research
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：43
• 期：1
• 页码：32-49
• 全文大小：2839 K
• 卷排序：43

文摘

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.