Algorithms for Evaluation of Biooptical Characteristics in the Gulf of Finland Using Empirical Orthogonal Functions

S. Vazyulya, S. Sheberstov
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Abstract

The paper presents the results of testing the possibility of using empirical orthogonal functions to develop algorithms for estimating the concentration of chlorophyll a and suspended matter, the biomass of cyanobacteria in the eastern part of the Gulf of Finland. To develop the algorithms, we used an array of data from field measurements of the subsurface radiance reflectance in 2012–2014, carried out simultaneously with the determination of bio-optical characteristics. It turned out that in the case of the concentration of chlorophyll a and suspended matter, such algorithms can be created not only using the hyperspectral radiance reflectance, but also for the spectral channels of satellite color scanners MODIS and OLCI. An estimation of the cyanobacteria biomass with the empirical orthogonal functions method is not applicable in the case of using satellite channels. A study of the possibility of the most prone to atmospheric correction errors shortwave MODIS channels exclusion was also made. It turned out that the concentration of chlorophyll a is more sensitive to such exclusion than the concentration of suspended matter. Validation on a MODIS data showed that empirical orthogonal functions algorithms give results no worse than regression ones.
用经验正交函数评价芬兰湾生物光学特性的算法
本文介绍了使用经验正交函数开发算法来估计芬兰湾东部叶绿素a和悬浮物浓度以及蓝藻生物量的可能性的测试结果。为了开发算法,我们使用了2012-2014年地下辐射反射率的现场测量数据,同时确定了生物光学特性。结果表明,在叶绿素a和悬浮物浓度的情况下,不仅可以利用高光谱辐射反射率,还可以利用卫星彩色扫描仪MODIS和OLCI的光谱通道建立这样的算法。在使用卫星通道的情况下,用经验正交函数法估计蓝藻生物量是不适用的。对最容易产生大气校正误差的短波MODIS信道排除的可能性进行了研究。结果表明,叶绿素a的浓度比悬浮物的浓度对这种排斥更为敏感。对MODIS数据的验证表明,经验正交函数算法的结果并不差于回归算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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