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Retrieval of Particle Scattering Coefficients and Concentrations by Genetic Algorithms in Stratified Lake Water

机译:基于遗传算法的分层湖水中颗粒物散射系数和浓度反演

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We retrieved the mass-specific scattering coefficient b*sm(λ) = 0.60·(λ/650)−1.82 of the inhomogeneous and optically complex water column of eastern Lake Constance in May 2012. In-situ measured and modelled remote-sensing reflectance Rrs(λ) were matched via a parameter search procedure using genetic algorithms. The optical modelling consisted of solving the azimuthally-averaged Radiative Transfer Equation, forced with in-situ suspended matter concentration (sm) data. b*sm(λ) was univocally determined at red wavelengths. In contrast, we encountered unresolved spectral ambiguity at blue wavelengths due to the absence of organic absorption in our dataset. Despite this, a surprisingly good sm retrieval regression is achieved (R2 > 0.95 with respect to independent data) using our b*sm(λ). Acquisition of accurate inherent optical properties in future field campaigns is needed to verify the estimated b*sm(λ) and related assumptions.
机译:我们检索了康斯坦茨湖东部非均匀且光学复杂水柱的质量比散射系数b * sm (λ)= 0.60·(λ/ 650) −1.82 于2012年5月进行。通过遗传算法通过参数搜索程序对现场测量和建模的遥感反射率R rs (λ)进行了匹配。光学建模包括求解方位角平均的辐射传递方程,并利用原位悬浮物浓度(sm)数据进行强迫。 b * sm (λ)是在红色波长下唯一确定的。相反,由于我们的数据集中没有有机吸收,我们在蓝色波长处遇到了无法解决的光谱模糊性。尽管如此,使用我们的b * sm (λ)却获得了令人惊讶的良好sm检索回归(相对于独立数据,R 2 sm (λ)和相关假设。

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