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Retrieval of Inherent Optical Properties for Turbid Inland Waters From Remote-Sensing Reflectance

机译:通过遥感反射反演内陆浑浊水的固有光学性质

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Remote estimation of inherent optical properties (IOPs) for water bodies cannot only provide indicators of water quality, but also be used in the study on biological and biogeochemical processes of waters. The quasi-analytical algorithm (QAA) is a simple and effective method to retrieve IOPs from remote-sensing reflectance $(R_{rm rs})$. The QAA has been widely validated and applied in oceans, but its application in inland waters is far less extensive. In this paper, the QAA was enhanced to retrieve IOPs for turbid inland waters based on the bandwidths of Medium Resolution Imaging Spectrometer (MERIS). The enhancement was achieved by proposing a semi-analytical model to estimate the spectral slope of particle backscattering, as well as a novel estimation model for phytoplankton absorption coefficient at 443 nm. Two data sets (i.e., noise-free synthetic data and in-situ data) were collected to assess the performance of the enhanced algorithm. Results show that the algorithm yields almost error-free estimations for total absorption and backscattering coefficients and estimations for phytoplankton absorption at 443 nm with acceptable accuracy in the case of synthetic data set. For the in-situ data set, the algorithm retrieves the total absorption coefficients (ranging 0.337–8.331 $hbox{m}^{-1}$) with root-mean-square-error in log scale (RMSE) and bias in log scale lower than 0.130 and 0.094, respectively, and phytoplankton absorption at 443 nm (ranging 0.378–4.669 $hbox{m}^{-1}$) with RMSE and bias in log scale of 0.151 and 0.096, respectively. These results indicate the potential of the enhanced QAA to accurately retrieve the IOPs from MERIS satellite observations for inland waters.
机译:远程估算水体的固有光学性质(IOP)不仅可以提供水质指标​​,而且可以用于研究水的生物和生物地球化学过程。准分析算法(QAA)是一种从遥感反射率中检索IOP的简单有效的方法 $(R_ {rm rs})$ 。 QAA已得到广泛验证,并已在海洋中应用,但其在内陆水域中的应用范围却远远不够。在本文中,基于中分辨率成像光谱仪(MERIS)的带宽,对QAA进行了增强,以检索混浊内陆水域的IOP。通过提出一个半分析模型来估计粒子反向散射的光谱斜率,以及一个新的在443 nm处浮游植物吸收系数的估计模型,可以实现这种增强。收集了两个数据集(即无噪声合成数据和原位数据)以评估增强算法的性能。结果表明,在合成数据集的情况下,该算法几乎可以无误差地估算出总吸收系数和反向散射系数以及443 nm处浮游植物吸收的估算值。对于原位数据集,该算法将检索总吸收系数(范围为0.337–8.331 $ hbox {m} ^ {-1} $ ),其对数标度(RMSE)的均方根误差和对数标度的偏差分别小于0.130和0.094,浮游植物在443 nm处的吸收(范围为0.378–4.669 $ hbox {m} ^ {-1} $ ),RMSE和对数刻度偏差分别为0.151和0.096。这些结果表明,增强型QAA可以从MERIS卫星观测结果中准确检索内陆水域的IOP。

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