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Estimation and Characterization of Physical and Inorganic Chemical Indicators of Water Quality Using SAR Images

机译:利用SAR图像估算和表征水质的物理和无机化学指标

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Recently, remote sensing is considering one of the most important tools in studies of water scattering and water characterization. Traditional methods for monitoring pollutants depended on optical satellite rather than Radar data. Thus, many of Water Quality Parameters (WQP) from optical imagery are still limited. In this paper, a new approach based on the TerraSAR-X images has been presented which it is used to map the region of interest and to estimate physical and chemical WQPs. This approach based on a Small Perturbation Model (SPM) for the electromagnetic scattering is applied by using the Elfouhaily spectrum. A series of inversions have been included in this model started by finding the reflectivity from backscattering coefficients which are calculated from SAR images. Another inversion has been applied to find dielectric constant from the calculation models of the reflectivity (in HH and W polarizations). Then, a Stogryn Debye formulation has been used to estimate temperature and salinity of water surface from SAR images. After many derivations we got a new model able to estimate temperature and salinity directly from backscattering coefficients obtained from radar images. Inorganic chemical parameters which are represented by Total Dissolved Salts (TDS) and the Electrical Conductivity (EC) are estimated directly from salinity. A tow dataset of instu data have been used to validate this work. The validation included a comparison between parameters measured in situ and those estimated from Terra SAR-X image.
机译:最近,遥感技术正在考虑研究水的散射和水的表征中最重要的工具之一。监测污染物的传统方法取决于光学卫星而不是雷达数据。因此,来自光学影像的许多水质参数(WQP)仍然受到限制。在本文中,提出了一种基于TerraSAR-X图像的新方法,该方法可用于绘制目标区域并估算物理和化学WQP。通过使用Elfouhaily频谱,采用了基于小扰动模型(SPM)的电磁散射方法。通过从由SAR图像计算出的反向散射系数中找到反射率,该模型中包含了一系列的反演。已应用另一种反演来从反射率的计算模型(在HH和W极化中)中找到介电常数。然后,使用Stogryn Debye公式从SAR图像估算水表面的温度和盐度。经过许多推导,我们得到了一个新模型,该模型能够直接从雷达图像获得的反向散射系数估算温度和盐度。由总溶解盐(TDS)和电导率(EC)表示的无机化学参数可以直接从盐度中估算出来。使用instu数据的两个数据集来验证这项工作。验证包括就地测量的参数与从Terra SAR-X图像估算的参数之间的比较。

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