A new approach to estimate the aerosol scattering ratios for the atmospheric correction of satellite remote sensing data in coastal regions
A new approach to estimate the aerosol scattering ratios for the atmospheric correction of satellite remote sensing data in coastal regions
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DOI：
10.1016/j.rse.2013.01.015
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发表时间：
2013-05
影响因子：
13.5
通讯作者：
Z. Mao;Jianyu Chen;Zengzhou Hao;D. Pan;B. Tao;Qiankun Zhu
中科院分区：
文献类型：
--
作者：
Z. Mao;Jianyu Chen;Zengzhou Hao;D. Pan;B. Tao;Qiankun Zhu
气溶胶散射反射率是卫星遥感数据大气改正中最不确定的项。可见光波段的数值取决于气溶胶散射率(epsilon光谱)。在两个近红外波段的出水反射率的暗像素假设下，估算了近红外波段的epsilon值，然后根据气溶胶模型确定了epsilon谱。这一假设通常对浑浊的沿海水域无效，导致卫星图像中被大气校正失败所掩盖的区域丢失。发展了一种新的方法来准确估计浑浊的沿海水域中的epsilon。这种方法是基于这样一种思想，即气溶胶散射反射率和epsilon值可以从现场测量的已知离水反射率中获得。根据候选气溶胶散射反射率的Angstrom定律，利用最佳非线性最小二乘拟合函数，通过选择离水反射率的查找表来确定离水反射率。在这种方法中，可以获得整个epsilon谱，并将其用于确定两个最接近的气溶胶模型，这两个模型用于对实际epsilon值进行内插。结果表明，用整个谱进行匹配比只用一个epsilon值得到的结果更可靠。利用模拟的大气顶部反射率、海景广视场传感器(SeaWiFS)图像和现场测量的气溶胶光学厚度对该方法的性能进行了评估。这种方法是基于气溶胶散射反射率服从Angstrom定律的假设，而不是标准的暗像素假设，称为ENLF模型。这一新假设适用于情况1和情况2的水域，甚至在陆地区域也是如此。因此，ENLF模式为卫星遥感数据大气改正的通用算法提供了一条潜在的途径。
Aerosol scattering reflectance is the most uncertain term to be determined in the atmospheric correction of satellite remote sensing data. The values in the visible bands depend on the aerosol scattering ratios (the epsilon spectrum). The epsilon value in the Near-infrared (NIR) band is estimated on the dark pixel assumption of the water-leaving reflectance in the two NIR bands and then the epsilon spectrum is determined from the aerosol models. This assumption usually becomes invalid for turbid coastal waters, leading to lost regions in the satellite imagery masked by the failure of the atmospheric correction. A new approach was developed to accurately estimate epsilon from turbid coastal waters. This method is based on the idea that the aerosol scattering reflectance and the epsilon values can be obtained from the known water-leaving reflectance of in situ measurements. The water-leaving reflectance is determined from the choice of a look-up table of the water-leaving reflectance based on the Angstrom law of the candidate aerosol scattering reflectance using the best non-linear least squares fit function. In this approach, the entire epsilon spectra can be obtained and used to determine the two closest aerosol models which are used to interpolate the actual epsilon values. It is demonstrated that the results from matching the entire spectra are more robust than that obtained from using only one epsilon value. The performance of the approach was evaluated using the simulated reflectance at the top of the atmosphere, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery, and in situ measured aerosol optical thickness. This approach is based on the assumption of the aerosol scattering reflectance following the Angstrom law instead of the standard dark pixel assumption, named as the ENLF model. This new assumption is valid for both Case 1 and Case 2 waters, even over terrestrial regions. Therefore, the ENLF model provides a potential approach for a universal algorithm of the atmospheric correction of satellite remote sensing data.