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Improving low-quality satellite remote sensing reflectance at blue bands over coastal and inland waters
Remote Sensing of Environment ( IF 13.5 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.rse.2020.112029
Jianwei Wei , Xiaolong Yu , Zhongping Lee , Menghua Wang , Lide Jiang

Abstract The satellite remote sensing reflectance (Rrs(λ)) at two short blue bands (410 or 412 nm and 443 nm) are prone to large uncertainties in coastal and inland waters, prohibiting algorithms from generating reliable ocean color products associated with these bands. In this study, we developed an algorithm to estimate Rrs(41×) and Rrs(443) when the satellite Rrs(λ) in blue bands suffer from large uncertainties. The algorithm first determines the Rrs(λ) spectral shape from the satellite-measured Rrs(λ) values at three wavelengths of 48× (486, 488, or 490), 55× (547, 551, or 555), and 67× (667, 670, or 671) nm. The algorithm then derives Rrs(41×) and Rrs(443) from the estimated Rrs(λ) spectral shape with algebraic formulations. We assessed the algorithm performance with satellite (SeaWiFS, MODISA, and VIIRS-SNPP) and in situ Rrs(λ) matchups from global waters. It is shown that the uncertainties of estimated Rrs(41×) and Rrs(443) are substantially smaller than the original satellite products when applicable. Besides, implementation of the algorithm contributes to a significant increase in the number of utilizable Rrs(41×) and Rrs(443) values. The algorithm is relatively stable and is best applicable to the satellite Rrs(λ) spectra for which the Rrs(48×) and Rrs(55×) measurements are subject to small uncertainties. The demonstrations support the application of the blue-band estimation algorithm to a wide range of coastal waters.

中文翻译:

改善沿海和内陆水域蓝色波段的低质量卫星遥感反射率

摘要 两个短蓝色波段(410 或 412 nm 和 443 nm)的卫星遥感反射率 (Rrs(λ)) 在沿海和内陆水域容易出现很大的不确定性,从而阻止算法生成与这些波段相关的可靠海洋颜色产品。在这项研究中,我们开发了一种算法来估计蓝色波段中的卫星 Rrs(λ) 受到较大不确定性时的 Rrs(41×) 和 Rrs(443)。该算法首先根据卫星测量的 Rrs(λ) 值在 48×(486、488 或 490)、55×(547、551 或 555)和 67× 三个波长处确定 Rrs(λ) 光谱形状(667、670 或 671) 纳米。然后,该算法使用代数公式从估计的 Rrs(λ) 光谱形状导出 Rrs(41x) 和 Rrs(443)。我们使用卫星(SeaWiFS、MODISA、和 VIIRS-SNPP) 和来自全球水域的原位 Rrs(λ) 匹配。结果表明,在适用的情况下,估计的 Rrs(41×) 和 Rrs(443) 的不确定性大大小于原始卫星产品。此外,算法的实现有助于显着增加可利用的 Rrs(41×) 和 Rrs(443) 值的数量。该算法相对稳定,最适用于Rrs(48×)和Rrs(55×)测量不确定度较小的卫星Rrs(λ)谱。演示支持将蓝带估计算法应用于广泛的沿海水域。算法的实现有助于显着增加可利用的 Rrs(41×) 和 Rrs(443) 值的数量。该算法相对稳定,最适用于Rrs(48×)和Rrs(55×)测量不确定度较小的卫星Rrs(λ)谱。演示支持将蓝带估计算法应用于广泛的沿海水域。算法的实现有助于显着增加可利用的 Rrs(41×) 和 Rrs(443) 值的数量。该算法相对稳定,最适用于Rrs(48×)和Rrs(55×)测量不确定度较小的卫星Rrs(λ)谱。演示支持将蓝带估计算法应用于广泛的沿海水域。
更新日期:2020-12-01
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