首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Optical Properties Using Adaptive Selection of NIR/SWIR Reflectance Correction and Quasi-Analytic Algorithms for the MODIS-Aqua in Estuarine-Ocean Continuum: Application to the Northern Gulf of Mexico
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Optical Properties Using Adaptive Selection of NIR/SWIR Reflectance Correction and Quasi-Analytic Algorithms for the MODIS-Aqua in Estuarine-Ocean Continuum: Application to the Northern Gulf of Mexico

机译:光学特性,使用NIR / SWIR反射措施校正的自适应选择和埃斯特林海洋MODIS-AQUA的准分析算法:在墨西哥北湾的应用

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摘要

An adaptive selection of the near/shortwave infrared (NIR/SWIR) reflectance correction and the quasi-analytic algorithms (QAAs) is proposed for the Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua) to utilize the strengths of different correction algorithms and QAAs in a single satellite scene with water types ranging from turbid coastal to clear open ocean waters. A blended satellite product is generated by merging three atmospheric-correction algorithms(AD-ATCOR): 1) iterative NIR correction; 2) management unit of the north sea mathematical models (MUMM); and 3) SWIR, using a spectral threshold-based selection for different water types. The validation analysis of a blended remote sensing reflectance product showed overall good agreement with AERONET-OC observations followed by NASA bio-optical marine algorithm data set (NOMAD) at the blue wavelengths and the estuarine data set at the green and red wavelengths. The results suggest that the adaptive method is a better alternative to address the challenging problem of selecting different correction algorithms for different water types in a single satellite scene. Likewise, an adaptive selection of a QAA (AD-QAA) used the QAA-v5 and the QAA-V to obtain merged inherent optical property (IOP) products in a single MODIS-Aqua scene with varying water types. As a case study, the two adaptive selection procedures were sequentially applied to the MODIS-Aqua imagery representing four environmental conditions in the northern Gulf of Mexico. Improved retrievals of the total absorption and backscattering coefficients along an estuarine to ocean continuum demonstrated the effectiveness of this method in an optically complex and dynamic river-dominated system.
机译:提出了一种自适应选择近/短波(NIR / SWIR / SWIR)反射态校正和准分析算法(QAAS),用于采用不同校正算法和QAAS中的不同校正算法和QAAS的强度单颗卫星场景与水类型,从浑浊的沿海程度透明开阔的海洋水域。通过合并三种大气校正算法(AD-ATCOR):1)迭代NIR校正来产生混合卫星产品; 2)北海数学模型管理单位(MUMM); 3)SWIR,使用基于光谱阈值的不同水类型的选择。混合遥感反射率产品的验证分析显示出与AeroNet-OC观测的总体良好的一致性,然后是NASA生物光学船用算法数据集(Nomad)在蓝色波长下设置为绿色和红色波长的河口数据。结果表明,自适应方法是更好的替代方案,以解决在单个卫星场景中为不同水类型选择不同的校正算法的具有挑战性问题。同样,QAA-V5和QAA-V的自适应选择使用QAA-V5和QAA-V在单个Modis-Aqua场景中获得合并的固有光学性质(IOP)产品,不同的水类型。作为一个案例研究,两个自适应选择程序顺序应用于代表墨西哥北部四个环境条件的Modis-Aqua图像。改进了沿着海洋连续酵母的总吸收和后散射系数的检索证明了该方法在光学复杂和动态河道主导系统中的有效性。

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