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A novel method for destriping of OCM-2 data and radiometric performance analysis for improved ocean color data products

机译:用于改进OCM-2数据去辐射和辐射性能分析的新方法,用于改进海洋颜色数据产品

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摘要

Despite the capability of Ocean Color Monitor aboard Oceansat-2 satellite to provide frequent, high-spatial resolution, visible and near-infrared images for scientific research on coastal zones and climate data records over the global ocean, the generation of science quality ocean color products from OCM-2 data has been hampered by serious vertical striping artifacts and poor calibration of detectors. These along-track stripes are the results of variations in the relative response of the individual detectors of the OCM-2 CCD array. The random unsystematic stripes and bandings on the scene edges affect both visual interpretation and radiometric integrity of remotely sensed data, contribute to confusion in the aerosol correction process, and multiply and propagate into higher level ocean color products generated by atmospheric correction and bio-optical algorithms. Despite a number of destriping algorithms reported in the literature, complete removal of stripes without residual effects and signal distortion in both low- and high-level products is still challenging. Here, a new operational algorithm has been developed that employs an inverted gaussian function to estimate error fraction parameters, which are uncorrelated and vary in spatial, spectral and temporal domains. The algorithm is tested on a large number of OCM-2 scenes from Arabian Sea and Bay of Bengal waters contaminated with severe stripes. The destriping effectiveness of this approach is then evaluated by means of various qualitative and quantitative analyses, and by comparison with the results of the previously reported method. Clearly, the present method is more effective in terms of removing the stripe noise while preserving the radiometric integrity of the destriped OCM-2 data. Furthermore, a preliminary time-dependent calibration of the OCM-2 sensor is performed with several match-up in-situ data to evaluate its radiometric performance for ocean color applications. OCM-2 derived water-leaving radiance products obtained after calibration show a good consistency with in-situ and MODIS-Aqua observations, with errors less than the validated uncertainties of ±5% and ±35% endorsed for the remote-sensing measurements of water-leaving radiance and retrieval of chlorophyll concentrations respectively. The calibration results show a declining trend in detector sensitivity of the OCM-2 sensor, with a maximum effect in the shortwave spectrum, which provides evidence of sensor degradation and its profound effect on the striping artifacts in the OCM-2 data products.
机译:尽管Oceansat-2卫星上的Ocean Color Monitor能够提供频繁,高空间分辨率,可见光和近红外图像,以用于沿海地区的科学研究以及全球海洋的气候数据记录,但仍可以生成科学品质的海洋彩色产品严重的垂直条纹伪影和检测器校准不佳阻碍了来自OCM-2数据的分析。这些沿轨道的条纹是OCM-2 CCD阵列各个检测器的相对响应变化的结果。场景边缘的随机非系统性条纹和条带会影响遥感数据的视觉解释和辐射完整性,加剧气溶胶校正过程中的混乱,并繁衍并传播到大气校正和生物光学算法生成的更高级别的海洋色彩产品中。尽管文献中报道了许多去条纹算法,但是在低水平和高水平产品中,如何完全去除条纹而没有残留效应和信号失真仍然是一项挑战。在这里,已经开发出一种新的运算算法,该算法采用了一个倒置的高斯函数来估计误差分数参数,这些误差分数参数是不相关的,并且在空间,频谱和时间域中都变化。在来自阿拉伯海和孟加拉湾水域的OCM-2场景中,对该场景进行了测试,该场景被严重条纹污染。然后,通过各种定性和定量分析,并与先前报道的方法的结果进行比较,评估这种方法的去除效果。显然,本发明的方法在去除条带噪声的同时保持被去条纹的OCM-2数据的辐射完整性的方面更有效。此外,利用几个匹配的原位数据对OCM-2传感器进行了与时间有关的初步校准,以评估其在海洋颜色应用中的辐射性能。校准后获得的OCM-2衍生出的辐射水产品与原位和MODIS-Aqua观测值显示出良好的一致性,其误差小于为水的遥感测量所认可的±5%和±35%的验证不确定度。离开辐射和叶绿素浓度的恢复。校准结果显示,OCM-2传感器的检测器灵敏度下降趋势,在短波频谱中影响最大,这提供了传感器性能下降及其对OCM-2数据产品中的条纹伪影的深刻影响的证据。

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