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首页> 外文期刊>Journal of Geophysical Research, C. Oceans: JGR >A new bio-optical algorithm for the remote sensing of algal blooms in complex ocean waters
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A new bio-optical algorithm for the remote sensing of algal blooms in complex ocean waters

机译:复杂海洋中藻华遥感的新型生物光学算法

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A new bio-optical algorithm has been developed to provide accurate assessments of chlorophyll a (Chl a) concentration for detection and mapping of algal blooms from satellite data in optically complex waters, where the presence of suspended sediments and dissolved substances can interfere with phytoplankton signal and thus confound conventional band ratio algorithms. A global data set of concurrent measurements of pigment concentration and radiometric reflectance was compiled and used to develop this algorithm that uses the normalized water-leaving radiance ratios along with an algal bloom index (ABI) between three visible bands to determine Chl a concentrations. The algorithm is derived using Sea-viewing Wide Field-of-view Sensor bands, and it is subsequently tuned to be applicable to Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua data. When compared with large in situ data sets and satellite matchups in a variety of coastal and ocean waters the present algorithm makes good retrievals of the Chl a concentration and shows statistically significant improvement over current global algorithms (e.g., OC3 and OC4v4). An examination of the performance of these algorithms on several MODIS/Aqua images in complex waters of the Arabian Sea and west Florida shelf shows that the new algorithm provides a better means for detecting and differentiating algal blooms from other turbid features, whereas the OC3 algorithm has significant errors although yielding relatively consistent results in clear waters. These findings imply that, provided that an accurate atmospheric correction scheme is available to deal with complex waters, the current MODIS/Aqua, MERIS and OCM data could be extensively used for quantitative and operational monitoring of algal blooms in various regional and global waters.
机译:已开发出一种新的生物光学算法,以提供准确的叶绿素a(Chl a)浓度评估,以检测和绘制光学复杂水中的卫星数据中的藻华,其中悬浮的沉积物和溶解物质的存在会干扰浮游植物的信号因此混淆了传统的带宽比率算法。汇编了同时测量颜料浓度和辐射反射率的全球数据集,并用于开发该算法,该算法使用归一化的放水辐射率以及三个可见谱带之间的藻华指数(ABI)来确定Chla浓度。该算法是使用海景宽视场传感器波段导出的,随后对其进行了调整,以适用于中等分辨率成像光谱仪(MODIS)/ Aqua数据。当与各种沿海和海洋水域中的大型现场数据集和卫星对位相比较时,本算法对Ch1a浓度进行了很好的检索,并且相对于当前的全局算法(例如OC3和OC4v4)在统计上有显着改进。在阿拉伯海和佛罗里达西部海域的复杂水域中,在几种MODIS / Aqua图像上对这些算法的性能进行了检查,结果表明,该新算法提供了一种更好的方法来检测和区分藻华与其他浑浊特征,而OC3算法具有尽管在清澈的水中产生相对一致的结果,但仍然存在重大错误。这些发现表明,只要有一个准确的大气校正方案可以处理复杂的水域,当前的MODIS / Aqua,MERIS和OCM数据就可以广泛地用于定量和运行监测各种区域和全球水域中的藻华。

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