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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Algorithms Merging for the Determination of Chlorophyll- ${a}$ Concentration in the Black Sea
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Algorithms Merging for the Determination of Chlorophyll- ${a}$ Concentration in the Black Sea

机译:合并叶绿素 - <内联公式> $ {a} $ 浓度在黑海中的算法

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Two regional bio-optical algorithms are combined to retrieve the Chlorophyll-a (Chl-a) concentration in the Black Sea. The first is a band-ratio algorithm that computes Chl-a as a function of the slope of Remote Sensing Reflectance (R-RS) values at two wavelengths using a polynomial regression that captures the overall data trend, enhancing extrapolation results. The second algorithm is a Multilayer Perceptron neural net based on Rgs values at three individual wavelengths that features interpolation capabilities helpful to fit data non-linearities. A new merging scheme is then designed to benefit from the complementarity of the two approaches. Remote sensing data employed to demonstrate the merging of regional results for the Black Sea are those acquired by the Ocean and Land Color Instrument on board Sentinel-3A to acknowledge the need for data products of higher accuracy within the long-term Copernicus program.
机译:将两个区域生物光学算法组合以检索黑海中的叶绿素-A(CHL-A)浓度。第一是一种带比算法,其使用捕获整体数据趋势的多项式回归来计算CHL-A作为遥感反射率(R-RS)值的斜率的函数,增强外推结果。第二算法是基于三个单独波长的RGS值的多层Perceptron神经网络,其具有有助于拟合数据非线性的插值能力。然后,新的合并方案旨在受益于两种方法的互补性。用于展示黑海区域结果的遥感数据是由海洋和土地彩色仪器收购的局域网,董事会-3a收购,以确认在长期哥白尼计划中获得更高准确性的数据产品。

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