首页> 外文期刊>European Journal of Remote Sensing >Multispectral data by the new generation of high-resolution satellite sensors for mapping phytoplankton blooms in the Mar Piccolo of Taranto (Ionian Sea, southern Italy)
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Multispectral data by the new generation of high-resolution satellite sensors for mapping phytoplankton blooms in the Mar Piccolo of Taranto (Ionian Sea, southern Italy)

机译:通过新一代高分辨率卫星传感器来绘制Phytoplankton在Mar Piccolo的Mar Piccolo(Ionian Hea,Southern Italy)的新一代高分辨率传感器

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The HR (High-Resolution) EO (Earth Observation) satellite systems Landsat 8 OLI and Sentinel 2 were tested for mapping the frequent phytoplankton blooms and Chl a distributions in the sea basin of the Mar Piccolo of Taranto (Ionian Sea, southern Italy), using the sea truth calibration data acquired in 2013. The data were atmospherically corrected for accounting of the aerosol load on optically complexes waters (case II). Various blue-green and additional spectral indices ratios, were then satisfyingly tested for mapping the distribution of Chl a and differently sized phytoplankton populations through PLS (Partial Least Square regression) models, regressive statistical models and bio-optical algorithms. The PLS models demonstrated higher robustness for assessing the distribution of all the phytoplankton and Chl a except for those related to sub-surface micro-phytoplankton. The distributions obtained via a bio-optical approach (OC3 algorithm and full physically based inversion) showed a general agreement with the previous ones produced by statistical methods. The reflectance signals, captured by OLI and Sentinel 2 sensors in the visible and shorter wavelengths once atmospherically corrected, were found to be useful to map the coastal variability at detailed scale of Chl a and different phytoplankton populations, in the optically complexes waters of the Mar Piccolo.
机译:HR(高分辨率)EO(地球观察)卫星系统Landsat 8 Oli和Sentinel 2进行了测绘,用于将频繁的浮游植物绽放和Chl A在Mar Taranto(Ionian Sea,Southern Southern Soutaly)的海域中进行绘制,使用2013年获取的海洋真理校准数据。数据在光学复合物水域上的气溶胶载量算时大气纠正(案例II)。然后,可以通过PLS(局部最小二乘回归)模型,回归统计模型和生物光学算法将各种蓝绿色和额外的光谱指标比映射CHL A和不同大小的浮游植物群体的分布。除了与亚表面微浮游植物相关的人外,PLS模型展示了评估所有浮游植物和CHL A的分布的鲁棒性。通过生物光学方法(OC3算法和全物理基础的反转)获得的分布显示了与通过统计方法产生的先前的一致。由Oli和Sentinel 2传感器捕获的反射信号在可见和更短的波长中捕获一次大气校正,以在MAR的光学复合物水域中以CHL A和不同的浮游植物种群的详细变化映射沿海可变性是有用的Piccolo。

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