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首页> 外文期刊>International journal of remote sensing >A new area-specific bio-optical algorithm for the Bay of Biscay and assessment of its potential for SeaWiFS and MODIS/Aqua data merging
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A new area-specific bio-optical algorithm for the Bay of Biscay and assessment of its potential for SeaWiFS and MODIS/Aqua data merging

机译:比斯开湾的一种特定于区域的新生物光学算法,并评估了其在SeaWiFS和MODIS / Aqua数据合并中的潜力

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摘要

Based on a feed-forward and error-back-propagated neural network (NN), a new bio-optical algorithm is developed for the Bay of Biscay. It is designed as a set of NNs individually dedicated to the retrieval of the phytoplankton chlorophyll (chl), and total suspended matter (tsm) from Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua data. The retrieved versus in situ measured concentrations of chl and tsm correlation coefficients for chl proved to be ~0.8 (SeaWiFS) and 0.72 (MODIS), and for tsm 0.71 (SeaWiFS) and 0.74 (MODIS). The developed NN-based bio-optical algorithms are employed to assess the compatibility of SeaWiFS and MODIS data on chl and tsm in the coastal zone of the Bay of Biscay (case 2 waters). The value of the ratio between the concentration of chl and tsm derived from the same-day SeaWiFS and MODIS data (the overflight time difference, △t is ≤2.5 hours) has in most cases values of approximately 1, however, in specific cases it varies appreciably. These results indicate that, unlike the reportedly very successful cases of merging of SeaWiFS and MODIS data on chl in open ocean waters (case 1 waters), the merging of chl (and tsm) data from these sensors collected over case 2 waters needs to be supervised at a level of a few pixels. At the same time, when averaged over the entire coastal zone of the Bay of Biscay, the retrieved monthly mean chl and tsm concentrations from SeaWiFS and MODIS practically coincide throughout the years (2002-2004) of contemporaneous operation of these two satellite sensors. Thus, even in the case of such dynamic and optically complex case 2 waters that are inherent in the Bay of Biscay, the potentials for ocean colour data merging are very good. The merging efficiency is assessed and illustrated via documenting the spatio-temporal dynamics of bottom sediment re-suspension in the bay occurring in winter - the season of heaviest cloudiness over the bay.
机译:基于前馈和错误传播的神经网络(NN),为比斯开湾开发了一种新的生物光学算法。它被设计为一组NN,分别致力于从海景宽视场传感器(SeaWiFS)和中等分辨率成像光谱仪(MODIS)检索浮游植物叶绿素(chl)和总悬浮物(tsm)。水族数据。测得的chl和tsm相关系数的浓度与实测值之间的相关性分别为〜0.8(SeaWiFS)和0.72(MODIS),tsm 0.71(SeaWiFS)和0.74(MODIS)。使用已开发的基于NN的生物光学算法来评估Biscay湾沿海地区(案例2的水域)的SeaWiFS和MODIS数据在chl和tsm上的兼容性。从当日SeaWiFS和MODIS数据得出的chl和tsm浓度之比(飞越时间差△t≤2.5小时)的值在大多数情况下约为1,但是,在特定情况下,变化很大。这些结果表明,与在公开海洋水域(案例1的水域)中将chl的SeaWiFS和MODIS数据合并的非常成功的案例不同,需要将来自案例2水域的这些传感器收集的chl(和tsm)数据进行合并在几个像素的水平上进行监督。同时,当对比斯开湾的整个沿海地区进行平均时,从这两个卫星传感器同时运行的几年(2002-2004年)中,从SeaWiFS和MODIS检索到的每月平均chl和tsm浓度实际上是一致的。因此,即使在比斯开湾固有的这种动态且光学上复杂的案例2的水域中,海洋颜色数据合并的潜力也非常好。通过记录冬季发生的海湾底部沉积物重新悬浮的时空动态,评估并说明了合并效率,该季节是海湾上最阴沉的季节。

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  • 来源
    《International journal of remote sensing》 |2010年第24期|p.6541-6565|共25页
  • 作者单位

    Nansen International Environmental and Remote Sensing Center, 14th Line 7, 199034, St. Petersburg, Russia,Russian State Hydrometeorological University, Malookhtinsky Prospect, 98, 195196, St. Petersburg, Russia;

    Nansen International Environmental and Remote Sensing Center, 14th Line 7, 199034, St. Petersburg, Russia,Nansen Environmental and Remote Sensing Center, Thorm0lhensgate 47, N-5006, Bergen, Norway;

    Nansen International Environmental and Remote Sensing Center, 14th Line 7, 199034, St. Petersburg, Russia,Nansen Environmental and Remote Sensing Center, Thorm0lhensgate 47, N-5006, Bergen, Norway;

    Nansen Environmental and Remote Sensing Center, Thorm0lhensgate 47, N-5006, Bergen, Norway;

    Russian State Hydrometeorological University, Malookhtinsky Prospect, 98, 195196, St. Petersburg, Russia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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