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Ocean Primary Production in China Shelf Sea Estimated with SeaWiFS and MODIS

机译:海洋初级生产在中国货架海洋估计与海盗和莫迪斯

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Ocean primary production (OPP) is an important indicator of ocean ecological system. The spatial and temporal pattern of OPP is helpful for global climate change study. Remote sensing has the advantage of dynamic and large-scale information collection. Integration of remote sensing and ecological model is promising for OPP study. The aim of our study is to: 1) choose the suitable coefficient algorithms in models for OPP calculation; 2) provide satellite-derived OPP pattern in China Shelf Sea. We have chosen VGPM (Vertical Generalized Production Model) to estimate OPP for its extensive validation. Some parameters of VGPM were calculated using new algorithms instead. Most of the parameters were estimated using SeaWiFS and MODIS data. The OPP in the China Shelf Sea were estimated using VGPM model. And a simple test was also implemented. The correlation coefficient between in situ OPP and estimated one is over 0.5. OPP variation was also analyzed in China Shelf Sea. The result shows that the OPP model based on the specific chlorophyll algorithm in China sea area can reveal the environment better. This method can provide reference for the large-scale tendency research of OPP in the whole sea area.
机译:海洋初级生产(OPP)是海洋生态系统的重要指标。 opp的空间和时间模式有助于全球气候变化研究。遥感具有动态和大规模信息收集的优势。遥感与生态模型的整合对opp学习有前途。我们研究的目的是:1)选择适用于OPP计算模型中的系数算法; 2)提供中国卫生卫星海洋的卫星衍生的OPP模式。我们选择了VGPM(垂直的广义生产模型)来估计它的广泛验证。使用新算法计算VGPM的一些参数。使用SEAWIFS和MODIS数据估计大多数参数。使用VGPM模型估计了中国货架海的OPP。还实施了一个简单的测试。原位OPP和估计的相关系数超过0.5。在中国货架海域也分析了互换变异。结果表明,基于中国海域特异性叶绿素算法的OPP模型可以更好地揭示环境。该方法可以为整个海域的互联网上的大规模趋势研究提供参考。

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