首页> 外文会议>Remote Sensing of the Marine Environment; Proceedings of SPIE-The International Society for Optical Engineering; vol.6406 >Estimation of chlorophyll-a concentration from satellite ocean color data in Upper Gulf of Thailand
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Estimation of chlorophyll-a concentration from satellite ocean color data in Upper Gulf of Thailand

机译:根据泰国上海湾的卫星海洋颜色数据估算叶绿素-a的浓度

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This study shows match-up analysis of chlorophyll-a concentration in coastal area in Upper Gulf of Thailand. An applicability of atmospheric correction are investigated in turbid area. When a suspended matter concentration is over 7 g/m3 in a mouth of Bangpakong river, atmospheric correction was failed, then chlorophyll-a concentration could not be estimated. Three algorithms which are MODIS (Moderate Resolution Imaging Spectroradiometer) standard, neural network for GLI (Global Imager) and regional empirical algorithm are compared using match-up data set. The regional algorithm has better correlation than other algorithms and its RMSE was minimum in three algorithms. MODIS standard algorithm has good performance in higher than 1mg/m~3, however, CHL was overestimated in lower concentration.
机译:这项研究显示了泰国上海湾沿岸地区叶绿素a浓度的匹配分析。在浑浊区域研究了大气校正的适用性。当邦帕孔河口的悬浮物浓度超过7 g / m3时,大气校正失败,因此无法估算叶绿素a的浓度。使用匹配数据集比较了MODIS(中等分辨率成像光谱仪)标准,GLI神经网络(全局成像仪)和区域经验算法这三种算法。区域算法比其他算法具有更好的相关性,并且在三种算法中其RMSE最小。 MODIS标准算法在高于1mg / m〜3时具有良好的性能,但是在较低浓度下CHL被高估了。

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