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LONG-TERM PREDICTION OF THE CHLOROPHYLL A CONCENTRATION IN THE SULU SEA FROM THE SATELLITE OBSERVATION

机译:从卫星观测长期预测苏鲁海域叶绿素a的浓度

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Sulu Sea is a deep ocean in Southeast Asia with remarkable features which has complex geometry and multi-scale dynamics deduced by the large-scale open-ocean and at mospheric forcing. Sulu Sea extended from 6°N to 12°N and from 117°E to 123°E is bounded by multiple islands and passages and this area holds higher productivity level than other ocean in South China Sea. Despite of the fact that Sulu Sea is high with primary production, this area is restricted to access due to the fact of political and security issues. Therefore, it limits the in-situ acquisition for scientific study. This is not the issue for satellite remote sensing observation as this method allows exploration on this inaccessible region at promising accuracy in space and time. The aim of this study is to forecast and predict the Chlorophyll a (hereafter Chl-a) concentration in Sulu Sea using the Holt-Winter forecasting procedures regardless of the need of synoptic in-situ data. In order to predict the Chl-a concentration of the Sulu Sea, Sea-viewing Wide Field-of-view Sensor (SeaWIFs) data is used to acquire ocean color information. SeaWiFS Data Analysis System (SeaDAS version 6 under Linux OS) was used for satellite image processing and analysis. This study determines spatial and long-term variations as well as the prediction on the Chl-a concentration using the selected model. The prediction method proved as an alternative to retrieve sea productivity level at the area that lack of in-situ data. Besides, the results are useful to local fisheries department to monitor the fishing ground in Sulu Sea region.
机译:苏禄海是东南亚的一个深海,具有显着特征,具有复杂的几何形状和多尺度动力学,这是由大规模开放海洋和大气强迫推导得出的。苏禄海从6°N延伸到12°N,从117°E延伸到123°E,周围有多个岛屿和航道,与南海其他海洋相比,该地区的生产力水平更高。尽管苏禄海的初级产品产量很高,但由于政治和安全问题,该地区只能进入。因此,它限制了科学研究的原位采集。对于卫星遥感观测而言,这不是问题,因为这种方法允许以有希望的时空精度在这个难以接近的区域进行探测。这项研究的目的是使用Holt-Winter预测程序来预测和预测苏禄海中的叶绿素a(以下称Chl-a)浓度,而与天气数据无关。为了预测苏禄海的Chl-a浓度,使用了海景宽视野传感器(SeaWIFs)数据来获取海洋颜色信息。 SeaWiFS数据分析系统(Linux OS下的SeaDAS版本6)用于卫星图像处理和分析。这项研究使用所选模型确定了空间和长期变化以及对Chl-a浓度的预测。事实证明,该预测方法是在缺乏现场数据的地区检索海洋生产力水平的一种替代方法。此外,研究结果对于当地渔业部门监测苏禄海地区的渔场很有用。

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