Ocean transparency from space: Validation of algorithms using MERIS, MODIS and SeaWiFS data
Ocean transparency from space: Validation of algorithms using MERIS, MODIS and SeaWiFS data
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DOI：
10.1016/j.rse.2011.05.019
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发表时间：
2011-12-15
影响因子：
13.5
通讯作者：
Garnesson, Philippe
中科院分区：
文献类型：
--
作者：
Doron, Maeva;Babin, Marcel;Garnesson, Philippe
海洋透明度，通常使用塞奇圆盘测量，是水质或生产力的有用指标，并用于许多环境研究。空间海洋颜色传感器提供天气和常规辐射测量数据，如果将数据转换成相关的海洋地球化学特性，可用于实施环境政策。我们适应和发展半分析和经验算法估计的Secchi深度从卫星海洋颜色数据在沿海和海洋沃茨。该算法的开发是基于使用一个全面的原位生物光学数据集的算法进行验证，使用一组广泛的一致的卫星估计和原位测量的塞奇深度（所谓的匹配）。为MERIS，MODIS和SeaWiFS传感器编制了400多个匹配。从遥感数据和原位测量的塞奇深度检索之间的比较产生的决定系数（R-2）在0.50和0.73之间，这取决于传感器和算法。II型线性回归的斜率和截距分别在0.95和1.46之间以及-0.8和6.2之间变化。虽然半分析算法提供了最有前途的结果，在现场数据，经验证明是更强大的遥感数据，因为它是不敏感的错误，由于错误的大气校正。使用海洋颜色档案，人们可以获得不同地区的海洋透明度地图。我们基于北海和波罗的海之间过渡区海洋颜色的塞奇深度气候学与历史数据集（C）2011 Elsevier Inc. All rights reserved.
Ocean transparency, often measured using Secchi disk, is a useful index of water quality or productivity and is used in many environmental studies. The spaceborne ocean color sensors provide synoptic and regular radiometric data and can be used for applying environmental policies if the data is converted into relevant biogeochemical properties. We adapted and developed semi-analytical and empirical algorithms to estimate the Secchi depth from satellite ocean color data in both coastal and oceanic waters. The development of the algorithms is based on the use of a comprehensive in situ bio-optical dataset The algorithms are validated using an extensive set of coincident satellite estimates and in situ measurements of the Secchi depth (so-called matchups). More than 400 matchups are compiled for the MERIS, MODIS and SeaWiFS sensors. The comparison between Secchi depth retrievals from remote sensing data and in situ measurements yields determination coefficients (R-2) between 0.50 and 0.73, depending on the sensor and algorithm. The type II linear regression slopes and intercepts vary between 0.95 and 1.46, and between -0.8 and 6.2 in, respectively. While semi-analytical algorithms provide the most promising results on in situ data, the empirical one proves to be more robust on remote sensing data because it is less sensitive to error due to erroneous atmospheric corrections. Using ocean color archives, one can derive maps of ocean transparency for different areas. Our climatology of the Secchi depth based on ocean color for the transition zone between the North Sea and Baltic Sea is compared to an historical dataset (C) 2011 Elsevier Inc. All rights reserved.