The CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight).
The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

由欧洲空间局（European Space Agency, ESA）资助的海岸色彩循环比对（CoastColour Round Robin, CCRR）项目（官网：http://www.coastcolour.org）旨在汇聚各类参考数据集，依托这些数据开展算法测试，并评估其反演水质参数的精度。该研究成果后续被用于辅助遥感产品的终端用户，为其所在沿海区域遴选精度最优的反演算法。为达成这一目标，研究团队针对沿海水体水色参数反演算法的性能开展了交叉比对工作，本次比对共采用三类数据集用于水色算法的测试验证。本文的核心内容即为这三类数据集的描述与交叉比对，其中涵盖中等分辨率成像光谱仪（Medium Resolution Imaging Spectrometer, MERIS）二级星地匹配数据集、原位反射率实测数据，以及辐射传输模型HydroLight生成的模拟数据。本次数据集总计包含6484条海洋反射率数据，关联各类几何参数（传感器观测角与太阳高度角）、天空状况以及水体组分：总悬浮颗粒物（Total Suspended Matter, TSM）浓度、叶绿素a（Chlorophyll-a, CHL）浓度，以及有色溶解有机物（Coloured Dissolved Organic Matter, CDOM）的吸收系数。模拟数据集（含5000组模拟样本）与3054个星地匹配采样点还同步提供了固有光学特性数据。研究对三类数据集在选定MERIS波段的反射率分布、波段比值，以及CHL、TSM随反射率变化的分布特征进行了对比分析，并识别出了存在算法偏差的星地匹配与原位观测站点。此外，本次研究还将三类反射率数据集与此前国际海洋色彩协调组（International Ocean Colour Coordinating Group, IOCCG, 2006）用于算法测试的模拟与原位反射率数据进行了比对，结果表明CCRR数据集覆盖了更多浑浊水体，实现了数据分布范围的显著拓展。