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Diversity II water quality parameters from ENVISAT (2002–2012): a new global information source for lakes

机译:ENVISAT(2002–2012)的多样性II水质参数:一个新的全球湖泊信息来源

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The use of ground sampled water quality information for global studies is limited due to practical and financial constraints. Remote sensing is a valuable means to overcome such limitations and to provide synoptic views of ambient water quality at appropriate spatio-temporal scales. In past years several large data processing efforts were initiated to provide corresponding data sources. The Diversity II water quality dataset consists of several monthly, yearly and 9-year averaged water quality parameters for 340 lakes worldwide and is based on data from the full ENVISAT MERIS operation period (2002–2012). Existing retrieval methods and datasets were selected after an extensive algorithm intercomparison exercise. Chlorophyll-a, total suspended matter, turbidity, coloured dissolved organic matter, lake surface water temperature, cyanobacteria and floating vegetation maps, as well as several auxiliary data layers, provide a generically specified database that can be used for assessing a variety of locally relevant ecosystem properties and environmental problems. For validation and accuracy assessment, we provide matchup comparisons for 24 lakes and a group of reservoirs representing a wide range of bio-optical conditions. Matchup comparisons for chlorophyll-a concentrations indicate mean absolute errors and bias in the order of median concentrations for individual lakes, while total suspended matter and turbidity retrieval achieve significantly better performance metrics across several lake-specific datasets. We demonstrate the use of the products by illustrating and discussing remotely sensed evidence of lake-specific processes and prominent regime shifts documented in the literature.
机译:由于实际和财务上的限制,将地面采样水质信息用于全球研究受到限制。遥感是克服这种局限性并在适当的时空尺度上提供周围水质概况的宝贵手段。在过去的几年中,开始了一些大型数据处理工作以提供相应的数据源。 “多样性II”水质数据集由全球340个湖泊的数个月度,年度和9年平均水质参数组成,并基于ENVISAT MERIS整个运行时期(2002-2012年)的数据。经过广泛的算法比对后,选择了现有的检索方法和数据集。叶绿素-a,总悬浮物,浊度,有色溶解有机物,湖面水温,蓝细菌和浮游植物图以及几个辅助数据层,提供了通用指定的数据库,可用于评估各种与当地相关的数据生态系统特性和环境问题。为了进行验证和准确性评估,我们提供了24个湖泊和一组代表广泛生物光学条件的储层的对比比较。叶绿素-a浓度的配对比较表明,各个湖泊的平均绝对误差和偏差以中位数浓度为顺序,而总悬浮物和浊度的取回在多个特定于湖泊的数据集中获得了更好的性能指标。我们通过说明和讨论有关湖泊特定过程和文献中记载的显着政权转移的遥感证据来证明产品的使用。

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