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首页> 外文期刊>Journal of great lakes research >Verification of a simple band ratio algorithm for retrieving Great Lakes open water surface chlorophyll concentrations from satellite observations
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Verification of a simple band ratio algorithm for retrieving Great Lakes open water surface chlorophyll concentrations from satellite observations

机译:验证从卫星观测中检索大湖露天水面叶绿素浓度的简单谱带比算法

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We compared in situ surface chlorophyll concentration values measured between 2012 and 2015 as part of the U.S. Environmental Protection Agency's Great Lakes National Program Office (GLNPO) annual monitoring program with corresponding concentration estimates obtained by applying our previously published (Lesht et al., 2013) Great Lakes Fit (GLF) band ratio algorithm to data from the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor. Coefficients used in the original GLF algorithm were derived from similarly matched GLNPO and satellite observations collected between 2002 and 2011. The Model II linear relationship between the original GLF-predicted log-transformed values and the new set (2012-2015) of field observations yielded intercept = 0.036, slope = 1.063, and r(2) = 0.830. Residuals for modeled chlorophyll concentrations below similar to 8.0 mg m(-3) were unbiased and normally distributed, but positively biased at higher modeled concentrations. When applied to the entire dataset (2002-2015), the linear relationship between the GLF-modeled and the observed values had intercept = 0.000, slope = 0.999, and r(2) = 0.820. New model coefficients derived from the entire (2002-2015) dataset were very similar to those obtained from the 2002-2011 data. Continual testing and assessment of any empirical model are desirable especially when the model is designed to be employed by a broad community. We conclude that this comparison of the GLF algorithm with the additional four years of independent data further validates its use for estimating surface chlorophyll concentrations from satellite observations of the open waters of the Great Lakes. (C) 2016 International Association for Great lakes Research. Published by Elsevier B.V. All rights reserved.
机译:我们将2012年至2015年间作为美国环境保护署大湖国家计划办公室(GLNPO)年度监测计划一部分测得的原位表面叶绿素浓度值与通过应用我们先前发表的数据得出的相应浓度估算值进行了比较(Lesht等人,2013)大湖区拟合(GLF)带宽比算法可处理中等分辨率成像光谱仪(MODIS)传感器的数据。原始GLF算法使用的系数来自相似匹配的GLNPO和2002年至2011年之间收集的卫星观测结果。模型II的线性关系由原始GLF预测的对数转换值与新的现场观测值集(2012-2015)得出截距= 0.036,斜率= 1.063,r(2)= 0.830。低于8.0 mg m(-3)的建模叶绿素浓度的残留物无偏见且呈正态分布,但在较高的建模浓度下为正偏。当应用于整个数据集(2002年至2015年)时,GLF模型和观测值之间的线性关系为:截距= 0.000,斜率= 0.999和r(2)= 0.820。从整个(2002-2015)数据集得出的新模型系数与从2002-2011数据获得的系数非常相似。希望对任何经验模型进行连续测试和评估,尤其是当该模型旨在为广大社区所采用时。我们得出的结论是,对GLF算法与另外四年的独立数据的比较进一步证实了它用于根据大湖开放水域的卫星观测估计表面叶绿素浓度的用途。 (C)2016国际大湖研究协会。由Elsevier B.V.发布。保留所有权利。

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