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Regional-scale algorithm to estimate the particulate organic carbon (POC) in inland waters using Landsat-5/TM images

机译:利用Landsat-5 / TM图像估算内陆水域颗粒状有机碳(POC)的区域规模算法

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摘要

A regional-scale algorithm was developed in order to test if the Landsat-5/TM can be used to estimate the particulate organic carbon (POC) in oligotrophic-to-mesotrophic inland water. To develop the POC algorithm two fieldworks were conducted, the first in May and the second in September 2009. The algorithm was calibrated using the dataset from September and validated using the dataset from May. The results showed that the best calibration was obtained using a polynomial fitting function (R2 of 0.80,p < 0.0001). This model was validated with a normalized root mean square error (NRMSE) of 6.21%. The algorithm was then applied in two Landsat-5/TM images from April and July 2009. The spatial distribution of POC obtained from the satellite images reveals a strong dependence of POC concentrations with the weather conditions. These results allowed us to conclude that there is a great potential to study the temporal dynamics of POC in inland waters using Landsat-5/TM images.
机译:开发了一种区域规模算法,以测试LANDSAT-5 / TM是否可用于估计寡核苷酸 - 培养的内陆水中的颗粒有机碳(POC)。 为了开发PoC算法,进行了两个实地工作,第一个5月和2009年9月的第二个。使用DataSet从9月开始校准该算法,并从5月份使用数据集进行验证。 结果表明,使用多项式拟合功能(R2为0.80,P <0.0001)获得最佳校准。 该模型被验证,标准化的根均方误差(NRMSE)为6.21%。 然后将该算法从4月和2009年7月应用于两种Landsat-5 / TM图像中。从卫星图像获得的Poc的空间分布揭示了PoC浓度与天气条件的强烈依赖。 这些结果允许我们得出结论,使用Landsat-5 / TM图像研究内陆水域中POC的时间动态存在巨大潜力。

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