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Using Landsat/TM Imagery to Estimate Nitrogen and Phosphorus Concentration in Taihu Lake, China

机译:利用Landsat / TM影像估算中国太湖的氮和磷浓度

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摘要

In this study, we evaluate the benefits of the use of broad-band reflectance data from remote-sensing imagery for improving point prediction of N (Nitrogen) and PC (Phosphorus Concentration) in lakes. The algorithms were calibrated and validated by in situ measurements, collected on 27 and 28 October, 2003, in Taihu Lake, China. Both two algorithms produced well performance in estimating NC and PC in Taihu Lake, but the PC retrieval model had a superior performance to NC retrieval model. The RE (Relative Error) of the PC and NC retrieval models were 11.7% and 35.6%, respectively. According to no more than 30% accuracy requirements of water quality estimation for remote-sensing technology, the accuracy of PC retrieval model is more acceptable than the NC retrieval mode's. Finally, the PC and NC were estimated from Landsat/TM imagery, collected on 28 October, 2003. The retrieval results showed that the NC and PC were higher in the south, east and center of the lake ( $>$18 mg/l and $>$2 mg/l for NC and PC, respectively) and lower in the west and north of the lake ( $<$18 mg/l and $<$2 mg/l for NC and PC, respectively). Although it was a special case study of this paper, the modeling procedures of NC and PC estimation algorithms could give us the implication when we used the remote-sensing technology to estimate the NC and PC from similar or dissimilar aquatic environments
机译:在这项研究中,我们评估了利用遥感影像中的宽带反射率数据改善湖泊中N(氮)和PC(磷浓度)的点预测的好处。通过对原位测量的校准和验证,该算法于2003年10月27日至28日在中国太湖进行了采集。两种算法在估算太湖地区的NC和PC方面均具有良好的性能,但PC检索模型的性能优于NC检索模型。 PC和NC检索模型的RE(相对误差)分别为11.7%和35.6%。根据遥感技术对水质估算精度的要求不超过30%,PC检索模型的精度比NC检索模式的精度更高。最后,根据2003年10月28日收集的Landsat / TM影像估算了PC和NC。检索结果显示,湖的南部,东部和中部的NC和PC较高($> $ 18 mg / l和$> $ 2 mg / l分别对湖的西和北($ <$ < / formula> 18 mg / l和$ <$ 2 mg / l分别用于NC和PC)。尽管这是本文的一个特殊案例研究,但是当我们使用遥感技术从相似或不相似的水生环境中估算NC和PC时,NC和PC估计算法的建模过程可以为我们带来启示。

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