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Water quality monitoring model construction by integration of multi-source data: a case study in Whangpoo River upper region

机译:多源数据集成的水质监测模型施工 - 以旺宝河上部地区为例

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The method by the integration of multi-source data including remote sensing data , ground spectral measurement data and other in situ monitoring data , is presented in this paper to construct a quantitative water quality inversion model. The upper region of Whangpoo River in Shanghai is selected as a study area and the dissolved oxygen is chose as a typical water quality indicator. We first process the remote sensing imagery and field spectrometer data to obtain the accurate water reflectance. An inversion model of dissolved oxygen is then derived from the modeling analysis between the water quality data and the reflectance. The accuracy of the model is further confirmed, and this model is applied to invert the dissolved oxygen distribution in Whangpoo River upper region. The inverted water quality distribution has a high consistency with the practical case. This proves that the method by integration of multi-source data is an effective way to monitor the water quality.
机译:本文提出了通过集成包括遥感数据,地面光谱测量数据和其他原位监测数据的多源数据的方法,以构建定量水质反转模型。上海旺宝河上部地区被选为研究区,并选择溶解氧作为典型的水质指标。我们首先处理遥感图像和现场光谱仪数据,以获得准确的水反射率。然后从水质数据和反射率之间的建模分析中得出溶解氧的反转模型。进一步证实了模型的准确性,并且该模型用于反转旺宝河上部区域的溶解氧气分布。倒水质量分布与实际情况具有高一致性。这证明了通过多源数据集成的方法是监控水质的有效方法。

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