| 摘要: |
| 传统水质监测方法耗时且费力，而基于高光谱的水质监测技术可实现对水质的快速、直观、原位监测。以扬州古运河三湾段为研究区域，基于无人机高光谱成像仪与水质走航监测船相配合，采用空地协同模式和偏最小二乘回归算法对总磷（TP）、总氮（TN）、氨氮（NH3-N）、高锰酸盐指数（IMn）4个水质参数进行定量反演研究。结果表明：该反演模型的决定系数（R2）为91%～97%；拟合效果依次为NH3-N＞IMn＞TN＞TP；各指标反演误差绝对值为0.2%～4%。该方法具有较好的反演效果，可快速、准确地获取城市河道水质分布情况，适用于城市水环境监测。 |
| 关键词: 空地协同 城市水环境 高光谱成像仪 偏最小二乘回归算法 |
| DOI：DOI：10.3969/j.issn.1674-6732.2024.01.011 |
| 分类号:X832 |
| 基金项目:江苏省环境监测科研基金项目（1701） |
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| Research on the Application of Space-ground Collaborative Mode in Urban Water Environmental Monitoring |
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TAO Qianhui， ZHANG Kaiyuan， DAI Yuan，SHEN Peishan
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Yangzhou Environmental Monitoring Center of Jiangsu Province， Yangzhou，Jiangsu 225100，China
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| Abstract: |
| Traditional water quality detection methods are time consuming and laborious， hyperspectral based water quality monitoring enables rapid， intuitive， and in situ monitoring of water quality. In this paper， taking the Sanwan section of the ancient canal in Yangzhou as the research area， based on the combination of UAV hyperspectral and water quality navigation monitoring vessel， the water ground collaborative mode and partial least squares algorithm were used to quantitatively invert the water quality parameters such as TP， NH3-N， TN， and IMn. The results show that the R2 of the partial least squares inversion model is between 91%～97%. The order of fitting effect was NH3-N>IMn>TN>TP. The absolute value of the inversion error of each index is between 0.2%～4%. The current method has a good inversion effect and can quickly and accurately obtain the distribution of urban river water quality， which is of great significance to urban water environment monitoring. |
| Key words: Air-ground coordination Urban water environment Hyperspectra Partial least squares |
