Using machine learning algorithms with in-situ hyperspectral reflectance data to assess comprehensive water quality of urban rivers
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DOI: 10.1109/tgrs.2022.3147695
Abstract: Remotely sensed hyperspectral data can support more effective water quality monitoring. Nevertheless, the variability and complexity of urban river water make it hard to retrieve comprehensive water quality characteristics directly, so that most current water… read more here.
Keywords: water; hyperspectral data; water quality; comprehensive water ... See more keywords