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Non-optical Water Quality Retrieval from Zhuhai-1 OHS Hyperspectral Images in Taipu River
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  • Yukun Yukun,
  • Yaojen Tu,
  • Wenpeng Lin,
  • Weiyue Li,
  • Qianwen Cheng
Yukun Yukun
Shanghai Normal University

Corresponding Author:[email protected]

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Yaojen Tu
Shanghai Normal University
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Wenpeng Lin
Shanghai Normal University
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Weiyue Li
Shanghai Normal University
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Qianwen Cheng
Shanghai Normal University
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Abstract

Hyperspectral remote sensing is thought to be a useful technology for assessing the condition of inland waters. However, non-optically active water quality parameters are rarely explored in hyperspectral remote sensing applications, despite they are highly valued in the aquatic environment condition. This study intends to evaluate the performance of non-optically active water quality parameters using Zhuhai-1 hyperspectral imagery. Focusing on total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH3-N) and nitrate-nitrogen (NO3-N) in Taipu River, we constructed empirical models to evaluate the precision of water quality inversion from OHS by comparing with Sentinel-2, and determined the sensitive bands of different water quality parameters. The final results showed that the polynomial model based on OHS had the greatest potential in retrieving TN, TP and NH3-N concentration, and the R2 was 0.9678, 0.7924, 0.7682 respectively. The combination of R(510)/R(820) and R(700)/R(806), R(940)/R(820) and R(806)/R(926), R(709)/R(806) and R(746)/R(620) were most sensitive to TN, TP and NH3-N respectively. The OHS and Sentinel-2 both had potential in retrieving NO3-N. The R2 was 0.9791 from OHS and was 0.9513 from Sentinel-2. The sensitive bands of NO3-N were R(596)/R(665) and R(466)/R(580) from OHS, and Red Eage3/Blue and SWIR1/Blue from Sentinel-2. We also analyzed the drivers of the spatial distribution of water quality in Taipu River, the results showed negative impacts of farmland and urban land on water quality, and beneficial impacts of forest land on water quality. This study represented a promising step in hyperspectral remote sensing for retrieving inland non-optically active water quality parameters utilizing Zhuhai-1.