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Remote Sensing for Natural Resources    2021, Vol. 33 Issue (3) : 45-53     DOI: 10.6046/zrzyyg.2020377
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Aquatic environmental monitoring of inland waters based on UAV hyperspectral remote sensing
ZANG Chuankai1(), SHEN Fang1,2(), YANG Zhengdong3
1. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China
2. Institute of Eco-Chongming(IEC), Shanghai 200062, China
3. Hydrological Station of Shanghai Chongming District, Shanghai 200062, China
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Abstract  

With the inland waters in Chongming Island, Shanghai as the study area, this study researched the color changes of waters and the identification of suspected polluted waters using unmanned aerial vehicle (UAV) hyperspectral remote sensing images. First, reflectance calibration was carried out for the radiance signals detected by the hyperspectral sensor carried by UAVs. Compared with on-site observations, this calibration method was more accurate, the average unbiased absolute percentage differences of various bands were 13.34% on average and the average determination coefficient R2 was 0.83. Afterward, the inversion of hue angle and apparent visible wavelength (AVW) was conducted using the hyperspectral reflectance of the inland waters according to the CIE-XYZ color space and weighted harmonic mean. Then an inversion model of water quality parameters was constructed based on measured data, and the water colors in the study area were classified by setting the threshold of hue angle. As indicated by the results, there exist many abnormal yellowish-brown inland waters in the Chongming Island in dry seasons and it is necessary to strengthen the supervision and governance of the aquatic environment of major shipping rivers. Finally, the suspected polluted inland waters were identified and analyzed by integrating the inversion results of the parameters of water color and water quality. This study shows that UAV hyperspectral remote sensing can be used to obtain the inversion results with high temporal-spatial continuity of the parameters of water color and water quality, which will provide credible technical support for the aquatic environment investigations of inland waters while saving costs.
Keywords UAV      hyperspectral remote sensing      water colour      inland waters      aquatic environment     
ZTFLH:  P231.1  
Corresponding Authors: SHEN Fang     E-mail: 51183904016@stu.ecnu.edu.cn;fshen@sklec.ecnu.edu.cn
Issue Date: 24 September 2021
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Chuankai ZANG
Fang SHEN
Zhengdong YANG
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Chuankai ZANG,Fang SHEN,Zhengdong YANG. Aquatic environmental monitoring of inland waters based on UAV hyperspectral remote sensing[J]. Remote Sensing for Natural Resources, 2021, 33(3): 45-53.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2020377     OR     https://www.gtzyyg.com/EN/Y2021/V33/I3/45
Fig.1  Research area and sampling point
水质参数 最小值 最大值 平均值 标准差
Chl-a/(mg·m-3) 4.62 311.63 41.98 54.15
TSM/(mg·L-1) 4.50 281.67 45.71 42.26
CDOM/m 0.30 2.22 0.88 0.46
浊度/NTU 5.95 142.00 51.17 30.23
TN/(mg·L-1) 0.44 2.53 1.34 0.53
TP/(mg·L-1) 0.009 0.93 0.15 0.18
Tab.1  Concentration distribution of water quality parameters at sampling points
Fig.2  Noise reduction process and evaluation of UAV hyperspectral image
Fig.3  Spectral curves and corresponding Hue angle of different types of water
水质
参数(y)		 自变量(x) 反演模型
Chl-a/
(mg·m-3)		 x=Rrs(636.91)/
Rrs(701.64)		 y=38.27x-6.10
TSM/(mg·L-1) x=Rrs(733) y=251 886x2-7 300.8x+74.94
CDOM/m x1=Rrs(600)/Rrs(709), x2=Rrs(652)/Rrs(725) y=2.098x1+0.286x2+2.950
浊度/
NTU		 x=(Rrs(651)-
Rrs(655))/Rrs(761)		 y=140.58exp(18x)
TN/
(mg·L-1)		 x=(Rrs(482)-
Rrs(677))/(Rrs(482)+Rrs(677))		 y=751.27x3+201.79x2+3.60x+0.72
TP/
(mg·L-1)		 x=(Rrs(618)-
Rrs(692))/(Rrs(618)+Rrs(692))		 y=7 084.4x3-1 177.7x2+55.84x-0.48
Tab.2  Inversion model for water quality parameters
Fig.4  UAV and in situ measured Rrs comparison verification
Fig.5  Verification of accuracy of UAV hyperspectral inversion of water colour parameters and water quality parameters
Fig.6  Hue angle classification of rivers and lakes in Chongming Island, Shanghai
Fig.7  Identification of suspected polluted water in the key observational rivers of Chongming Island in Shanghai
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