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Hyperspectral quantitative inversion model for water quality parameters of lakes at the Jiuzhaigou World Natural Heritage Site(PDF)

Chinese Journal of Applied & Environmental Biology[ISSN:1006-687X/CN:51-1482/Q]

2021 05
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Hyperspectral quantitative inversion model for water quality parameters of lakes at the Jiuzhaigou World Natural Heritage Site
TANG Zhonglin1 2 ZHU Zhongfu2 3 4 LI Xiaohui2 3 ZHONG Bo2 3 XU Liang5 Zhuomanta4 An?elka Plenkovi?-Moraj6 & SUN Geng2?
1 School of Economics, Chongqing Technology and Business University, Chongqing 400067, China 2 China-Croatia “Belt and Road” Joint Laboratory on Biodiversity and Ecosystem Services & CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization & Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences Chengdu 610041, China 3 University of Chinese Academy of Sciences, Beijing 100049, China 4 Jiuzhaigou National Nature Rreserve Administration, Aba 623402, China 5 Sichuan Ecological Environment Monitoring Centre, Chengdu 610074, China 6 Faculty of Science, University of Zagreb, Zagreb 10000, Croatia
Jiuzhaigou water quality parameter hyperspectral quantitative inversion

Hyperspectral inversion of lake water quality parameters is an important prerequisite for the rapid monitoring of water quality using hyperspectral remote sensing. In this study, field investigations and sampling focused on water monitoring were carried out at the Jiuzhaigou World Natural Heritage site. The hyperspectral quantitative inversion of water quality parameters was performed using a stepwise regression method combined with the measurement of the physicochemical properties of the water and an analysis of its spectral morphological characteristics. The results showed the following. (1) The spectral curve of the Jiuzhaigou water body conforms to the characteristics of Class II inland lakes. (2) The multiple linear inversion model of water quality parameters was constructed using a stepwise regression analysis method that extracted spectral morphological features in 3 categories and 24 subcategories as well as 4-value spectral coding information, with the results showing that the model could be tested on 9 indicators including color difference; chroma; Ca2+, Mg2+, F-, SO42-, DO, TN/TP, and DO levels; and conductivity; of these, the R2 of Mg2+ was the highest at 0.911 and that of DO was the lowest at 0.751. (3) Verification of the water quality parameter sample showed that the minimum R2 of the Jiuzhaigou water quality parameter inversion model was 0.691 and the maximum was 0.847 and that the relative root mean-squared error (RRMSE) was lower than 4%. These results show that the Jiuzhaigou water quality parameter inversion model constructed in this study, which was based on a hyperspectral quantitative inversion of the water quality parameters, has a high inversion accuracy. It has thus provided theoretical and data-based support for further monitoring of the water in Jiuzhaigou Lake using hyperspectral remote sensing.


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Last Update: 2021-10-25