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Multitype inland water atmospheric correction and water quality estimation based on HY-1C CZI images

  • role： First author第一作者
  • Affiliation：

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

  • Email：zhangff07@radi.ac.cn
  • Introduction：张方方，研究方向为水环境遥感。E-mail：zhangff07@radi.ac.cn
ZHANG Fangfang12,  
  • role： Corresponding author通信作者
  • Affiliation：

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：lijs@radi.ac.cn
  • Introduction：李俊生，研究方向为水环境遥感。E-mail：lijs@radi.ac.cn
LI Junsheng123*,  
  • Affiliation：

    Institute of Geographical Sciences, Henan Academy of Sciences, Zhengzhou 450052, China

WANG Chao4,  
  • Affiliation：

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

WANG Shenglei12,  
  • Affiliation：

    Institute of Geographical Sciences, Henan Academy of Sciences, Zhengzhou 450052, China

WANG Zheng4,  
  • Affiliation：

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100049, China

ZHANG Bing123

Resümee

The Coastal Zone Imager (CZI) on HY-1C has great potential in the application of water color remote sensing for inland water. At present, few studies exist on the atmospheric correction and water quality estimation of HY-1C CZI images in inland water, and problems, such as the lack of atmospheric correction and water quality estimation models applicable to different types of inland water, still need to be solved. Therefore, in this study, a synchronization experiment was carried out on five lakes and reservoirs with different turbidity degrees in the North China Plain: Xiaolangdi Reservoir, Guanting Reservoir, Danjiangkou Reservoir, Baikushan Reservoir, and Baiyangdian Lake. The surface remote sensing reflectance spectra and typical water quality parameters of 85 sampling points were obtained. The relative atmospheric correction algorithm for HY-1C CZI images based on Sentinel-2 MSI images and system calibration model were developed. The average unbiased relative errors (AUREs) of remote sensing reflectance estimation in blue, green, red, and near-infrared bands of HY-1C CZI are 14.7%, 11.2%, 28.9%, and 41.7%, respectively. The atmospheric correction accuracy of blue, green, and red bands is relatively high. In addition, the mean value of correlation coefficient between atmospheric correction and measured spectra is 0.978, and the mean value of spectral angle distance is 0.109, indicating that the shape of the reflectance spectra of atmospheric correction is consistent with that of the measured spectra. The estimation models of chlorophyll-a concentration and Secchi disk depth were established on the basis of the measured data. The AURE of chlorophyll-a concentration estimation from HY-1C CZI images is 33.8%, and the root-mean-square error (RMSE) is 4.8 μg/L. The AURE and RMSE of Secchi disk depth estimation are 25.0% and 34.9 cm, respectively. The results show that HY-1C CZI images can be applied to the water quality estimation of multiple inland water bodies in the North China Plain.This method solved the problem of water atmospheric correction when HY-1C lacks short wave infrared band by borrowing Sentinel-2 MSI data. And realized the bottleneck of high-precision water remote sensing reflectance calculation of 4-band multispectral images, and improves the quantitative processing and the application level of water color remote sensing of HY-1C data.

Schlüsselwort

HY-1C CZI;inland water;atmospheric correction;chlorophyll-a;secchi disk depth

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