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

被引:0
|
作者
Zhang F. [1 ,2 ]
Li J. [1 ,2 ,3 ]
Wang C. [4 ]
Wang S. [1 ,2 ]
Wang Z. [4 ]
Zhang B. [1 ,2 ,3 ]
机构
[1] International Research Center of Big Data for Sustainable Development Goals, Beijing
[2] Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing
[3] University of Chinese Academy of Sciences, Beijing
[4] Institute of Geographical Sciences, Henan Academy of Sciences, Zhengzhou
基金
中国国家自然科学基金;
关键词
atmospheric correction; Chlorophyll-a; HY-1C CZI; inland water; secchi disk depth;
D O I
10.11834/jrs.20235010
中图分类号
学科分类号
摘要
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. © 2023 National Remote Sensing Bulletin. All rights reserved.
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页码:79 / 91
页数:12
相关论文
共 23 条
  • [1] Cai L N, Zhou M R, Liu J Q, Tang D L, Zuo J C., HY-1C observations of the impacts of islands on suspended sediment distribution in Zhoushan Coastal Waters, China, Remote Sensing, 12, 11, (2020)
  • [2] Cai T., The launch of “Haiyang” - 1D satellite will successfully create China’s first maritime civil satellite constellation, Aerospace China, 6, (2020)
  • [3] Canty M J, Nielsen A A, Schmidt M., Automatic radiometric normalization of multitemporal satellite imagery, Remote Sensing of Environment, 91, 3, pp. 441-451, (2004)
  • [4] Cao Z G, Ma R H, Liu J Q, Ding J., Improved radiometric and spatial capabilities of the coastal zone imager onboard Chinese HY-1C satellite for inland lakes, IEEE Geoscience and Remote Sensing Letters, 18, 2, pp. 193-197, (2021)
  • [5] Chen X Y, Zhang J, Tong C, Liu R J, Mu B, Ding J., Retrieval algorithm of chlorophyll-a concentration in turbid waters from satellite HY-1C coastal zone imager data, Journal of Coastal Research, 90, sp1, pp. 146-155, (2019)
  • [6] Du Y, Teillet P M, Cihlar J., Radiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection, Remote Sensing of Environment, 82, 1, pp. 123-134, (2002)
  • [7] Duan H T, Zhang Y Z, Zhang B, Song K S, Wang Z M., Assessment of chlorophyll-a concentration and trophic state for Lake Chagan using Landsat TM and field spectral data, Environmental Monitoring and ASsessment, 129, 1, pp. 295-308, (2007)
  • [8] Guo L F, Gao X H, Kang J, Meng X Q., Application of the pseudo-invariant feature in normalization process of the remote sensing images, Remote Sensing Technology and Application, 24, 5, pp. 588-595, (2009)
  • [9] Liang C, Liu L, Liu J Q, Zou B, Zou Y R, Cui S X., Extracting mangrove information using MNF transformation based on HY-1C CZI spectral indices reconstruction data, Haiyang Xuebao, 42, 4, pp. 104-112, (2020)
  • [10] Liu J Q, Ye X M, Zeng T, Ma X F, Liu J P., HY-1D satellite captured the volcanic eruption in Antarctica, Haiyang Xuebao, 43, 2, pp. 139-140, (2021)