Remote Sensing Technology and Application, Volume. 40, Issue 2, 265(2025)

Atmospheric Correction Method of Sentinel-2 Data for Inland Water Quality Remote Sensing

Jiayi LI, Ruru DENG*, Yan YAN, Yu GUO, Yuhua LI, Yiling LI, Longhai XIONG, and Yeheng LIANG
Author Affiliations
  • School of Geography and Planning, Sun Yat-Sen University, Guangzhou511400, China
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    References(34)

    [1] SEDIGHKIA M, DATTA B, SAEEDIPOUR P et al. Predicting water quality distribution of lakes through linking remote sensing–based monitoring and machine learning simulation. Remote Sensing, 15, 3302(2023).

    [2] ZHAO J R, JIN S G, ZHANG Y Y. Dynamic water quality changes in the main stream of the Yangtze River from multi-source remote sensing data. Remote Sensing, 15, 2526(2023).

    [3] NAJAFZADEH M, BASIRIAN S. Evaluation of river water quality index using remote sensing and artificial intelligence models. Remote Sensing, 15, 2359(2023).

    [4] LI Jun, ZHANG Wenzhi, DENG Ruru et al. Study of spatial-temporal characteristics for CODMn in Shenzhen reservoir based on GF-1 WFV. National Remote Sensing Bulletin, 26, 1562-1574(2022).

    [5] WANG Simeng, QIN Boqiang. Research progress on remote sensing monitoring of lake water quality parameters. Environmental Science, 44, 1228-1243(2023).

    [6] Olmanson G L, PAGE P B, FINLAY C J et al. Regional measurements and spatial/temporal analysis of CDOM in 10 000 optically variable minnesota lakes using Landsat 8 Imagery. Science of the Total Environment, 724, 138141(2020).

    [7] KONG Zhuo, YANG Haitao, ZHENG Fengjie et al. Research advances in atmospheric correction of hyperspectral remote sensing images. Remote Sensing for Natural Resources, 34, 1-10(2022).

    [8] LI Zhenwang, LIU Liangyun, ZHANG Hao et al. Radiometric calibration and validation of TG-1 Hyper Spectral imager. Remote Sensing Technology and Application, 28, 850-857(2013).

    [9] CAI L N, BU J, TANG D L et al. Geosynchronous satellite GF-4 observations of Chlorophyll-a distribution details in the Bohai Sea, China. Sensors, 20, 5471(2020).

    [10] YANG M M, HU Y, TIAN H Z et al. Atmospheric correction of airborne hyperspectral CASI data using polymer, 6S and FLAASH. Remote Sensing, 13, 5062-5062(2021).

    [11] LI Shu, LIU Qijing. Effect on atmospheric correction by ground elevation and atmospheric model parameters of FLAASH mode. Remote Sensing Technology and Application, 30, 939-945(2015).

    [12] WANG Jianan, YE Qin, LIN Yi. Comparing effects of different atmospheric correction algorithms in remote sensing dynamic monitoring of cyanobacteria bloomin inland lakes. Remote Sensing Technology and Application, 28, 157-165(2013).

    [13] MA Gong, LI Zhengqiang, LI Hao et al. Influence of aerosol model in the atmospheric correction of satellite images——A case study over Tianjin Region. Remote Sensing Technology and Application, 29, 410-418(2014).

    [14] VERMOTE E F, TANRE D. Second simulation of the satellite signal in the solar spectrum,6S:An overview. IEEE Transactions on Geoscience and Remote Sensing, 35, 675-686(1997).

    [15] CHENG Chunmei, WEI Yuchun, LI Yuan et al. Atmospheric correction of GF-1/WFV image in Taihu Lake based on the 6S model pixel by pixel. Remote Sensing Technology and Application, 35, 141-152(2020).

    [16] ALEXANDER A, MARINA R I, STEVEN B. Empirical line model for the atmospheric correction of Sentinel-2A MSI images in the Caribbean Islands. European Journal of Remote Sensing, 51, 765-776(2018).

    [17] JR P S C. Image-based atmospheric corrections-revisited and improved. Photogrammetric Engineering and Remote Sensing, 62, 1025-1036(1996).

    [18] XING Xiaoda, SHEN Qian, LI Junsheng et al. Inversion of suspended matter concentration of the River of Manwan Dam Regions based on HJ-CCDD data. Remote Sensing Technology and Application, 31, 682-690(2016).

    [19] CONCHA J A, SCHOTT J R. A Model-based ELM for Atmospheric Correction over Case 2 Water with Landsat8. Ocean Sensing and Monitoring VI, 2014(9111).

    [20] XAVIER S, JESÚS D, PATRICIA E U et al. Assessment of Sentinel-2-MSI atmospheric correction processors and in situ spectrometry waters quality algorithms. Remote Sensing, 14, 4794-4794(2022).

    [21] WANG Bo, HUANG Jinhui, GUO Hongwei et al. Progress in research on inland water quality monitoring based on remote sensing. Water Resources Protection, 38, 117-124(2022).

    [22] SU Wei, ZHANG Mingzheng, JIANG Kunping et al. Atmospheric correction method for Sentinel-2 satellite imagery. Acta Optica Sinica, 38, 322-331(2018).

    [23] CHEN Jianxiong, LIU Xiaobo. Water quality status and change trend of Qingyuan Section of Beijiang River in the past 10 years. Guangdong Water Resources and Hydropower, 53-57(2023).

    [24] WANG Runtian, LIU Da, QIU Jing et al. River evolution and analysis of the upstream and downstream of the Feilaixia Hydraulic project in the Beijiang River. China Water Resources, 2022, 73-75,60.

    [25] ZHANG Y Y, HE X Q, LIAN G et al. Monitoring and spatial traceability of river water quality using Sentinel-2 Satellite images. The Science of the Total Environment, 894, 164862(2023).

    [26] LIU Yuchen, GAO Yongnian. Surface water extraction in Yangtze River Basin based on Sentinel time series image. National Remote Sensing Bulletin, 26, 358-372(2022).

    [27] WU Qingshuang, WANG Mingxiu, SHEN Qian et al. Small water body extraction method based on Sentinel-2 satellite multi-spectral remote sensing image. National Remote Sensing Bulletin, 26, 781-794(2022).

    [28] WARREN M, SIMIS S, MARTINEZ-VICENTE V et al. Assessment of atmospheric correction algorithms for the Sentinel-2A multispectral imager over coastal and inland waters. Remote Sensing of Environment, 225, 267-289(2019).

    [29] ZHANG Yanli, ZHANG Liping. Snow cover identification and area change in mountainous regions based on Sentinel-2 time series data. Chinese Journal of Ecology, 39, 2810-2820(2020).

    [30] LIU Wenya, DENG Ruru, LIANG Yeheng et al. Retrieval of Chlorophyll-a concentration in Chaohu based on radiative transfer model. Remote Sensing for Land and Resources, 31, 102-110(2019).

    [31] WU Yi, DENG Ruru, QIN Yan et al. The study of spatial-temporal characteristics for Chlorophyll concentration derived from remote sensing image in Xinfengjiang Reservoir. Remote Sensing Technology and Application, 32, 825-834(2017).

    [32] HE Yingqing, DENG Ruru, CHEN Lei et al. The atmospheric correction for tm image under complicated geographic conditions based on automatically extracted many dark objects. Remote Sensing Technology and Application, 25, 532-539(2010).

    [33] KONG Zhuo, YANG Haitao, ZHENG Fengjie et al. Automatic atmospheric correction method of Gaofen-5 hyperspectral image. Remote Sensing Information, 38, 112-118(2023).

    [34] SHI Xi, XIA Junqiang, SUN Jian. Comparison of methods to derive river water temperature using thermal infrared imagery: A case study of the upper Yangtze River Catchment. Journal of Lake Sciences, 34, 307-319(2022).

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    Jiayi LI, Ruru DENG, Yan YAN, Yu GUO, Yuhua LI, Yiling LI, Longhai XIONG, Yeheng LIANG. Atmospheric Correction Method of Sentinel-2 Data for Inland Water Quality Remote Sensing[J]. Remote Sensing Technology and Application, 2025, 40(2): 265

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    Paper Information

    Category:

    Received: Aug. 29, 2023

    Accepted: --

    Published Online: May. 23, 2025

    The Author Email: Ruru DENG (esdrr@mail.sysu.edu.cn)

    DOI:10.11873/j.issn.1004-0323.2025.2.0265

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