Spectroscopy and Spectral Analysis, Volume. 41, Issue 11, 3565(2021)

Inland Water Chemical Oxygen Demand Estimation Based on Improved SVR for Hyperspectral Data

Hui SHENG1、1;, Hai-xu CHI1、1;, Ming-ming XU1、1; *;, Shan-wei LIU1、1;, Jian-hua WAN1、1;, and Jin-jin WANG2、2;
Author Affiliations
  • 11. College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266580, China
  • 22. Zhuhai Orbita Aerospace Science & Technology Co., Ltd., Zhuhai 519080, China
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    Figures & Tables(7)
    The maps of Weihe and Xiashan reservoirs
    Optimization SVR model using SA-PSO
    Measured reflectance spectra (a); and normalized spectra (b)
    Pearson’s correlation coefficient (r) between band ratios Rrs(λ2)/Rrs(λ1) and COD in the spectral range of 466~940 nm
    SA-PSO-SVR accuracy evaluation
    Evaluations of predictions using SVR, BP neural network and LR method
    Spatial distribution of COD concentration obtained from OHS data
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    Hui SHENG, Hai-xu CHI, Ming-ming XU, Shan-wei LIU, Jian-hua WAN, Jin-jin WANG. Inland Water Chemical Oxygen Demand Estimation Based on Improved SVR for Hyperspectral Data[J]. Spectroscopy and Spectral Analysis, 2021, 41(11): 3565

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    Paper Information

    Category: Orginal Article

    Received: Oct. 22, 2020

    Accepted: --

    Published Online: Dec. 17, 2021

    The Author Email:

    DOI:10.3964/j.issn.1000-0593(2021)11-3565-07

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