• DocumentCode
    1061244
  • Title

    Determination of CDOM and NPPM absorption coefficient spectra from coastal water remote sensing reflectance

  • Author

    Alimonte, Davide D. ; Zibordi, Giuseppe ; Berthon, Jean-François

  • Author_Institution
    Neural Comput. Res. Group, Aston Univ., Birmingham, UK
  • Volume
    42
  • Issue
    8
  • fYear
    2004
  • Firstpage
    1770
  • Lastpage
    1777
  • Abstract
    Multilayer perceptron (MLP) neural network algorithms were developed to retrieve the absorption coefficient spectra of the colored dissolved organic matter (CDOM) and nonpigmented particulate matter (NPPM) from the remote sensing reflectance Rrs of optically complex waters. The two MLP algorithms, consisting of one hidden layer with ten neurons and requiring Rrs at 412, 490, and 665 nm as inputs, were trained with a comprehensive experimental dataset of the Northern Adriatic Sea coastal waters. The products of the proposed regional MLP algorithms showed higher accuracies than regional band-ratio algorithms, and exhibited average uncertainties of 20% and 25% in the determination of CDOM and NPPM absorption coefficients at 412 nm, respectively.
  • Keywords
    multilayer perceptrons; oceanographic regions; oceanographic techniques; remote sensing; seawater; 412 nm; 490 nm; 665 nm; CDOM absorption coefficient spectra; NPPM absorption coefficient spectra; Northern Adriatic Sea coastal waters; biooptical modeling; coastal water remote sensing reflectance; colored dissolved organic matter; hidden layer; multilayer perceptron; neural network algorithms; nonpigmented particulate matter; ocean color; optically complex waters; regional band-ratio algorithms; Absorption; Multi-layer neural network; Multilayer perceptrons; Neural networks; Optical computing; Optical fiber networks; Optical sensors; Reflectivity; Remote sensing; Sea measurements; Biooptical modeling; neural network; ocean color;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2004.831444
  • Filename
    1323133