A Wavelet-Enhanced Inversion Method for Water Quality Retrieval From High Spectral Resolution Data for Complex Waters

Eva Ampe, D Raymaekers, Erin Hestir, Maarten Jansen, E Knaeps, Okke Batelaan

    Research output: Contribution to journalArticlepeer-review

    9 Citations (Scopus)


    Optical remote sensing in complex waters is challenging because the optically active constituents may vary independently and have a combined and interacting influence on the remote sensing signal. Additionally, the remote sensing signal is influenced by noise and spectral contamination by confounding factors, resulting in ill-posedness and ill-conditionedness in the inversion of the model. There is a need for inversion methods that are less sensitive to these changing or shifting spectral features. We propose WaveIN, a wavelet-enhanced inversion method, specifically designed for complex waters. It integrates wavelet-transformed high-spectral resolution reflectance spectra in a multiscale analysis tool. Wavelets are less sensitive to a bias in the spectra and can avoid the changing or shifting spectral features by selecting specific wavelet scales. This paper applied WaveIN to simulated reflectance spectra for the Scheldt River. We tested different scenarios, where we added specific noise or confounding factors, specifically uncorrelated noise, contamination due to spectral mixing, a different sun zenith angle, and specific inherent optical property (SIOP) variation. WaveIN improved the constituent estimation in case of the reference scenario, contamination due to spectral mixing, and a different sun zenith angle. WaveIN could reduce, but not overcome, the influence of variation in SIOPs. Furthermore, it is sensitive to wavelet edge effects. In addition, it still requires in situ data for the wavelet scale selection. Future research should therefore improve the wavelet scale selection.

    Original languageEnglish
    Article number6847235
    Pages (from-to)869-882
    Number of pages14
    JournalIEEE Transactions on Geoscience and Remote Sensing
    Issue number2
    Publication statusPublished - Feb 2015


    • Chlorophyll-a
    • continuous wavelet transforms
    • dissolved organic matter
    • hyperspectral remote sensing
    • multiscale
    • optically complex waters
    • suspended matter


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