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Destriping algorithm for improved satellite-derived ocean color product imagery.

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    A new method effectively removes striping from satellite imagery, improving ocean color data. This technique enhances the quality of normalized water-leaving radiance spectra and derived ocean products.

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    Area of Science:

    • Earth Observation
    • Oceanography
    • Remote Sensing

    Background:

    • Multi-detector sensors in satellite imagery can produce striping artifacts.
    • Existing sensor calibration methods cannot fully correct these striping issues.
    • Previous methods successfully addressed striping in thermal infrared bands.

    Purpose of the Study:

    • To adapt and apply a novel destriping methodology to solar reflective bands.
    • To remove significant striping from normalized water-leaving radiance spectra (nLw(λ)).
    • To improve the quality of satellite-derived ocean biological and biogeochemical products.

    Main Methods:

    • Modified the Bouali and Ignatov (2014) destriping approach.
    • Applied the adjusted methodology to solar reflective band data, specifically nLw(λ).
    • Ensured the destriping was applied to nLw(λ) and not top-of-atmosphere radiances.

    Main Results:

    • Successfully removed striping artifacts from satellite-derived nLw(λ) spectra.
    • Demonstrated significant improvements in image quality for nLw(λ).
    • Showcased enhanced accuracy for derived ocean products like chlorophyll-a and Kd(490).

    Conclusions:

    • The adapted destriping method is effective for solar reflective bands.
    • Improved nLw(λ) data leads to better oceanographic and biogeochemical product retrieval.
    • This technique offers a valuable tool for enhancing satellite ocean color data quality.