Atmospheric Correction Algorithms for Ocean Color Remote Sensing

Ocean colour remote sensing relies on the precise retrieval of water-leaving reflectance from satellite measurements taken at the top of the atmosphere. Since less than 10 % of the detected signal originates from the ocean surface, robust atmospheric correction algorithms are essential to remove contributions from molecular scattering, aerosols and surface glint. Traditional approaches exploit the dark pixel assumption in near-infrared or shortwave-infrared bands, where water reflectance is minimal, to estimate atmospheric path radiance. Physics-based radiative transfer models simulate the interaction of sunlight with atmospheric constituents and the sea surface, while semi-empirical and machine-learning schemes fuse theoretical constraints with in situ data to improve performance in bio-optically complex waters. Recent advances have focused on turbid coastal and estuarine environments, where high turbidity and variable aerosol loads challenge standard methods. Incorporation of additional spectral bands, optimisation routines and uncertainty quantification has underpinned improved retrievals of chlorophyll-a, suspended particulate matter and coloured dissolved organic matter. These developments support global monitoring of marine ecosystems, carbon cycling and water quality, with applications ranging from climate studies to fisheries management.

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Atmospheric Correction Algorithms for Ocean Color Remote Sensing publication trend

The graph below shows the total number of articles in atmospheric correction algorithms for ocean color remote sensing across all publications each year (not limited to Nature Index journals).

Technical terms

Remote sensing reflectance (Rrs): The ratio of water-leaving radiance to downwelling irradiance just above the sea surface, fundamental for deriving water constituents.

Rayleigh scattering: Elastic scattering of light by atmospheric molecules, wavelength-dependent and dominant in the blue end of the spectrum.

Aerosol optical thickness (AOT): A dimensionless measure of aerosol load in a vertical column, affecting the attenuation of solar radiation.

Dark Spectrum Fitting (DSF): An algorithm that estimates atmospheric path radiance by fitting to near-infrared or shortwave-infrared pixels assumed to have negligible water reflectance.

Radiative transfer model (RTM): A computational framework simulating the propagation and scattering of electromagnetic radiation through atmospheric and oceanic media.

References

1. HY-1C/D CZI Image Atmospheric Correction and Quantifying Suspended Particulate Matter. Remote Sensing (2023).
2. Determining the primary sources of uncertainty in the retrieval of marine remote sensing reflectance from satellite ocean color sensors II. Sentinel 3 OLCI sensors. Frontiers in Remote Sensing (2023).
3. Atmospheric correction of Sentinel-3/OLCI data for mapping of suspended particulate matter and chlorophyll-a concentration in Belgian turbid coastal waters. Remote Sensing of Environment (2021).
4. Revisiting short-wave-infrared (SWIR) bands for atmospheric correction in coastal waters.. Optics Express (2017).