Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space.

Area of Science:

• Oceanography
• Remote Sensing
• Atmospheric Science

Background:

• Current atmospheric correction algorithms are limited to clear, deep ocean waters.
• Turbid coastal waters present challenges for accurate ocean color data retrieval.
• Hyperspectral remote sensing offers potential for improved coastal water analysis.

Purpose of the Study:

• To develop a novel atmospheric correction algorithm for hyperspectral remote sensing of ocean color.
• To enable accurate retrieval of water-leaving radiances in turbid coastal environments.
• To support the use of future instruments like the Coastal Ocean Imaging Spectrometer.

Main Methods:

• Utilized a vector radiative transfer code to generate look-up tables.
• Employed a spectrum-matching technique using wavelengths longer than 0.86 µm to determine aerosol parameters.
• Integrated aerosol models to extrapolate information to visible wavelengths for water-leaving radiance retrieval.

Main Results:

• Successfully processed hyperspectral imaging data from an airborne spectrometer.
• Obtained reasonable water-leaving radiance values in turbid coastal water conditions.
• Demonstrated the algorithm's capability to handle complex coastal water optical properties.

Conclusions:

• The developed algorithm is effective for atmospheric correction in turbid coastal waters.
• Hyperspectral data combined with this algorithm significantly advances ocean color remote sensing capabilities.
• This approach is vital for accurate monitoring of coastal marine environments.