Ocean Color & Marine Remote Sensing

Satellite-based observation of ocean bio-optical properties, chlorophyll concentration, and water constituents

Overview

Ocean color remote sensing measures the spectral distribution of light leaving the ocean surface to infer concentrations of phytoplankton (via chlorophyll-a), colored dissolved organic matter (CDOM), and total suspended matter (TSM). Sensors like MODIS, VIIRS, Sentinel-3 OLCI, and the upcoming PACE mission provide global-scale observations of marine primary productivity, water clarity, and biogeochemical cycles. Atmospheric correction is a critical preprocessing step, as ~90% of the signal at the top of atmosphere originates from the atmosphere rather than the ocean.

~90%

TOA signal from atmosphere

PACE

NASA's next-gen ocean color mission

~50%

Earth's O₂ from ocean phytoplankton

0.01–64

Chl-a range (mg/m³) in global ocean

Sensor	Platform	Bands	Resolution	Period
SeaWiFS	OrbView-2	8	1.1 km	1997–2010
MODIS	Terra/Aqua	36	250m–1km	1999–present
VIIRS	Suomi NPP / NOAA-20	22	375m–750m	2011–present
OLCI	Sentinel-3A/B	21	300m	2016–present
OCI	PACE	Hyperspectral	1 km	2024–present

Key Concepts

Inherent Optical Properties

IOPs — absorption (a) and scattering (b) coefficients — are intrinsic properties of water constituents. They depend on wavelength and the composition of phytoplankton, CDOM, and suspended particles. IOPs form the physical basis for semi-analytical ocean color algorithms.

a(λ) = a_w(λ) + a_ph(λ) + a_CDOM(λ) + a_NAP(λ)

Remote Sensing Reflectance

R_rs(λ) is the ratio of water-leaving radiance to downwelling irradiance just above the surface. It is the primary ocean color product after atmospheric correction and encodes information about water constituents.

R_rs(λ) = L_w(λ) / E_d(0⁺, λ)

Chlorophyll-a Algorithms

Empirical band-ratio algorithms (OC3M, OC4) relate the ratio of blue-to-green reflectance to Chl-a. Semi-analytical algorithms (QAA, GSM) invert R_rs using physical models. Machine learning approaches are increasingly used for complex optical waters.

Atmospheric Correction

Removing atmospheric effects (Rayleigh scattering, aerosol scattering, absorbing gases) is essential. The Gordon & Wang (1994) algorithm iteratively estimates aerosol contributions using NIR bands where water is essentially black.

CDOM & TSM Retrieval

CDOM absorbs strongly in UV/blue wavelengths and can be retrieved via its exponential absorption spectrum. TSM increases backscattering and is retrieved from red/NIR bands where water absorption dominates.

Primary Productivity

Satellite Chl-a combined with PAR and SST drives models of net primary production (NPP). The VGPM (Behrenfeld & Falkowski, 1997) and Carbon-based Productivity Model (CbPM) estimate global ocean carbon fixation.

Interactive Visualizations

Spectral Remote Sensing Reflectance

Chlorophyll-a Seasonal Variability

Absorption Spectra of Water Constituents

Key References

IOCCG (2000). Remote Sensing of Ocean Colour in Coastal, and Other Optically-Complex, Waters. Reports of IOCCG, No. 3.
Gordon, H.R. & Wang, M. (1994). Retrieval of water-leaving radiance and aerosol optical thickness. Applied Optics, 33(3), 443–452.
O'Reilly, J.E. et al. (1998). Ocean color chlorophyll algorithms for SeaWiFS. J. Geophys. Res., 103(C11), 24937–24953.
Behrenfeld, M.J. & Falkowski, P.G. (1997). Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnology and Oceanography, 42(1), 1–20.
Lee, Z. et al. (2002). Deriving inherent optical properties from water color: a multi-band quasi-analytical algorithm. Applied Optics, 41(27), 5755–5772.