Share Email Print
cover

Proceedings Paper

Improved ocean-color remote sensing in the Arctic using the POLYMER algorithm
Author(s): Robert Frouin; Pierre-Yves Deschamps; Didier Ramon; François Steinmetz
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Atmospheric correction of ocean-color imagery in the Arctic brings some specific challenges that the standard atmospheric correction algorithm does not address, namely low solar elevation, high cloud frequency, multi-layered polar clouds, presence of ice in the field-of-view, and adjacency effects from highly reflecting surfaces covered by snow and ice and from clouds. The challenges may be addressed using a flexible atmospheric correction algorithm, referred to as POLYMER (Steinmetz and al., 2011). This algorithm does not use a specific aerosol model, but fits the atmospheric reflectance by a polynomial with a non spectral term that accounts for any non spectral scattering (clouds, coarse aerosol mode) or reflection (glitter, whitecaps, small ice surfaces within the instrument field of view), a spectral term with a law in wavelength to the power -1 (fine aerosol mode), and a spectral term with a law in wavelength to the power -4 (molecular scattering, adjacency effects from clouds and white surfaces). Tests are performed on selected MERIS imagery acquired over Arctic Seas. The derived ocean properties, i.e., marine reflectance and chlorophyll concentration, are compared with those obtained with the standard MEGS algorithm. The POLYMER estimates are more realistic in regions affected by the ice environment, e.g., chlorophyll concentration is higher near the ice edge, and spatial coverage is substantially increased. Good retrievals are obtained in the presence of thin clouds, with ocean-color features exhibiting spatial continuity from clear to cloudy regions. The POLYMER estimates of marine reflectance agree better with in situ measurements than the MEGS estimates. Biases are 0.001 or less in magnitude, except at 412 and 443 nm, where they reach 0.005 and 0.002, respectively, and root-mean-squared difference decreases from 0.006 at 412 nm to less than 0.001 at 620 and 665 nm. A first application to MODIS imagery is presented, revealing that the POLYMER algorithm is robust when pixels are contaminated by sea ice.

Paper Details

Date Published: 11 December 2012
PDF: 12 pages
Proc. SPIE 8525, Remote Sensing of the Marine Environment II, 85250I (11 December 2012); doi: 10.1117/12.981224
Show Author Affiliations
Robert Frouin, Univ. of California, San Diego (United States)
Pierre-Yves Deschamps, Univ. of California, San Diego (United States)
Hygeos, Euratechnologies (France)
Didier Ramon, Hygeos, Euratechnologies (France)
François Steinmetz, Hygeos, Euratechnologies (France)


Published in SPIE Proceedings Vol. 8525:
Remote Sensing of the Marine Environment II
Robert J. Frouin; Naoto Ebuchi; Delu Pan; Toshiro Saino, Editor(s)

© SPIE. Terms of Use
Back to Top