Evaluation of MODIS SWIR and NIR-SWIR atmospheric correction algorithms using SeaBASS data

Using the NASA maintained ocean optical and biological in situ data that were collected during 2002–2005, we have evaluated the performance of atmospheric correction algorithms for the ocean color products from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua. Specifically, algorith...

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Bibliographic Details
Published in:Remote sensing of environment Vol. 113; no. 3; pp. 635 - 644
Main Authors: Wang, Menghua, Son, SeungHyun, Shi, Wei
Format: Journal Article
Language:English
Published: New York, NY Elsevier Inc 16.03.2009
Elsevier
Subjects:
Algorithm validation
Animal, plant and microbial ecology
Applied geophysics
Atmospheric correction for turbid waters
Biological and medical sciences
Dicentrarchus labrax
Earth sciences
Earth, ocean, space
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Internal geophysics
Marine
Marine geology
Ocean color remote sensing
Teledetection and vegetation maps
Algorithm validation
Ocean color remote sensing
Atmospheric correction for turbid waters
sea water
short period waves
Validation
algorithms
turbidity
color
NASA
near infrared radiation
remote sensing
Mixed method
in situ
Standards
evaluation
Reflection spectrometry
marine environment
ocean
algorithm performance
standard samples
near infrared spectroscopy
atmospheric correction
ISSN:0034-4257, 1879-0704
Online Access:Get full text
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Summary:Using the NASA maintained ocean optical and biological in situ data that were collected during 2002–2005, we have evaluated the performance of atmospheric correction algorithms for the ocean color products from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua. Specifically, algorithms using the MODIS shortwave infrared (SWIR) bands and an approach using the near-infrared (NIR) and SWIR combined method are evaluated, compared to the match-up results from the NASA standard algorithm (using the NIR bands). The in situ data for the match-up analyses were collected mostly from non-turbid ocean waters. It is critical to assess and understand the algorithm performance for deriving MODIS ocean color products, providing science and user communities with the important data quality information. Results show that, although the SWIR method for data processing has generally reduced the bias errors, the noise errors are increased due mainly to significantly lower sensor signal-noise ratio (SNR) values for the MODIS SWIR bands, as well as the increased uncertainties using the SWIR method for the atmospheric correction. This has further demonstrated that future ocean color satellite sensors will require significantly improved sensor SNR performance for the SWIR bands. The NIR–SWIR combined method, for which the non-turbid and turbid ocean waters are processed using the NIR and SWIR method, respectively, has been shown to produce improved ocean color products.
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ISSN:0034-4257
1879-0704
DOI:10.1016/j.rse.2008.11.005