Literature DB >> 18349929

Atmospheric correction of satellite ocean color imagery: the black pixel assumption.

D A Siegel, M Wang, S Maritorena, W Robinson.   

Abstract

The assumption that values of water-leaving radiance in the near-infrared (NIR) are negligible enable aerosol radiative properties to be easily determined in the correction of satellite ocean color imagery. This is referred to as the black pixel assumption. We examine the implications of the black pixel assumption using a simple bio-optical model for the NIR water-leaving reflectance [rho(w)(lambda(NIR))](N). In productive waters [chlorophyll (Chl) concentration >2 mg m(-3)], estimates of [rho(w)(lambda(NIR))](N) are several orders of magnitude larger than those expected for pure seawater. These large values of [rho(w)(lambda(NIR))](N) result in an overcorrection of atmospheric effects for retrievals of water-leaving reflectance that are most pronounced in the violet and blue spectral region. The overcorrection increases dramatically with Chl, reducing the true water-leaving radiance by roughly 75% when Chl is equal to 5 mg m(-3). Relaxing the black pixel assumption in the correction of Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) satellite ocean color imagery provides significant improvements in Chl and water-leaving reflectance retrievals when Chl values are greater than 2 mg m(-3). Improvements in the present modeling of [rho(w)(lambda(NIR))](N) are considered, particularly for turbid coastal waters. However, this research shows that the effects of nonzero NIR reflectance must be included in the correction of satellite ocean color imagery.

Entities:  

Year:  2000        PMID: 18349929     DOI: 10.1364/ao.39.003582

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  5 in total

1.  Water-leaving contribution to polarized radiation field over ocean.

Authors:  Peng-Wang Zhai; Kirk Knobelspiesse; Amir Ibrahim; Bryan A Franz; Yongxiang Hu; Meng Gao; Robert Frouin
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2.  Monitoring Algal Blooms in drinking water reservoirs using the Landsat 8 Operational Land Imager.

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3.  Expected improvements in the quantitative remote sensing of optically complex waters with the use of an optically fast hyperspectral spectrometer-a modeling study.

Authors:  Wesley J Moses; Jeffrey H Bowles; Michael R Corson
Journal:  Sensors (Basel)       Date:  2015-03-13       Impact factor: 3.576

4.  Hybrid forward-selection method-based water-quality estimation via combining Landsat TM, ETM+, and OLI/TIRS images and ancillary environmental data.

Authors:  Min-Cheng Tu; Patricia Smith; Anthony M Filippi
Journal:  PLoS One       Date:  2018-07-30       Impact factor: 3.240

5.  Automated satellite remote sensing of giant kelp at the Falkland Islands (Islas Malvinas).

Authors:  Henry F Houskeeper; Isaac S Rosenthal; Katherine C Cavanaugh; Camille Pawlak; Laura Trouille; Jarrett E K Byrnes; Tom W Bell; Kyle C Cavanaugh
Journal:  PLoS One       Date:  2022-01-06       Impact factor: 3.240

  5 in total

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