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Proceedings Paper

Modeling satellite imaging sensors over optically complex bodies of water
Author(s): Robert Nevins; Aaron Gerace
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Paper Abstract

Although several currently operating remote sensing satellites can take effective data from case-1 waters, which are dominated by phytoplankton, few instruments have the appropriate spatial and radiometric resolution for taking effective data from Case 2 waters, which contain significant levels of chlorophyll, suspended material, and color-dissolved organic matter. The Operational Land Imager, which was launched on February 11th 2013, should have sufficient spatial and radiometric resolution to take useful data from Case 2 waters as well as the continental Earth. The purpose of this study was to compare the constituent retrieval accuracy of the Operational Land Imager over these waters to that of existing sensors. The models used to evaluate the sensors were based on signal-to-noise ratios calculated from image data, spectral response functions, and bit depths of each satellite. The sensor models were used to sample radiance spectra from different Hydrolight simulations, which were calculated based on user-specified levels of the Case 2 constituents. Then, the concentrations were retrieved for each satellite based on the sensor models, and the error was found with respect to the known levels for each spectral curve. Thus, we present an approximation of how effective the Operational Land Imager will be for monitoring Case 2 waters, compared to existing sensors.

Paper Details

Date Published: 18 May 2013
PDF: 6 pages
Proc. SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 87431W (18 May 2013); doi: 10.1117/12.2015501
Show Author Affiliations
Robert Nevins, St. Olaf College (United States)
Aaron Gerace, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 8743:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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