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Proceedings Paper

Using state-of-the-art hydrodynamic models to generate synthetic data cubes for imaging spectral sensing applications
Author(s): Jim Kao; William S. Smith; Barham W. Smith; Christoph C. Borel
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Paper Abstract

An airborne IR hyperspectral imaging sensor based on the Fourier transform spectrometer technique has been used for studying atmospheric gaseous plumes under the auspice of U.S. Department of Energy. Model generated synthetic data of spectral intensity associated withe the plume and the surface background is useful in terms of performing trade studies as well as testing new algorithms. To cope with the highly turbulent and transient atmospheric boundary layer where plume emissions and evolution are embedded, we have used a high-resolution (at the scale of 1 m) time-dependent Napier-Stoke atmospheric hydrodynamic code, HIGRAD, to replace the Gaussian/multi-fractal approach in the original package of the Los Alamos End-to-End Modeling of Imaging Spectral Sensing Applications (EMISSA). The output from HIGRAD is then used for calculations of radiance reaching the sensor through the Fast Atmospheric Signature Code (FASCODE) with a spectral resolution of 1 cm-1 or less. The modeled plume structure in concentrations and associated plume images in radiance bear great resemblance to the contrast model for its capability in quantifying the column densities of chemical species. The synthetic data produced through our approach proves to be effective in evaluation our understanding of the thermal infrared imaging process.

Paper Details

Date Published: 17 January 2002
PDF: 9 pages
Proc. SPIE 4480, Imaging Spectrometry VII, (17 January 2002); doi: 10.1117/12.453342
Show Author Affiliations
Jim Kao, Los Alamos National Lab. (United States)
William S. Smith, Los Alamos National Lab. (United States)
Barham W. Smith, Los Alamos National Lab. (United States)
Christoph C. Borel, Los Alamos National Lab. (United States)

Published in SPIE Proceedings Vol. 4480:
Imaging Spectrometry VII
Michael R. Descour; Sylvia S. Shen, Editor(s)

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