Using state-of-the-art hydrodynamic models to generate synthetic data cubes for imaging spectral sensing applications

Jim Kao; William S. Smith; Barham W. Smith; Christoph C. Borel

doi:10.1117/12.453342

17 January 2002 Using state-of-the-art hydrodynamic models to generate synthetic data cubes for imaging spectral sensing applications

Jim Kao, William S. Smith, Barham W. Smith, Christoph C. Borel

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Proceedings Volume 4480, Imaging Spectrometry VII; (2002) https://doi.org/10.1117/12.453342
Event: International Symposium on Optical Science and Technology, 2001, San Diego, CA, United States

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.

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Jim Kao, William S. Smith, Barham W. Smith, and Christoph C. Borel "Using state-of-the-art hydrodynamic models to generate synthetic data cubes for imaging spectral sensing applications", Proc. SPIE 4480, Imaging Spectrometry VII, (17 January 2002); https://doi.org/10.1117/12.453342

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KEYWORDS

Data modeling

Atmospheric modeling

Atmospheric sensing

Sensors

Spectral resolution

Thermal modeling

Infrared imaging

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