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Proceedings Paper

Correlated-k based fast accurate bandpass radiance and transmittance calculations for hyperspectral and multispectral scenes
Author(s): Prabhat Acharya; Alexander Berk; Raphael Panfili; Steven M. Adler-Golden; Alan Wetmore; Richard Shirkey
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Paper Abstract

The ability to rapidly calculate at-sensor radiance over a large number of lines of sight (LOSs) is critical for hyperspectral and multispectral scene simulations and look-up table generation, both of which are increasingly used for sensor design, performance evaluation, data analysis, and software and systems evaluations. We have demonstrated a new radiation transport (RT) capability that combines an efficient multiple-LOS (MLOS) multiple scattering (MS) algorithm with a broad-bandpass correlated-k methodology called kURT-MS, where kURT stands for correlated-k-based Ultra-fast Radiative Transfer. The MLOS capability is based on DISORT and exploits the existing MODTRAN-DISORT interface. kURT-MS is a new sensor-specific fast radiative transfer formalism for UV-visible to LWIR wavelengths that is derived from MODTRAN's correlated-k parameters. Scattering parameters, blackbody and solar functions are cast as a few sensor-specific and bandpass-specific k-dependent source terms for radiance computations. Preliminary transmittance results are within 2% of MODTRAN with a two-orders-of-magnitude computational savings. Preliminary radiance computations in the visible spectrum are within a few percent of MODTRAN results, but with orders of magnitude speed up over comparable MODTRAN runs. This new RT capability (embodied in two software packages: kURT-MS and MODTRAN-kURT) has potential applications for remote sensing applications such as hyperspectral scene simulation and look-up table generation for atmospheric compensation analysis as well as target acquisition algorithms for near earth scenarios.

Paper Details

Date Published: 24 October 2007
PDF: 9 pages
Proc. SPIE 6748, Image and Signal Processing for Remote Sensing XIII, 67480G (24 October 2007); doi: 10.1117/12.738151
Show Author Affiliations
Prabhat Acharya, Spectral Sciences, Inc. (United States)
Alexander Berk, Spectral Sciences, Inc. (United States)
Raphael Panfili, Spectral Sciences, Inc. (United States)
Steven M. Adler-Golden, Spectral Sciences, Inc. (United States)
Alan Wetmore, Army Research Lab. (United States)
Richard Shirkey, Army Research Lab. (United States)

Published in SPIE Proceedings Vol. 6748:
Image and Signal Processing for Remote Sensing XIII
Lorenzo Bruzzone, Editor(s)

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