Share Email Print
cover

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
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

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)

© SPIE. Terms of Use
Back to Top