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Proceedings Paper

Advanced atmospheric modeling with perturbation for VNIR/SWIR hyperspectral data analysis
Author(s): Perry Fuehrer; Glenn Healey; David Slater; Brian Rauch; Anthony Ratkowski
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Paper Abstract

Models for material reflectance properties, atmospheric effects and hyperspectral sensor properties in the VNIR/SWIR spectral region can be used to predict the detailed spectral structure of spectra to be measured in future field data collections. It is useful to have databases of predicted spectra that span a wide range of possible atmospheric conditions, given that the ambient environmental conditions for a measurement are rarely known in advance. A radiative transfer (RT) code such as MODTRAN® can be used to model the effects of atmospheric propagation in the predicted spectra as measured by a remotely deployed sensor. We are generating a database of optimized atmospheres that considers variations in solar angle, vertical-path-integrated water vapor density, and aerosol and cloud scatterer types and densities. This database provides a large set of discrete atmospheres. To improve the accuracy of the atmospheric spectral functions for a given hyperspectral image, we have developed an atmospheric perturbation model that is based on a rigorous physics-based approach to the variation of the spectral functions that are contained in the database. We will demonstrate how this new approach to atmospheric modeling improves the accuracy of models for VNIR/SWIR spectra collected with a space-based hyperspectral sensor.

Paper Details

Date Published: 12 May 2010
PDF: 12 pages
Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 769517 (12 May 2010); doi: 10.1117/12.850776
Show Author Affiliations
Perry Fuehrer, HyperTech Systems (United States)
Glenn Healey, HyperTech Systems (United States)
David Slater, HyperTech Systems (United States)
Brian Rauch, HyperTech Systems (United States)
Anthony Ratkowski, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 7695:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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