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Updated: Aug 18, 2026

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions
Published on: January 10, 2019
Global spectral irradiance variability and material discrimination at Boulder, Colorado
Zhihong Pan1, Glenn Healey, David Slater
1Computer Vision Laboratory, Department of Electrical and Computer Engineering, University of California, Irvine, Irvine, California 92697, USA.
Abstract:
We analyze 7,258 global spectral irradiance functions over 0.4-2.2 microm that were acquired over a wide range of conditions at Boulder, Colorado, during the summer of 1997. We show that low-dimensional linear models can be used to capture the variability in these spectra over both the visible and the 0.4-2.2 microm spectral ranges. Using a linear model, we compare the Boulder data with the previous study of Judd et al. [J. Opt. Soc. Am. 54, 1031 (1964)] over the visible wavelengths. We also examine the agreement of the Boulder data with a spectral database generated by using the MODTRAN 4.0 radiative transfer code. We use a database of 223 minerals to consider the effect of the spectral variability in the global spectral irradiance functions on hyperspectral material identification. We show that the 223 minerals can be discriminated accurately over the variability in the Boulder data with subspace projection techniques.

