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Proceedings Paper

Recent efforts to validate EOS observations. Hyperspectral data noise characterization using PCA: application to AIRS
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Paper Abstract

Exploiting the redundancy in high spectral resolution observations, dependent set Principle Component Analysis (PCA) is a simple yet very powerful tool not only for noise filtering and lossy compression, but also for the characterization of sensor noise and other variable artifacts using Earth scene data. Our approach for dependent set PCA of AIRS Earth scene data is presented. Aspects of the analyses include 1) estimation of NEDT using PCA and comparisons to values derived from on-board blackbodies, 2) estimation of the scene dependence of NEDN, 3) estimation of the spectrally correlated component of NEDT and comparison to pre-launch analyses using blackbody views, 4) investigation of non- Gaussian noise behavior, and 5) inspection of individual PCs. The results of the PCA analyses are generally consistent with results obtained pre-launch and on-orbit using blackbody and/or space view data. Specific findings include: 1) PCA estimates of AIRS spectrally random and spectrally correlated NEDN compare well with estimates computed from on-board blackbody and space views, 2) the signal dependence of AIRS NEDN is accurately parameterized in terms of the scene radiance, 3) examination of the reconstruction error allows non-Gaussian phenomenon such as popping to be characterized, and 4) inspection of the PCs and individual PC filtered radiance spectra is a powerful technique for diagnosing low level artifacts in hyperspectral data.

Paper Details

Date Published: 1 September 2006
PDF: 9 pages
Proc. SPIE 6301, Atmospheric and Environmental Remote Sensing Data Processing and Utilization II: Perspective on Calibration/Validation Initiatives and Strategies, 630107 (1 September 2006); doi: 10.1117/12.683981
Show Author Affiliations
David Tobin, Univ. of Wisconsin, Madison (United States)
Henry Revercomb, Univ. of Wisconsin, Madison (United States)
Paolo Antonelli, Univ. of Wisconsin, Madison (United States)
Kenneth Vinson, Univ. of Wisconsin, Madison (United States)
Steven Dutcher, Univ. of Wisconsin, Madison (United States)
Robert Knuteson, Univ. of Wisconsin, Madison (United States)
Joseph Taylor, Univ. of Wisconsin, Madison (United States)
Fred Best, Univ. of Wisconsin, Madison (United States)
Chris Moeller, Univ. of Wisconsin, Madison (United States)
Mathew Gunshor, Univ. of Wisconsin, Madison (United States)


Published in SPIE Proceedings Vol. 6301:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization II: Perspective on Calibration/Validation Initiatives and Strategies
Allen H. L. Huang; Hal J. Bloom, Editor(s)

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