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Proceedings Paper

Thin-cloud effects on spectral/spatial remote sensing and information content within Vis-SWIR hyperspectral imagery
Author(s): Joseph G. Shanks; William A.M. Blumberg; Steven J. Heising; Bruce V. Shetler
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Paper Abstract

Modem optical sensors can provide high quality multi/hyperspectral data at high spatial resolution, permitting the application of diverse and sophisticated algorithms for remote sensing of the terrain and atmosphere. With global coverage of perceptible cloud exceeding seventy-five percent [Wylie & Menzel, 1999], it is important that the effects of intervening cloud be anticipated and minimized to realize the full potential of such systems. Cloud contamination also bears on the more general issue of "information content" in a HSI data stream. This paper will describe the application of the Vis-LWIR scene simulation tools CLDSIM / GENESSIS / MOSART for assessing spectral/spatial matched-filter algorithms for the detection and classification of features-of-interest against terrain, with and without thin clouds. Following a review of the methodology, the sensitivity of matched-filter SNR to cloud-cover, vs GSD, as captured in sequential subsets of the primary principal-components will be presented. The potential for mis-classification due to undetected thin-clouds will also be described.

Paper Details

Date Published: 23 August 2000
PDF: 12 pages
Proc. SPIE 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, (23 August 2000); doi: 10.1117/12.410368
Show Author Affiliations
Joseph G. Shanks, Photon Research Associates, Inc. (United States)
William A.M. Blumberg, Air Force Research Lab. (United States)
Steven J. Heising, Photon Research Associates, Inc. (United States)
Bruce V. Shetler, Photon Research Associates, Inc. (United States)

Published in SPIE Proceedings Vol. 4049:
Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI
Sylvia S. Shen; Michael R. Descour, Editor(s)

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