Thin-cloud effects on spectral/spatial remote sensing and information content within Vis-SWIR hyperspectral imagery

Joseph G. Shanks; William A.M. Blumberg; Steven J. Heising; Bruce V. Shetler

doi:10.1117/12.410368

23 August 2000 Thin-cloud effects on spectral/spatial remote sensing and information content within Vis-SWIR hyperspectral imagery

Joseph G. Shanks, William A.M. Blumberg, Steven J. Heising, Bruce V. Shetler

Author Affiliations +

Proceedings Volume 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI; (2000) https://doi.org/10.1117/12.410368
Event: AeroSense 2000, 2000, Orlando, FL, United States

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.

Citation Download Citation

Joseph G. Shanks, William A.M. Blumberg, Steven J. Heising, and Bruce V. Shetler "Thin-cloud effects on spectral/spatial remote sensing and information content within Vis-SWIR hyperspectral imagery", Proc. SPIE 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, (23 August 2000); https://doi.org/10.1117/12.410368

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