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- W2012122528 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." @default.
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- W2012122528 date "2000-08-23" @default.
- W2012122528 modified "2023-09-23" @default.
- W2012122528 title "Thin-cloud effects on spectral/spatial remote sensing and information content within Vis-SWIR hyperspectral imagery" @default.
- W2012122528 doi "https://doi.org/10.1117/12.410368" @default.
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