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Sensors 2010, 10(9), 8652-8662; doi:10.3390/s100908652
Article

Predicting the Detectability of Thin Gaseous Plumes in Hyperspectral Images Using Basis Vectors

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Received: 17 July 2010; in revised form: 13 August 2010 / Accepted: 19 August 2010 / Published: 17 September 2010
(This article belongs to the Section Physical Sensors)
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Abstract: This paper describes a new method for predicting the detectability of thin gaseous plumes in hyperspectral images. The novelty of this method is the use of basis vectors for each of the spectral channels of a collection instrument to calculate noise-equivalent concentration-pathlengths instead of matching scene pixels to absorbance spectra of gases in a library. This method provides insight into regions of the spectrum where gas detection will be relatively easier or harder, as influenced by ground emissivity, temperature contrast, and the atmosphere. Our results show that data collection planning could be influenced by information about when potential plumes are likely to be over background segments that are most conducive to detection.
Keywords: plume; detection; LWIR; basis vectors; NECL plume; detection; LWIR; basis vectors; NECL
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Anderson, K.K.; Tardiff, M.F.; Chilton, L.K. Predicting the Detectability of Thin Gaseous Plumes in Hyperspectral Images Using Basis Vectors. Sensors 2010, 10, 8652-8662.

AMA Style

Anderson KK, Tardiff MF, Chilton LK. Predicting the Detectability of Thin Gaseous Plumes in Hyperspectral Images Using Basis Vectors. Sensors. 2010; 10(9):8652-8662.

Chicago/Turabian Style

Anderson, Kevin K.; Tardiff, Mark F.; Chilton, Lawrence K. 2010. "Predicting the Detectability of Thin Gaseous Plumes in Hyperspectral Images Using Basis Vectors." Sensors 10, no. 9: 8652-8662.



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