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Proceedings Paper

Data analysis strategies for passive multispectral and hyperspectral infrared remote sensors
Author(s): Gary W. Small; Lin Zhang
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Paper Abstract

The detection of airborne chemicals is a key capability in a variety of environmental monitoring scenarios. For these applications, passive IR remote sensors collect IR emissions form natural and man-made sources such as the radiant emission from the earth or emissions from the stacks of a chemical plant. Chemical compounds absorb or emit IR energy at characteristic wavelengths, and the profile of these absorption or emission signatures can be used to identify a chemical and to estimate the amount present. Passive IR remote sensors can be implemented in either imaging or non- imaging configurations and can be constructed to acquire IR emission data in either multispectral or hyperspectral modes. Implementing these measurements successfully requires the construction of rugged, portable instruments and the development of computer processing techniques that allow the automated analysis of the large quantities of data acquired by these sensors. The research presented here describes the development of novel signal processing and pattern recognition methodology for application to multispectral imaging data and to non-imaging data acquired with a hyperspectral instrument. Remote sensing data were collected with these instruments mounted on an aircraft platform. Data acquired at an industrial site are used to demonstrate the characteristics of each sensor and the data analysis methodology.

Paper Details

Date Published: 22 February 2002
PDF: 12 pages
Proc. SPIE 4577, Vibrational Spectroscopy-based Sensor Systems, (22 February 2002); doi: 10.1117/12.455728
Show Author Affiliations
Gary W. Small, Ohio Univ. (United States)
Lin Zhang, Ohio Univ. (United States)


Published in SPIE Proceedings Vol. 4577:
Vibrational Spectroscopy-based Sensor Systems
Steven D. Christesen; Arthur J. Sedlacek, Editor(s)

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