Research Papers

Long-wave infrared imaging of vegetation for detecting leaking CO2 gas

[+] Author Affiliations
Jennifer E. Johnson

Montana State University, Electrical and Computer Engineering Department, Bozeman, Montana 59717-3780

Joseph A. Shaw

Montana State University, Electrical and Computer Engineering Department, Bozeman, Montana 59717-3780

Rick Lawrence

Montana State University, Land Resources and Environmental Sciences Department, Bozeman, Montana 59717-3120

Paul W. Nugent

Montana State University, Electrical and Computer Engineering Department, Bozeman, Montana 59717-3780

Laura M. Dobeck

Energy Research Institute, Montana State University, Bozeman, Montana 59717-2465

Lee H. Spangler

Montana State University, Chemistry and Biochemistry Department, Bozeman, Montana 59717-3780

J. Appl. Remote Sens. 6(1), 063612 (Dec 10, 2012). doi:10.1117/1.JRS.6.063612
History: Received September 13, 2012; Accepted November 12, 2012
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Abstract.  The commercial development of uncooled-microbolometer, long-wave infrared (LWIR) imagers, combined with advanced radiometric calibration methods developed at Montana State University, has led to new uses of thermal imagery in remote sensing applications. One specific novel use of these calibrated imagers is imaging of vegetation for CO2 gas leak detection. During a four-week period in the summer of 2011, a CO2 leak was simulated in a test field run by the Zero Emissions Research and Technology Center in Bozeman, Montana. An LWIR imager was deployed on a scaffold before and during the CO2 release, viewing a vegetation test area that included regions of high and low CO2 flux. Increased root-level CO2 concentration caused plant stress that led to reduced thermal regulation of the vegetation, which was consistent with increased diurnal variation of IR emission observed in this study. In a linear regression, the IR data were found to have a strong relationship to the CO2 emission and to be consistent with the location of leaking CO2 gas. Reducing the continuous data set to one image per day weakened the regression fit, but maintained sufficient significance to indicate that this method could be implemented with once-daily airborne images.

Figures in this Article
© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Jennifer E. Johnson ; Joseph A. Shaw ; Rick Lawrence ; Paul W. Nugent ; Laura M. Dobeck, et al.
"Long-wave infrared imaging of vegetation for detecting leaking CO2 gas", J. Appl. Remote Sens. 6(1), 063612 (Dec 10, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063612


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