Methane is a prevalent greenhouse gas with potent heat trapping capabilities, but methane emissions can be difficult to detect and track. Hyperspectral imagery is an effective method of detection which can locate methane emission sources in order to mitigate leaks, as well as provide accountability for reaching emissions reduction goals. Because of methane’s absorption features in the infrared, both shortwave infrared (SWIR) and longwave infrared (LWIR) hyperspectral sensors have been used to accurately detect methane plumes. However, surface, environmental and atmospheric background conditions can cause methane detectability to vary. This study compared methane detectability under varying environmental conditions for two airborne hyperspectral sensors: AVIRIS-NG in the SWIR and HyTES in the LWIR. For this trade study, we modeled methane plume detection under a wide variety of precisely known conditions by making use of synthetic images which were comprised of MODTRAN-generated radiance curves. We applied a matched filter to these images to assess detection accuracy, and used these results to identify the conditions which have the greatest impact on detectability in the SWIR and LWIR: surface reflectance, surface temperature, and water vapor concentration. We then computed the specific boundaries on these conditions which make methane most detectable for each instrument. The results of this trade study can help inform decision making about which sensors are most useful for various types of methane emission analysis, such as leak detection, plume mapping, and emissions rate quantification.

Library of Congress Subject Headings

Methane--Detection; Hyperspectral imaging--Evaluation

Publication Date


Document Type


Student Type


Degree Name

Imaging Science (MS)

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


John Kerekes

Advisor/Committee Member

Emmett Ienitilluci

Advisor/Committee Member

Carl Salvaggio


RIT – Main Campus

Plan Codes