Comparison of methane plume detection using shortwave and longwave infrared hyperspectral sensors under varying environmental conditions

Abstract

Identifying methane gas emissions sources is crucial to the mitigation of greenhouse gas emissions, and hyperspectral imagery is effective at methane leak detection. Hyperspectral sensors in both the shortwave infrared (SWIR) and longwave infrared (LWIR) can detect methane plumes, but surface background and atmospheric conditions cause methane detectability to vary depending on the sensor’s spectral region. This study compared methane detectability under varying background conditions for two airborne hyperspectral sensors: AVIRIS-NG in the SWIR, and HyTES in the LWIR. The trade study modeled methane plumes under a wide variety of conditions by making use of synthetic images generated using MODTRAN radiance curves, and applying a matched filter for methane detection. The modeling method was validated through comparison with real AVIRIS-NG and HyTES data. In the SWIR, the factors which most strongly influenced methane detectability were surface reflectance of the background and surface reflectance directly underneath the methane plume. In the LWIR, the temperature of the methane plume and the temperature of the surface had the highest impact on methane detection. We 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 methane studies, such as leak detection, plume mapping, and emissions rate quantification.