Comparison of Estimation Methods to Quantify Methane Plume Concentration at High Spatial Resolution from Hyperspectral Images

Abstract. The detection and the quantification of greenhouse gases is essential to climate change studies, avoid leakages in industrial site, prevent accidental explosions. Because of these properties, methane (CH4) is an important target gas in remote sensing quantification. We focused on industrial plume quantification with data obtained during airborne campaign with HySpex-Neo hyperspectral camera. The 1.4 m of spatial resolution allows comparing quantification methods on real data combined with full or semi-synthetic plume case. A linear method largely used in the literature is compared with a quantification method based on the rebuilt background image and the estimation of plume transmission (PTE method). We have developed a hybrid approach using intermediate results of two previous methods. The hybrid method is based on the optimal estimation (OE) formalism and is providing uncertainty estimates. We show that the linear method underestimates the concentration of plumes for concentration above 5000 ppm.m. For low reflectance pixels, the hybrid method is more robust than the PTE method. The uncertainty of the hybrid method is about 30% for pixels with concentrations above 5000 ppm.m. For a HySpex-Neo image, the total mass of the plume is underestimated by 30% with the linear method compared to the hybrid method.