Exploiting the entire near-infrared spectral range to improve the detection of methane plumes with high-resolution imaging spectrometers

Abstract. Remote sensing has emerged as an important tool for the detection of methane plumes emitted by so-called point sources, which are common in the energy sector (e.g., oil and gas extraction and coal mining activities). In particular, satellite imaging spectroscopy missions covering the shortwave infrared part of the solar spectrum, such as PRISMA, EnMAP, or GaoFen-5 AHSI, have proven very effective for this application. These instruments sample the methane absorption features at the spectral regions around 1700 and 2300 nm, which enables the retrieval of per-pixel methane concentration enhancements. Data-driven retrieval methods, in particular those based on the matched filter concept, are widely used to produce maps of methane concentration enhancements from imaging spectroscopy data. These maps are being used for the detection of plumes and the subsequent identification of active sources. However, retrieval artifacts caused by particular surface components may sometimes appear as false plumes or disturbing elements in the methane maps, which complicates the identification of real plumes. In this work, we have used a matched filter that exploits a wide spectral window (1000–2500 nm) instead of the usual 2100–2450 nm window with the aim of reducing the occurrence of retrieval artifacts and background noise. This enables a greater ability to discriminate between surface elements and methane. The improvement in plume detection is evaluated through both simulated data and real data from areas including active point sources, such as the O&G industry from the Permian Basin (U.S.) and the coal mines from the Shanxi region (China). Data sets from the PRISMA, EnMAP, and GF5-02 satellite imaging spectrometers missions and from the airborne AVIRIS-NG instrument are used. Results show that the new approach reduces background noise and can remove a great fraction of the retrieval artifacts. For example, the analysis of a scene from the Shanxi region reveals that 15 plumes could be detected from the proposed procedure, whereas only 5 had been identified using the classical matched filter applied to the 2300 nm window. In addition, plume masking derived from this new approach let us propose a new procedure for point source quantification optimized for flux rate values lower than 1000 kg/h.