Detection of Point-Source Methane Enhancements from MethaneSAT Observations with Target-Driven Spectral Matching Algorithm

Yingqi Yan, Fei Li, Shiwei Sun, Shengxi Bai, Qidan Huang, Jiayi Liu, Yongguang Zhang

Methane is a potent greenhouse gas with large emissions often arising from localized point sources in industrial facilities. MethaneSAT, launched in 2024, observes the 1598-1683 nm band with sub-nanometer resolution and 100 m × 400 m footprints, enabling sensitive detection of methane absorption. We introduce an updated matched filter (BCMF) with covariance exclusion and a statistical correction for linearization bias. Simulations and retrievals show that BCMF removes a ∼20% underestimation, yielding unbiased enhancements. Across multiple emission scenarios, 19 plumes were detected and cross-section emission flux estimates agree with MethaneSAT proxy products (r=0.965, MAPE = 20.3%, n=16). These results demonstrate BCMF as a fast, robust approach for quantifying methane emissions with next-generation high-resolution satellite sensors.