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A large number of studies have shown that earthquakes can cause methane gas anomalies in the atmosphere. This study selects a certain area in Sichuan-Yunnan region, taking the September 2021 Luxian earthquake in Sichuan as an example. Based on the atmospheric infrared detection of the hyperspectral sensor carried on the American earth observation satellite AQUA/EOS, using the mature RST algorithm to extract the methane anomaly information before and after the earthquake, the methane gas products obtained by the AIRS were used, and the time series analysis of the methane anomaly index was carried out for earthquakes of magnitude 6 or above in the region since 2008. The results show that the methane anomaly has a certain corresponding relationship with earthquakes, which is mainly manifested as breaking the regional historical methane spatial and temporal distribution law, and showing a certain change characteristic with the seismogenic process as a whole: initial intensification-anomaly intensification-peak-attenuation-quiet. There is no obvious relationship between the abnormal amplitude and the magnitude, but the abnormal duration may be related to the earthquake, that is, the methane anomaly caused by the earthquake is not accidental and has a certain abnormal duration. Anomalies may correspond to earthquakes in a certain area. In the follow-up, it is necessary to comprehensively analyze the structural geological conditions in the area, the magnitude of the earthquake, and the comparison of the radius of different study areas, and carry out more in-depth research. It is feasible to carry out seismic anomaly monitoring of methane gas in the Sichuan-Yunnan region based on remote sensing methods, which is related to the fact that the region itself is rich in a large amount of hydrocarbon gas. Rapid migration, diffusion and release into the atmosphere in weak areas such as the surface. Whether the seismic monitoring of methane can be carried out without the conditions of oil and gas fields outside this area, and the monitoring efficiency, etc., still need to be deeply analyzed through a lot of work.