Methane (CH4) is an important greenhouse gas which has significant impact on the regional atmospheric ecological environments and global climate changing. Therefore, tracking and monitoring of near-surface methane anomalous emissions accurately are crucial. High spectral data could be easily affected due to the interference of complex surface backgrounds, the absorption peaks of other gases in the atmosphere also influence on the detecting atmospheric methane concentrations significantly. In addition, uncertainties in meteorological data may cause false alarms in the detection of near-surface methane anomalous emissions. In response to the above issues, this paper introduces a rapid remote sensing identification and flux estimation method for near-surface methane anomalous emissions. Firstly, generating methane absorption spectrum and screening out the methane-sensitive channels based on satellite spectral information; Then, using matching-filter algorithm to retrieve the methane enhancement. Based on morphological operation methods, identifying methane point source plumes and emission points; Finally, estimating methane emission fluxes by taking the wind field data into account comprehensively. The results from GF-5 satellite data in Shanxi Province showed this can locate the areas of high near-surface methane emissions and detect in coal mining areas. All identified methane strong point sources located in the high methane value areas detected when compared with the data from S5P/TROPOMI. It is also showed that there are coal mining facilities in the point source area by the high-resolution Satellite imagery. This method is significant effective for monitoring of large-scale methane anomalous emissions, and providing critical support for regional methane emission regulation.