Abstract: To address the limitations of a single remote sensing method in the identification accuracy of shallow coal fire areas, this study takes the Wuda Coalfield fire area as a case study. Based on multiple scenes of Landsat-8 OLI/TIRS Collection 2 Level 2 images and Sentinel-1A images, multi-source remote sensing identification research on shallow coal seam fire areas was realized through methods like threshold extraction and spatiotemporal coupling analysis with overlay operations. The results show that the differences in surface temperature are significantly correlated with seasonal changes, and the characteristics of temperature anomaly areas are more prominent in non-?summer periods. The stable temperature anomaly areas obtained through threshold screening and time-scale verification are basically consistent with the measured coal fire areas. There are multiple abnormal subsidence areas in the study area, with a maximum deformation rate of -192 mm/a, and the distribution of surface subsidence areas is basically consistent with that of the measured coalfield fire areas. Surface temperature anomalies and deformation anomalies exhibit minor discrepancies in their spatial morphological distribution, and there is a certain spatial offset between the peak values of surface temperature and deformation; however, the two show obvious synergistic consistency in the temporal dimension. Compared with a single remote sensing method, By adopting the spatio-temporal combined analysis approach of long-term surface temperature and deformation, it can effectively eliminate the interference of temperature anomalies and surface deformation caused by non-coal fire factors, and offering reliable technical support for the extensive regional general survey and scientific prevention and governance of coal fire disasters