Abstract: Soil moisture (SM) plays an irreplaceable role in agricultural production, and agricultural water use, yield estimation, and drought monitoring are all closely related to SM. Therefore, it is of great significance to monitor the changes in SM. At present, the remote sensing technique is an effective tool for the monitoring of the changes in SM in large areas. Optical remote sensing is sensitive to the composition of surface vegetation, while microwaves can penetrate vegetation to obtain the information of SM under vegetation. Meanwhile, the sensitivity of synthetic aperture Radar (SAR) backscattering to the changes in SM is greatly affected by the vegetation canopy. In areas covered by vegetation, microwave remote sensing will be affected by both surface roughness and vegetation. Therefore, the joint application of optical and SAR remote sensing can well remove the impacts of vegetation and surface roughness, thus improving the inversion accuracy of SM. This paper summarizes the remote sensing models and retrieval methods commonly used in the research on the cooperative inversion of SM using optical and SAR remote sensing. Meanwhile, it proposes the difficulties in the research and the future development of the cooperative inversion.