Surface subsidence in mining areas poses significant risks, including ground collapse, infrastructure damage, and threats to resident safety. Traditional monitoring methods, such as leveling surveys, are labor-intensive and lack spatial continuity, while conventional InSAR and probabilistic integration methods face limitations in accuracy and automation. To address these challenges, this study proposes a refined monitoring method by integrating spatial interpolation with InSAR technology. The paper combines the advantages of spatial interpolation in InSAR and probabilistic integration method, and proposes a method of fine monitoring of surface settlement in mining area jointly by InSAR and probabilistic integration method. The paper takes a mining area in Shandong as the study area, and adopts the 21-view SAR images during the period of October 16, 2016-March 4, 2018 and the level measurement data of the working face to verify the feasibility and accuracy of the method. The method is able to obtain settlement results that match the actual situation under the premise of reducing the level monitoring workload, and its monitoring capability is obviously better than that of conventional InSAR and probability integral method.