Abstract: Surface deformation monitoring is an important technical guarantee for safe production of coal mines and buildings maintenance in mining areas, and can provide the basic data information for environmental governance and ecological restoration in mining areas. In order to adapt to the development of modern surveying and mapping technology such as InSAR, 3D laser scanning, drone, photogrammetry, etc., andperfect the damage degree judgment indicators of area mapping technology applied to surface monitoring in coal mine area, to make up for the defects of traditional surveying and mapping based on point mapping to obtain surface tilting method, this study proposed a method of extracting the ground tilt based on the surface 3D laser scanning point cloud data of a working face of Daliuta Mine. Firstly, the point cloud data is denoised through S-G filter and the three-dimensional digital elevation model of the subsidence area is established. Secondly, the local surface fitting method is used to obtain the feature point normal vector, and the normal vector variation of each feature point before and after the surface deformation is calculated. Finally, the vector variation is compared with the true tilt angle of the feature points. The results show that the S-G filter can effectively eliminate the ground noise points and smoothing the point cloud data, which makes the edge gradient reduced by 31.8 and can improve the accuracy of generating DEM. Based on the point cloud data, the medium error between the slope deformation obtained from the local surface fitting method and that from the traditional method reaches 0.78°, which can meet the requirements of practical work.