Large-scale deformation can not be detected by traditional D-InSAR technique because of the limit of its detectable deformation gradient,we propose a method that combines SAR data with point cloud data obtained by 3D laser scanning to improve the gradient of deformation detection.The proposed method takes advantage of high-density of 3D laser scanning point cloud data and its high precision of point positioning after 3D modeling.The specifc process can be described as follows:frst,large-scale deformation points in the interferogram are masked out based on interferometric coherence;second,the interferogram with holes is unwrapped to obtain a deformation map with holes,and last,the holes in the deformation map are flled with point cloud data using inverse distance weighting algorithm,which will achieve seamless connection of monitoring region.We took the embankment dam above working face of a certain mining area in Shandong province as an example to study large-scale deformation in mining area using the proposed method.The results show that the maximum absolute error is 64 mm,relative error of maximum subsidence value is 4.95%,and they are consistent with leveling data of ground observation stations,which confrms the feasibility of this method.The method we presented provides new ways and means for achieving large-scale deformation monitoring by D-InSAR in mining area. Large-scale deformation can not be detected by traditional D-InSAR technique because of the limit of its detectable deformation gradient, we propose a method that combines SAR data with point cloud data obtained by 3D laser scanning to improve the gradient of deformation detection. proposed method takes advantage of high-density of 3D laser scanning point cloud data and its high precision of point positioning after 3D modeling. The specifc process can be described as follows: frst, large-scale deformation points in the interferogram are masked out based on interferometric coherence; second, the interferogram with holes is unwrapped to obtain a deformation map with holes, and last, the holes in the deformation map are flixed with point cloud data using inverse distance weighting algorithm, which will achieve seamless connection of monitoring region .We took the embankment dam above working face of a certain mining area in Shandong province as an example to study large-scale deformation in minin g area using the proposed method. The results show that the maximum absolute error is 64 mm, relative error of maximum subsidence value is 4.95%, and they are consistent with leveling data of ground observation stations, which confrms the feasibility of this method. method we presented provides new ways and means for achieving large-scale deformation monitoring by D-InSAR in mining area.