It has been realized that the points collected twice by the laser scanner for the same target do not coincide

and the landslide displacement cannot be quickly determined by direct comparison of the point cloud. Because the position of a single point cloud is uncertain and the density of regional point clouds is stable

the density of the point cloud can be used as the characterization of the deformation of the landslide surface. The article proposes a landslide displacement monitoring method based on point cloud density characteristics. First

the discrete three-dimensional point cloud is converted into a two-dimensional density image. Then

the particle image velocimetry technique is used to analyze the correlation between the two point cloud density images before and after displacement

thereby to calculate the relative displacement value of each subset in the raster image. When the entire displacements of each subset are calculated

the plane displacement field of the target area is obtained. The indoor block movement test shows that the calculation accuracy of this method is affected by the deformation gradient

which will produce a certain degree of error at the place where the ground surface changes drastically

and the subset correlation coefficient cannot reach 1.0. In the displacement monitoring of the Huangzangsi landslide

the method was used to identify the changing area of the slope

and the plane displacement field of the landslide was calculated. The calculation results intuitively reflect the deformation of the landslide surface

which verifies the practicability of the proposed method.