Abstract: An approach of point cloud classification based on point feature histogram was proposed. Through building the spatial relations between the center point of the point cloud and its neighborhood points, a multidimensional histogram is formed which describes the geometry attribute in its neighborhood. The point feature histogram is used as the classification feature to divide the point cloud into vegetation, ground, and building by a random forest classifier. Comparing point feature histogram with the classic normal and height difference, the results show that the classification based on point feature histogram has better stability and better accuracy.