The invention relates to a layered point cloud segmentation method based on DBSCAN. Firstly, a CSF is adopted to separate a ground point from a non-ground point; In a non-ground point segmentation process, point clouds in the vertical direction are layered according to a certain height, DBSCAN clustering is carried out on projection points of each layer on an XOY plane to obtain a central point ofeach cluster, all the clustered central points are projected to the XOY plane, and each object main body is clustered by utilizing DBSCAN to obtain a plurality of object main bodies; a judgment is made whether each main body point exists in each layer of each main body or not, judging the number of objects contained in each cluster, and finally, a cluster of multiple objects is segmented. For segmentation of side viewpoint cloud data, extraction of most of main bodies in a scene can be guaranteed, certain robustness is achieved, particularly, the invention has good performance in the scene with trees as the main component, and the result obtained through the method has certain significance in point cloud classification and point cloud three-dimensional reconstruction after point cloud segmentation.