In order to fully explore the application potential of single wood segmentation algorithm,and to realize the precise location of single wood position,and accurate division of tree crown,the single tree segmentation algorithm of UAV LiDAR plantation is proposed.Four artificial forest samples are selected according to the difference of dominant tree species and stand density by using the point cloud data of unmanned airborne LiDAR,and the watershed segmentation algorithm is evaluated by using detection rate P,accuracy R and overall accuracy F.The sensitivity analysis of single tree segmentation is carried out by changing the grid resolution and the density of point cloud.The results show that the segmentation results of the four algorithms are good,the overall F value is 0.89,the overall R value is 0.85,and the overall P value is 0.94. It is showed that the segmentation accuracy of sparse sample plots is higher than that of dense sample plots,and the watershed algorithm has the best accuracy and adaptability；selecting the appropriate CHM resolution can improve the segmentation accuracy of single trees,and the segmentation results based on CHM algorithm are the best when the grid resolution is 0.3 m×0.3 m；with the decrease of point cloud density,the segmentation accuracy of point cloud clustering segmentation algorithm decreases.When the point cloud density is 100% (65 pts·m -2),F value is 0.77,the point cloud density is 10% (6.5 pts·m -2),F value is 0.58,F value decreases by 0.19.