Abstract: 【Objective】 Based on LiDAR point data of Tianshan sprucewith different densities, canopy height model is used to extract individual tree height of spruce in Tianshan Mountains, and the extraction accuracy of individual tree height from LiDAR point data with different densities was compared and analyzed in the hope of providing a theoretical basis for the extraction of individual tree height in Xinjiang mountain natural forests. 【Methods】 Based on the practice forest farm of Xinjiang Agricultural University, Tianshan spruce was selected as the research object. Combined with the measuring scale of each tree in the sample plot and the positioning of each tree in the sample plot by RTK, the digital surface model (DSM) and digital elevation model (DEM) were extracted by cloth analog filtering algorithm, and the canopy height model (CHM) was obtained by difference between the two. Finally,the single tree height of Tianshan spruce was obtained by the above model. 【Results】 The extracted Tianshan spruce density was 57.66 number/m², the average accuracy was 93.28%, the extraction effect was 1.60 number/m², the fit degree was only 0.754,6, the cloud density of single wood was 138.53 number/m², the recognition rate was 98.7%, the cloud density was 1.6 number/m², and the recognition rate was 70.8%. 【Conclusion】 DSM and DEM are extracted by cloth simulation filtering algorithm, and CHM has been calculated.If the point cloud density is about 2.76 number/m², it can be effectively used as the single tree height extraction point cloud density with large investigation scope and limited cost, and the relevant technical requirements of forestry resource investigation are met.