Abstract: Canopy volume is an important tree measurement factor for trees, and the accurate measurement of its volume value plays an important role in the in-depth study of three-dimensional green quantity and regional carbon cycle. Aiming at the problems of overestimation and underestimation in the existing methods of measuring tree canopy volume from point cloud data,a α-shape boundary extraction method that took into account the point cloud boundary density and variable threshold was proposed. The length of the optimal linear-iterative step and the interval between layers of the method were determined through experimental analysis,so as to realize the accurate calculation of canopy volume. Firstly,the canopy point cloud data was sliced at equal intervals; then,an improved α-shape algorithm was used to extract the more realistic and natural boundary polygons of the point cloud slices; finally,the section area and the volume of the platform between each layer point cloud were calculated,and the canopy volume was obtained by adding the platform volumes. The experimental results showed that the accuracy of obtaining the canopy volume was related to the structure of branches and leaves inside the canopy and the point cloud density. Regardless of high-density or low-density canopies,the canopy volume value calculated by the improved α-shape algorithm not only had good stability,but also was more accurate than that of existing methods,which avoided the overestimation of Graham convex hull algorithm,and was more conducive to the calculation of the overall volume of the canopy compared with the volume element accumulation method.