Abstract: In view of the characteristics of UAV LiDAR technology to quickly obtain high-precision three-dimensional spatial information of targets, the collected data was used to extract and verify the tree height of Pinus massoniana, and the single tree parameter information extracted from the point cloud was extracted. Multiple linear regression, random forest, extreme gradient lifting and other methods were used to establish the diameter fitting model of Pinus massoniana and verify the results. The results showed that the tree height extracted by point cloud is highly correlated with the real tree height, and the determination coefficient R2of the fitting model is 0.78, and the root-mean-square difference is 0.66 m. In the case of a small number of parameter features, the multiple linear regression fitted DBH model has the best results with R2of 0.64 and root-mean-square difference of 1.21 cm. Airborne LiDAR point cloud extraction and fitting of Pinus massoniana single tree parameters and DBH are reliable, which provides a certain basis for the realization of large-area airborne LiDAR point cloud to obtain the DBH information of Pinus massoniana.