The light detection and ranging (LiDAR) technique, which has the advantages of high efficiency and high accuracy in forest survey and is superior to the traditionalinformation acquisitionmethods, can be used to quickly obtain high-resolution mapping of morphological structures of forest. In this paper, two rubber forest plots (forest plot 1, clonePR107; forest plot 2, clone CATAS7-20-59) are taken as the study subjects, which are under the long-term impact of wind-induced disturbance severity and located in Danzhou city, the largest rubber production base of Hainan Island, China. First, point cloud of the forest plots through man-loaded mobile LiDAR was collectedand Ruili entropy method was designed to process the scanned data for calculating the slope angle of tree trunk (typhoon-induced) in order to find the canopy centre of each tree. Second, after the vertical projection of scanned forest points, Watershed and Mean shift algorithm were adopted to realize individual tree canopy delineation. Finally, many tree parameters, such as crown breadth, Diameter at Breast Height (DBH), crown volume, leaf area density, leaf distribution and included angle between trunk and main branches, were deduced automatically for analyzing the impact of typhoon disturbance on the two forest plots. Overall parameters obtained from our methods were compared with manual field measurements. The calculated average crown diameter in west-east direction of rubber trees in forest plot 1 and plot 2 using our method were 3.95 and 3.73 m, respectively, with false rate of 1.74% for forest plot 1 and 6.27% for plot 2. The calculated average crown diameter in north-south direction of rubber trees in forest plot 1 and plot 2 using our method were 6.47 and 6.51 m, respectively, with false rate of 4.02% for forest plot 1 and 2.54% for plot 2. The calculated average diameter at breast height (DBH) for forest plot 1 and plot 2 using our method were 5.20 and 4.73 cm, respectively, with false rate of 2.44% for forest plot 1 and 0.64% for plot 2. The calculated average crown volume for forest plot 1 and plot 2 using our method were 168.01 and 141.80 m3, respectively, with false rate of 0.67% for forest plot 1 and 0.85% for plot 2. The calculated average inclination angle of rubber trunk for forest plot 1 and plot 2 using our method were 18.80° and 13.11°, respectively, with false rate of 5.53% for forest plot 1 and 7.09% for plot 2. The calculated average included angle between trunk and branch for forest plot 1 ranged from 45.21° to 69.23°, and the calculated average included angle between trunk and branch for forest plot 2 ranged from 10.63° to 32.14°. Thedifference in the included angles of two forest plots was nearly 62.63%. Meanwhile, the leaf area index (LAI) of forest plot 1 derived fromhemispherical photos of various zenith angles was generally higher than forest plot 2. Compared with the in-situ measurements, the forest parameters from the subsample (scanned data of 150 trees per forest plot) were accurately retrieved using our method with a deviation of less than 8%. A variety of disturbance, such as the perspective occlusion caused by closed forest canopies, the error produced by multi-scan registration, vegetative elements moved by wind during the scanning process, beam divergence and scanning range constraint of the scanner, hampers the accurate scanned data acquisition and generates computer errors in the algorithm. Meanwhile, the included angle between trunks and branches, canopy volume and leaf area index of rubber tree clone PR107 (in forest plot 1) were overall higher than the parameters of rubber tree clone CATAS7-20-59 (in forest plot 2), resulting in the existence of higher vulnerability of clone PR107 than clone CATAS7-20-59 when wind damage propagation occurred in the forest plots. Thus, our research can be used to study the effects of wind disturbance on different forest plots and to quantify ecological instability of the forest in response to wind excitation. Our method makes a contribution to solving the problem of tree canopy delineation and forest parameter retrieval using man-loaded laser scanning technique, showing promise for further exploration of utilizing mobile terrestrial LiDAR as an effective tool for the applications in forest survey.