Abstract: Abstract: Accurate structural parameters and crown characterization of large isolated apple trees were vital for adjusting spray doses, trimming, autonomous harvesting. According to previous research, canopy measurement methods to characteristic the whole tree structure could be classified in two groups: Manual measurements and electronic procedures to estimate tree dimensions. These methods were time consuming and required specialist knowledge, so a simpler crown characterization measurement method was required. Terrestrial laser scanning (TLS) could provide accurate canopy information through non-destructive methods, which filled the gap between tree scale manual measurements and large scale LiDAR measurements. Laser scanning delivers a dense cloud of points, and this raw point data were filtered for deriving a digital terrain model and subsequent fitting of a parametric stem model. In this study, Trimble TX8 had been used to getting point clouds of the apple tree canopy with trees height 3.2-5.1 m and 7 years old, in the orchard environment. A method and registration algorithm for reconstructing the three-dimensional (3D) apple tree canopy based on terrestrial laser scanner point cloud data from apple trees was presented. After an initial alignment had been obtained from this last set of correspondences, the object ball point clouds were extracted, and the noise was deleted by hands. In order to improve convergence speed, KD-tree improved ICP(iterated closest points), and combined with object ball, to estimate the optimal transform. The object residual errors and fitting errors at different distances between object and scanner were analyzed. Results showed that, the average residual errors was 1.3 mm, and the average fitting errors was 0.95 mm at the distance from 1 000 to 13 000 mm. All the errors were less than the traditional registration accuracy 5 mm. In addition, wind as an importance factor always influenced point clouds quality. In order to find the influence between them, several pieces of branches, apples and 80 pieces of leaves had been extracted in the wind speed from 0.9 to 4.5 m/s. And the branches and apple structures, the leaf characteristics were studied under different wind speed. Results showed that, the branches and apple outline clearly, both the single tree and group trees, the geometric parameters, such as apple diameter, stem diameter, trunk detection, canopy height, canopy diameter, planting distance, line spacing, could been extracted easily even if the average wind speed was 4.5m/s in the scanning instant. Great changes had taken place in the leaves edge and thickness, when the wind speed changed from 0.9 to 2.4 m/s. The thickness of the leaf profile had changed from 2.2 to about 35.8 mm, and the original point clouds Delaunay triangular mesh also became irregular. And long and narrow triangle appeared at the moment of the average wind speed 1.9 m/s. The three leaf thickness fitting curves, as quadratic curve, cubic curve and exponential curve, were in good agreements for the whole range of studied volumes (R2 =0.976, R2 =0.986 and R2 = 0.983, P < 0.001). The fitting curve showed that, apple canopy 3D point cloud data could be obtained with good quality in orchard environment. Comparing with the traditional manual measurement, the relative errors of the canopy parameter measurement values obtained from 3D point clouds data were less than 4%.