Three-Dimensional Modeling and Visualization of Single Tree LiDAR Point Cloud Using Matrixial Form

Abstract

Tree modeling and visualization still represent a challenge in the Light Detecting And Ranging (LiDAR) area. Starting from the segmented tree point clouds, this paper presents an innovative tree modeling and visualization approach. The algorithm simulates the tree point cloud by a rotating surface. Three matrixes, X, Y, and Z are calculated by considering the middle of the projected tree point cloud on the horizontal plane. This mathematical form not only allows tree modeling and visualization, but also permits the calculation of geometric characteristics and parameters of the tree. The superimposition of the tree point cloud over the constructed model confirms its high accuracy where all the points of the tree cloud are within the constructed model. The tests with multiple single trees demonstrate an overall average fit between 0.3 and 0.89 m. The built tree models are also compliant with the Open Geospatial Consortium (OCG) City GML standards at the level of a physical model. This approach opens a door to numerous applications for visualization, computation, and study of forestry and vegetation in urban as well as rural areas.