Tree modelling from mobile laser scanning data‐sets

Abstract In recent times mobile laser scanning (MLS) has been used to acquire massive 3D point clouds in urban areas and along road corridors for the collection of detailed data for 3D city modelling, building façade reconstruction and capture of vegetation and road features for inventories. The objectives of this paper are the extraction of tree features from such data‐sets and the modelling of trees for the purpose of visualisation in 3D city models. After the detection of high vegetation the point cloud is reduced using a 3D alpha shape approach. Then the required model parameters such as crown and stem height, crown and stem diameter, and crown shape are derived and the trees are modelled individually in a realistic manner. The tree model so generated correctly represents the overall appearance of the tree. However, the inner structure such as the branching of the tree crown is parameterised. The workflow reduces the point cloud by means of a step‐by‐step process, which eases the handling of the massive MLS data‐sets. The thinning using 3D alpha shapes reduces the amount of data to be processed by about 95%. It is shown that the model parameters are not influenced by the thinning procedure employed. This proves the robustness of the data reduction method and the tree modelling approach.