Tree Diameter at Breast Height Automatic Estimation Based on Forest Terrestrial Laser Scanning

Abstract:

This paper presents a tree diameter at breast height （DBH）estimation algorithm using terrestrial laser scanning （TLS） based on the randomized random sample consensus （RANSAC） model. First， the forest cloud data were filtered by the cloth simulation filtering （CSF） algorithm. Digital elevation model （DEM） and the point cloud at the DBH of the tree were extracted. Then， Euclidean distance clustering was performed. Finally， the tree model was fitted on the basis of the randomized RANSAC model. The algorithm was verified on laser point cloud data from two sample plots in Qingpu District， Shanghai. The average biases from the actual diameter of trees were 0.79 cm and 0.52 cm， respectively. Experiment results show that the algorithm is better than those based on Hough transform or the least-squares in terms of the accuracy and running time.