The Estimation of Tree Height Based on LiDAR Data and QuickBird Imagery

1 Key Laboratory of Agricultural Information Technology, Ministry of Agriculture, Beijing, 100081, China; 2 College of Information and Electrical Engineering, China Agricultural University, Beijing 100083 Abstract: The estimation of tree height is advanced following the development of LiDAR technique. The estimation model of tree height considering suppressed trees is developed in order to extract tree height accurately using LiDAR data. Filtered LiDAR data and Quickbird imagery are segmented using watershed segmentation method based on mathematical morphology to get the boundary of trees. And the highest point in each canopy object is used to estimate tree height. Weibull distribution is used to estimate height distribution of the suppressed trees. The experiment results indicate that the watershed segmentation method based on mathematical morphology is an effective method to extract the boundary of trees. And the R between the tree height estimated using estimation model of tree height considering suppressed trees and the tree height measured by field work is 0.93.