Individual Trees Recognition in Dense Forest Based on Airborne LiDAR

Abstract:

By analyzing the shortage of traditional approach,a new individual trees recognition method was proposed. Firstly, the generalized Gaussian function was used to analyze the fitting pulse shape LiDAR data, and the high density point cloud and the waveform parameters were obtained, then the non-ground points were gained by establishing DEM; secondly, the spatial characteristics of point cloud was computed to receive forest points; lastly, Markov random fields were exploited to label individual trees in 3D. The experimental results show that this method can effectively improve the recognition accuracy, especially in the low dense, small trees identification effect, and the average recognition accuracy is 75%. 