The Method of Extracting Information of Cunninghamia lanceolata Crown Combined with RGB and LiDAR Based on UAV

With the Nianzhu forest field as the research area, the visible light image and lidar data of UAV were used as the data source, and the watershed segmentation algorithm and object-oriented method were used to extract single tree crown width information in different forest canopy densities and verify the extraction accuracy. First, tree crown was extracted from visible light image using object-oriented method which was to extract the canopy tree crown range. Then, the watershed segmentation method was used to obtain the preliminary segmentation results of single tree crown based on CHM. Finally, divided again to extract the information of single tree crown based on the preliminary segmentation boundary and crown area. The results of show that the extraction effect of individual tree crown and area is better in different density. The F-measure was between 88.07%–95.08% and 78.57%–88.29%; and a linear regression model was established between extracted crown area and the measured crown area, the R² were 0.8591 and 0.7367 and RMSE were 2.49m² and 3.29m². A linear regression model was established between extracted crown diameter and the measured crown diameter, the R² were 0.8306 and 0.7246, RMSE of which were 0.46 m and 0.57 m. Based on the visible light image of the UAV, the tree crown area extracted by object-oriented multi-scale segmentation method has eliminated the influence of naked and shrub in the forest. At the same time, the UAV-LiDAR data can accurately distinguish individual tree. The combination of the 2 data sources can take advantages of both and improves the extraction accuracy of single tree crown. This study can provide a reference for quickly obtaining individual tree crown information under different canopy density stands.