A Decidious-coniferous Single Tree Classification and Internal Structure Derivation Using Airborne Lidar Data

This project has two main purposes; the first is to perform deciduous-coniferous classification for 65 trees by using the leaf-on single flight LiDAR data. It was done by looking at the geometrical properties of the crown shapes (spherical, conical or cylindrical), these shapes were developed by a rule-driven method Lindenmayer Systems (L systems). Two more parameters that are data driven (convex hull analysis and buffer analysis) were developed to further capture the geometrical differences between deciduous and coniferous trees. Proposed methods are scale independent and arithmetically simple, they were developed simply by looking at the geometrical differences between the two types of trees. The classification rate was cross-validated and trees are 85% 88% correctly classified. The second part of the project is to derive the internal structures of the LiDAR tree according to the results obtained from the first part. Internal structures include bole and branches; the location and orientation of the bole was done by connecting the geographic centres of horizontal slices of the tree. The branches were derived by k-means clustering techniques, different types of trees will yield a different type of branching structures for better visualization. * Corresponding author.