Tree Height Derivation under Homogeneous Tree Pattern by Segmentation Algorithm

Abstract

Tree height is an important element in plantation areas to determine the tree's maturity for harvesting. Airborne Laser Scanning (ALS) technology can give accurate elevation using point cloud data. However, this technology is quite expensive and unsuitable for small areas and low-budget projects. This research focuses on the UAV technology, exploring the appropriate methods of determining a tree height from the UAV’s photogrammetry images. This research aims to evaluate the tree height from the delineation of the tree crown. Three different algorithms have been used in this research to delineate tree crowns. The delineate tree crowns were extracted in vector format, and the crowns were used to calculate the tree height using the specific formula. The results of tree heights were assessed using Residual Mean Square Error (RMSE) to determine the accuracy of the outcome. It was found that the OBIA algorithm gives the best accuracy among these three algorithms. It is followed by WS algorithm and then IWS algorithm. The OBIA algorithm can give an accuracy of about 0.444m at 40m and 0.381m for 60 altitude. The accuracy for WS and OBIA stated that the 60m altitude gives the better accuracy compared to 40m altitude. However, the IWS gives the vice versa result. This research could help the planters to manage their plantations for the harvesting process.