Point Cloud Data from Terrestrial Laser Scanning, Unmanned Aerial Vehicle and Aerial LiDAR Data: Estimations of Forest Stand Parameters in Open Forest Stand

Abstract

Two of the very basic forestry parameters, the Breast Height Diameter (DBH) and Tree Height (TH) are very effective when characterizing forest stands and individual trees. The traditional measurement process of these parameters takes a lot of time and consumes human power. However, because of the development of PC power and digital storage in recent years, 3D Point Cloud (PC) gains quickly provide a very detailed view of forestry parameters. PC data sources include Airborne LiDAR Systems (ALS), Terrestrial Laser Scanning (TLS) and finally, the Unmanned Air Vehicle (UAV) for forestry applications. In this study, the PC datasets from these sources were used to study the feasibility of the DBH and TH values of a D-stage oak stand. The DBH and TH estimates are compared with the onsite measurements, which are considered to be fundamental truths, to their performance due to overall error statistics, as well as the cost of calculation and the difficulties in data collection. The results show that the computer data obtained by TLS has the best average square error (0.22 cm for DBH and 0,051 m for TH) compared to other computer data. The size of Pearson correlation between TLS-based and on-site-based measurements has reached 0.97 and 0.99 for DBH, respectively.