Automatic Estimation of Tree Position and Stem Diameter Using a Moving Terrestrial Laser Scanner

Abstract

Airborne laser scanning is now widely used for forest inventories. An essential part of inventory is a collection of field reference data including measurements of tree stem diameter at breast height (DBH). Traditionally this is acquired through manual measurements. The recent development of terrestrial laser scanning (TLS) systems in terms of capacity and weight have made these systems attractive tools for extracting DBH. Multiple TLS scans are often merged into a single point cloud before the information extraction. This technique requires good position and orientation accuracy for each scan location. In this study, we propose a novel method that can operate under a relatively coarse positioning and orientation solution. The method divides the laser measurements into limited time intervals determined by the laser scan rotation. Tree positions and DBH are then automatically extracted from each laser scan rotation. To improve tree identification, the estimated center points are subsequently processed by an iterative closest point algorithm. In a small reference data set from a single field plot consisting of 18 trees, it was found that 14 were automatically identified by this method. The estimated DBH had a mean differences of 0.9 cm and a root mean squared error of 1.5 cm. The proposed method enables fast and efficient data acquisition and a 250 m2 field plot was measured within 30 s.