Individual Tree Parameters Estimation from Terrestrial Laser Scanner Data

Abstract

Tree models and information on the various characteristics of trees and forests are required for forest management, city models, carbon accounting and the management of assets. In order to get precise characteristics and information, tree modelling must be done at individual tree level as it represents the interaction process between trees. For sustainable forest management, more information is needed, however, the traditional methods of investigating forest parameters such as, tree height, diameter at breast height, crown diameter, stem curve and stem mapping or tree location are complex and labour-intensive. Light detection and ranging (LiDAR) has been proposed as a suitable technique for mapping of forest biomass. LiDAR can be operated in airborne configuration (Airborne laser scanning) or in a terrestrial setup. Terrestrial Laser Scanner measures forests from below canopy and offers a much more detailed description of the individual trees. The aim of this study is to derive the essential tree parameters for estimation of biomass from terrestrial LiDAR data. Tree height, diameter at breast height, crown diameter, stem curve and tree locations were extracted from Terrestrial Laser Scanner point clouds.