Diameter at Breast Height (DBH) Estimation and Stem Cross-Section Shape Analysis of Eucalyptus Trees Using LiDAR Data after Noisy Removal

Abstract

LiDAR data offer new possibilities for obtaining geometric parameters of forest areas, such as diameter at breast height (DBH), basal area, height, volume, biomass, and carbon stock. Terrestrial Laser Scanning (TLS) is highly accurate and can be used to obtain the shape of a tree stem. This paper proposes a method for automatically eliminating noisy points, classifying the cross-section shape of eucalyptus trees into circular and non-circular, and identifying insufficient sampling. In addition, an analysis is made of the relationship between the shape of the cross-section and the circumference adjustment, which is traditionally used to estimate DBH. Based on the proposed method, the DBH estimated from TLS data showed a Root Mean Square Error (RMSE) of 0.7 cm for trees with a cross-section considered circular and an RMSE of 3.7 cm for cross-sections considered non-circular. The results showed that the shape of the cross-section is relevant for estimating biometric parameters such as DBH and that additional evaluations are needed for precise applications, such as volume estimation for trees with non-circular cross-sections.