3D Forest: An application for descriptions of three-dimensional forest structures using terrestrial LiDAR

• Published in: PloS one Vol. 12; no. 5; p. e0176871
• Main Authors: Trochta, Jan, Krůček, Martin, Vrška, Tomáš, Král, Kamil
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 04.05.2017; Public Library of Science (PLoS)
• Subjects: Algorithms; Automation; Biology and Life Sciences; Biomass; Computer and Information Sciences; Data processing; Ecology; Ecology and Environmental Sciences; Engineering and Technology; Forests; Hough transformation; Imaging, Three-Dimensional; Lasers; Lidar; Optical radar; Physical Sciences; Remote sensing; Research and Analysis Methods; Scanners; Segmentation; Terrestrial environments; Three-dimensional imaging; Trees
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0176871

Terrestrial laser scanning is a powerful technology for capturing the three-dimensional structure of forests with a high level of detail and accuracy. Over the last decade, many algorithms have been developed to extract various tree parameters from terrestrial laser scanning data. Here we present 3D Forest, an open-source non-platform-specific software application with an easy-to-use graphical user interface with the compilation of algorithms focused on the forest environment and extraction of tree parameters. The current version (0.42) extracts important parameters of forest structure from the terrestrial laser scanning data, such as stem positions (X, Y, Z), tree heights, diameters at breast height (DBH), as well as more advanced parameters such as tree planar projections, stem profiles or detailed crown parameters including convex and concave crown surface and volume. Moreover, 3D Forest provides quantitative measures of between-crown interactions and their real arrangement in 3D space. 3D Forest also includes an original algorithm of automatic tree segmentation and crown segmentation. Comparison with field data measurements showed no significant difference in measuring DBH or tree height using 3D Forest, although for DBH only the Randomized Hough Transform algorithm proved to be sufficiently resistant to noise and provided results comparable to traditional field measurements.