Abstract
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.
Highlights
Much forest ecosystem research is based on spatially oriented data
To better demonstrate the workflow of 3D Forest and its outputs, we present an example of terrestrial laser scanning (TLS) data processing using a small subplot (20m x 40m) of a larger study site known as the Velka Ples Forest Dynamics Plot (VPFDP) (Fig 1)
The testing was performed on artificial dataset designed as a pooled sample of simulated diameters at breast height (DBH) rings composed of points representing mixture of different levels of all tested factors
Summary
Much forest ecosystem research is based on spatially oriented data. Research on forest dynamics commonly makes use of large census plots, where the position and size of every tree individual are measured and recorded [1]. These observations are fundamentally two-dimensional, trees being represented as points with X, Y coordinates of the tree base and other parameters (e.g. species, diameter in breast height—DBH, height) only recorded in a database. Tree regeneration, tree growth and competition (especially aboveground competition for light) all take.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
