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

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.

Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach

“…Direct use of raw simpletree QSMs to estimate tree volume highlighted the (expected) difficulties of the cylinder‐based, automated approach to describe large tree stumps and crowns, requiring manual edits and the separate modelling of buttressed parts with a mesh model (Cushman, Muller‐Landau, Condit, & Hubbell, ; Nogueira, Fearnside, Nelson, Barbosa, & Keizer, ; Nölke et al., ; Olagoke et al., ; Picard & Saint‐andré, ). While reconstruction algorithms are rapidly evolving (Raumonen et al., , ; Stovall et al., ; Tao et al., ; Trochta et al., ) in the hope to upscale studies to entire forest stands, the semi‐automated procedure proposed here is already fully operational even in very dense tropical forests at the leaf‐on stage, allowing to improve validation R ² for tree volumes from .75 to .98, and to reduce from 29% to 12%. It offers a real alternative to destructive approaches, without significant loss of precision, and with the very significant added value that other measurements will be feasible on the sampled trees at a later stage, including for multi‐temporal comparisons, allowing the precise monitoring of tree growth patterns, crown plasticity, interactions with neighbours, etc.…”

“…As long as harvesting and weighing complete forest plots remain impractical (but see Clark & Kellner, ), and no other method allows to directly measure AGB at the plot level in dense tropical forests (Raumonen et al., , ; Tao, Wu, et al., ; Trochta, Kruček, Vrška, & Kraâl, ), the estimation of forests plot AGB and the associated error largely depend on tree‐level AGB prediction models (Chave et al., ; Picard, Boyemba Bosela, & Rossi, ). The latter are calibrated on destructive datasets and combine easily as measurable tree descriptors—typically diameter at breast height (DBH), tree height (H) and wood density (WD)—to derive tree AGB estimate.…”

LeWoS: A universal leaf‐wood classification method to facilitate the 3D modelling of large tropical trees using terrestrial LiDAR

“…The acquired high‐density point clouds allow very precise measurements of tree structures in a non‐destructive way. These measurements include forest inventory (Liang et al, ) leaf angle distribution (Vicari, Pisek, & Disney, ), structural parameters (Trochta, Krůček, Vrška, & Král, ; Wang, Hollaus, Puttonen, & Pfeifer, ), above‐ground volume and biomass (AGB) (Calders et al, ; Gonzalez de Tanago et al, ; Momo Takoudjou et al, ). Moreover, allometric equations can be non‐destructively performed with data derived from TLS (Lau et al, ; Momo Takoudjou et al, ).…”

High-Resolution Urban Greenery Mapping for Micro-Climate Modelling Based on 3d City Models

“…The point cloud representing just the trees (Fig. 5B) was then segmented into point clouds of individual trees by the 3D Forest software (Trochta et al, 2017). The result of segmentation was exported in the PLY format and meshed in the GeomagicWrap 2015 software to create 3D tree models with the Wrap tool (Fig.…”