Three-dimensional quantification of tree architecture from mobile laser scanning and geometry analysis

Abstract

Key message Mobile laser scanning and geometrical analysis revealed relationships between tree geometry and seed dispersal mechanism, latitude of origin, as well as growth. Abstract The structure and dynamics of a forest are defined by the architecture and growth patterns of its individual trees. In turn, tree architecture and growth result from the interplay between the genetic building plans and environmental factors. We set out to investigate whether (1) latitudinal adaptations of the crown shape occur due to characteristic solar elevation angles at a species’ origin, (2) architectural differences in trees are related to seed dispersal strategies, and (3) tree architecture relates to tree growth performance. We used mobile laser scanning (MLS) to scan 473 trees and generated three-dimensional data of each tree. Tree architectural complexity was then characterized by fractal analysis using the box-dimension approach along with a topological measure of the top heaviness of a tree. The tree species studied originated from various latitudinal ranges, but were grown in the same environmental settings in the arboretum. We found that trees originating from higher latitudes had significantly less top-heavy geometries than those from lower latitudes. Therefore, to a certain degree, the crown shape of tree species seems to be determined by their original habitat. We also found that tree species with wind-dispersed seeds had a higher structural complexity than those with animal-dispersed seeds (p < 0.001). Furthermore, tree architectural complexity was positively related to the growth performance of the trees (p < 0.001). We conclude that the use of 3D data from MLS in combination with geometrical analysis, including fractal analysis, is a promising tool to investigate tree architecture.

Assessing Forest Vitality and Forest Structure Using 3D Data: A Case Study From the Hainich National Park, Germany

“…Using the single tree point clouds, several structural attributes were computed. The analysis was restricted to beech in this case study because of known structural differences between the different tree species (Seidel, 2018;Seidel et al, 2019a;Dorji et al, 2021), except for the plot-level complexity calculations. The complexity of each tree was determined by using the algorithm of Seidel (2018) in Mathematica (Wolfram Research, Champaign, IL, United States).…”

“…Recent studies showed that the box-dimension relates to a number of individual structural attributes of a tree (Seidel et al, 2019a,c) and that it is also responsive to factors affecting tree growth, such as competition (Seidel, 2018;Dorji et al, 2019;Seidel et al, 2019a) and management (Saarinen et al, 2020;Stiers et al, 2020). It was also shown that the box-dimension is related to the seed dispersal strategy of a tree (Dorji et al, 2021). Unsurprisingly, the amount and distribution of the tree organs, as described by the box-dimension, also relate to tree growth (Seidel, 2018;Dorji et al, 2019).…”

Measuring the Contribution of Leaves to the Structural Complexity of Urban Tree Crowns with Terrestrial Laser Scanning

“…In this study, the mean D b of the leaf-on tree point clouds was greater than 2 across all study tree species (see Table 1), indicating a possible structural difference between trees in rural versus urban areas. However, rural forest trees growing in more open conditions and facing less competition for light (e.g., in forest gaps and in thinned forest stands), also had larger D b values [13,19,106], in some cases exceeding 2 [107]. This suggests a benefit to having an increased D b with more light and fewer neighbors, but at some level the energy benefits from increased photosynthesis would be minimized due to a high level of self-shading [90].…”

Woody Surface Area Measurements with Terrestrial Laser Scanning Relate to the Anatomical and Structural Complexity of Urban Trees

“…Data from mobile laser scanning (MLS) could also be used to study the WSA of trees covering larger spatial scales if occlusion effects in the point clouds are not significant. According to Dorji et al [82], MLS data can be used to study the structural complexity of trees based on fractal analysis and quantified by the D b metric.…”