Exploring the Potential of Mobile Laser Scanning to Quantify Forest Structural Complexity

Abstract

Today, creating or maintaining forest structural complexity is a management paradigm in many countries due to the positive relationships between structural complexity and several forest functions and services. In this study, we tested whether the box-dimension (Db), a holistic and objective measure to describe the structural complexity of trees or forests, can be used to quantify the structural complexity of 14 European beech (Fagus sylvatica L.) dominated forest plots by means of mobile laser scanning (MLS). The goal of this study was to explore the potential of this approach for quantifying the effect of leaves (summer vs winter) and management (lately unmanaged vs managed) on forest structural complexity. The findings suggest that repeated measurements on the same site and at the same time yielded consistent results if the measuring scheme is standardized. The results also showed that standardized measurement protocols allowed quantifying differences in forest structural complexity due to season. The highest stand structural complexity was found in leaf-on condition during summer, with the complexity being significantly higher than in winter condition. Also, in case of our beech-dominated plots, managed forests were more complex in structure than formerly managed but now unmanaged forests. This study illustrates the potential of MLS for monitoring the changes in forest structural complexity and allows correcting stand structural information for seasonality.

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

“…This is for several reasons: We used 35 scans during both campaigns, distributed in a similar pattern, and both scanners have a similar range (79 m for the Imager, 70 m for the Faro Focus M70). As shown by Neudam et al (2022), repeated laser scanning measurements that are based on similar scan designs result in comparable measures of structural complexity (boxdimension) if the resolution is not too fine. Here, we used a lower cutoff of 10 cm for the calculation of the box-dimension, thereby minimizing its dependency on the scanner's resolution (10,000 points per 360 • for the Z+F Imager in winter 2013, 10,240 points per 360 • for the Faro in winter 2021).…”

What Are We Missing? Occlusion in Laser Scanning Point Clouds and Its Impact on the Detection of Single-Tree Morphologies and Stand Structural Variables

“…It is also conceivable that environmental influences such as slight leaf shaking, which cannot be avoided, even when there is no wind, could additionally amplify the noise. Neudam et al [20] and Guzmán et al [58] also concluded that leaf-bearing trees produce more scattered point clouds than leafless trees. At the stand level, occlusion is particularly evident in the canopy layer of beech trees (Figure 5).…”

“…Additionally, difficulties arise in obtaining detailed tree structures due to canopy occlusion [19]. Mobile laser scanners, on the other hand, are well suited for scanning forest stands and individual trees with a high level of detail, e.g., [20,21].…”

TreeArchTraits: an R package to analyse the architectural traits of trees using TLS data

“…Box-dimension parameter ( Db ) is an integrative measure of tree architecture firstly suggested by Mandelbrot (Mandelbrot 1982). Considering the TLS technology potential for a 3D detailed analysis, Db was recently re-introduced by some authors (Seidel et al 2019; Heidenreich and Seidel 2022; Neudam, Annighöfer, and Seidel 2022). Db is a measure sensitive to both outer shape and internal structure of a tree.…”