Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning

Abstract

Terrestrial laser scanning (TLS) has been adopted as a feasible technique to digitize trees and forest stands, providing accurate information on tree and forest structural attributes. However, there is limited understanding on how a variety of forest structural changes can be quantified using TLS in boreal forest conditions. In this study, we assessed the accuracy and feasibility of TLS in quantifying changes in the structure of boreal forests. We collected TLS data and field reference from 37 sample plots in 2014 (T1) and 2019 (T2). Tree stems typically have planar, vertical, and cylindrical characteristics in a point cloud, and thus we applied surface normal filtering, point cloud clustering, and RANSAC-cylinder filtering to identify these geometries and to characterize trees and forest stands at both time points. The results strengthened the existing knowledge that TLS has the capacity to characterize trees and forest stands in space and showed that TLS could characterize structural changes in time in boreal forest conditions. Root-mean-square-errors (RMSEs) in the estimates for changes in the tree attributes were 0.99–1.22 cm for diameter at breast height (Δdbh), 44.14–55.49 cm2 for basal area (Δg), and 1.91–4.85 m for tree height (Δh). In general, tree attributes were estimated more accurately for Scots pine trees, followed by Norway spruce and broadleaved trees. At the forest stand level, an RMSE of 0.60–1.13 cm was recorded for changes in basal area-weighted mean diameter (ΔDg), 0.81–2.26 m for changes in basal area-weighted mean height (ΔHg), 1.40–2.34 m2/ha for changes in mean basal area (ΔG), and 74–193 n/ha for changes in the number of trees per hectare (ΔTPH). The plot-level accuracy was higher in Scots pine-dominated sample plots than in Norway spruce-dominated and mixed-species sample plots. TLS-derived tree and forest structural attributes at time points T1 and T2 differed significantly from each other (p < 0.05). If there was an increase or decrease in dbh, g, h, height of the crown base, crown ratio, Dg, Hg, or G recorded in the field, a similar outcome was achieved by using TLS. Our results provided new information on the feasibility of TLS for the purposes of forest ecosystem growth monitoring.

Revealing Changes in the Stem Form and Volume Allocation in Diverse Boreal Forests Using Two-Date Terrestrial Laser Scanning

“…Compared to the use of conventional forest mensuration tools, the point cloud-based methods enable detailed characterization of the 3D structure of trees (e.g., [29,30,35,39]) and their change in time [49]. The results of this study demonstrated that the point cloudbased methods can be successfully utilized also in detecting changes in the stem form and volume allocation of trees, and the validity of the findings were confirmed in different forest conditions.…”

“…Performance of the point cloud processing method used in this study to extract attributes characterizing stem form and volume allocation was validated in [49,51]. The conclusion of the studies was that the forest structure is the most important factor affecting the accuracy of the point cloud-based method.…”

“…It enables a non-destructive approach to estimate the stem profile and volume [40][41][42][43][44] which are the key attributes to be monitored when assessing the allocation of tree growth resources. Besides the capability of point cloud-based approaches to characterize trees at one time point (e.g., [31]), the feasibility of using TLS in detecting and quantifying trees' structural changes has been recently investigated [45][46][47][48][49]. These efforts combined have strengthened our understanding of the capabilities of using point clouds in forest monitoring applications even further.…”

Individual Tree Structural Parameter Extraction and Volume Table Creation Based on Near-Field LiDAR Data: A Case Study in a Subtropical Planted Forest

“…Terrestrial laser scanning (TLS)-namely, ground-based LiDAR-also offers a detailed 3D representation of the surroundings of forest structures with millimeter accuracy [10,23,24]. Compared to conventional forest inventory tools, such as the use of hypsometers to measure tree height and tapes to measure tree stem diameters [25], the use of TLS point clouds provides non-destructive estimates of stem curve profiles and characterizes the branching structures of trees, thus further improving the modeling of the individual tree volume. TLS data can be collected with either a single-or a multiple-scan mode [24,26].…”

“…To relieve these occlusion problems, a plot can be scanned with multiple scans at differ-ent positions instead of a single scan in a fixed position. Yrttimaa et al [25] employed a multiple-scan TLS with point cloud cluster and RANSAC-cylinder filtering algorithms to quantify structural changes in boreal forests in Evo in southern Finland. Their results indicated that multiple-scan TLS has the capacity to characterize trees and forest stands in space and showed that TLS technology could estimate structural changes over time in boreal forests.…”