A Novel Approach to Characterizing Crown Vertical Profile Shapes Using Terrestrial Laser Scanning (TLS)

Abstract

Crown vertical profiles (CVP) play an essential role in stand biomass and forest fire prediction. Traditionally, due to measurement difficulties, CVP models developed based on a small number of individual trees are not convincing. Terrestrial laser scanning (TLS) provides new insights for researching trees’ CVPs. However, there is a limited understanding of the ability to accurately describe CVPs with TLS. In this study, we propose a new approach to automatically extract the crown radius (CR) at different heights and confirm the correctness and effectiveness of the proposed approach with field measurement data from 30 destructively harvested sample trees. We then applied the approach to extract the CR from 283 trees in 6 sample plots to develop a two-level nonlinear mixed-effects (NLME) model for the CVP. The results of the study showed that the average extraction accuracy of the CR when the proposed approach was applied was 90.12%, with differences in the extraction accuracies at different relative depths into the crown (RDINC) ranges. The TLS-based extracted CR strongly correlated with the field-measured CR, with an R2 of 0.93. Compared with the base model, the two-level NLME model has significantly improved the prediction accuracy, with Ra2 increasing by 13.8% and RMSE decreasing by 23.46%. All our research has demonstrated that TLS has great potential for accurately extracting CRs, which would provide a novel way to nondestructively measure the crown structure. Moreover, our research lays the foundation for the future development of CVP models using TLS at a regional scale.

Evaluation of Accuracy in Estimating Diameter at Breast Height Based on the Scanning Conditions of Terrestrial Laser Scanning and Circular Fitting Algorithm

“…This study examined the variations in accuracy depending on the data construction methods centered around DBH. Recently, research using LiDAR systems to estimate various forest-related parameters such as tree height, biomass, forest structure, and 3D modeling was conducted [43][44][45][46][47]. Therefore, future research should not only explore DBH but also how data construction methods influence the estimation of various forest parameters.…”

Comparison of Three Approaches for Estimating Understory Biomass in Yanshan Mountains

“…As an active remote sensing approach, LiDAR (Light Detection and Ranging) allows accurate measurement of distances by transmitting laser pulses and analyzing the returned energy as a function of time [20], and it has emerged as a feasible tool for extracting crucial forest structure parameters [21]. Over the past two decades, LiDAR developed rapidly with multiple platforms, including satellite platforms (ICESat and GEDI, and spaceborne laser scanning, SLS), airborne platforms including manned aircraft and drones (airborne laser scanning, ALS), and ground platforms (terrestrial laser scanning, TLS), providing technical support for monitoring a wide range of forest dynamics changes [22]. Airborne laser scanning (ALS) is well-established in forestry research for characterizing three-dimensional variation in a tree canopy structure at plot or stand level [23] and has proven to be a highly accurate tool for assessing tree volume [24] and biomass [25] in forested stands.…”

Enhancing Tree Species Identification in Forestry and Urban Forests through Light Detection and Ranging Point Cloud Structural Features and Machine Learning

“…In forestry, laser scanning techniques, such as Airborne Laser Scanning (ALS), Terrestrial Laser Scanning (TLS), including mobile LiDAR systems such as handheld systems, and Mobile Laser Scanning (MLS), have been widely investigated for applications in forest inventory [2,3]. These techniques provide efficient means for acquiring detailed three-dimensional (3D) data from vegetation, enabling the extraction of tree and forest parameters such as tree height, crown dimensions, and biomass [4][5][6][7][8][9][10][11][12][13][14][15][16].…”