Terrestrial Laser Scanning for Non-Destructive Estimation of Aboveground Biomass in Short-Rotation Poplar Coppices

Abstract

Poplar plantations in high-density and short-rotation coppices (SRC) are a suitable way for the fast production of wood that can be transformed into bioproducts or bioenergy. Optimal management of these coppices requires accurate assessment of the total standing biomass. However, traditional field inventory is a challenging task, given the existence of multiple shoots, the difficulty of identifying terminal shoots, and the extreme high density. As an alternative, in this work, we propose to develop individual stool and plot biomass models using metrics derived from terrestrial laser scanning (TLS) as predictors. To this aim, we used data from a SRC poplar plantation, including nine plots and 154 individual stools. Every plot was scanned from different positions, and individual stools were felled, weighed, and dried to compute aboveground biomass (AGB). Individual stools were segmented from the cloud point, and different TLS metrics at stool and plot level were derived following processes of bounding box, slicing, and voxelization. These metrics were then used, either alone or combined with field-measured metrics, to fit biomass models. Our results indicate that at individual-stool level, the biomass models combining TLS metrics and easy to measure in field metrics (stool diameter) perform similarly to the traditional allometric models based on field inventories, while at plot scales, TLS-derived models show superiority over traditional models. Our proposed methodology permits accurate and non-destructive estimates of the biomass fixed in SRC plantations.

Comparison of Three Approaches for Estimating Understory Biomass in Yanshan Mountains

“…However, other studies may hold contradictory results, implying that the error magnitudes for the investigated point cloud metrics and plant metrics are the lowest with scaled voxels or with the smallest fixed-sized voxels (2 cm) [64]. In contrast, Menéndez et al [44] denoted that a large voxel grid of 25 cm (low number of voxels) is more efficient than finer resolutions of voxelization. Determining the optimal voxel size based on features of PCD and mathematical approaches should be a focus of concern.…”

“…The specification of voxel size in the process of voxelization has proven to have a significant impact on the estimation accuracy in previous studies, and optimal voxel size needs to be determined [37,38]. Among vegetation complexity, subcanopy structure, and clumping effect, several factors are proposed to be influencing the value of optimal voxel size [39,40], and measures have been taken to tackle this problem, including limiting occlusion by conducting multiple scans and introducing correction factors in different voxel sizes [41], yet the specification of optimal voxel size still remains contradictory in different studies [42][43][44]. Here, we applied a non-voxel-based approach as an alternative and conducted comparisons to evaluate its performance for understory biomass estimation.…”

Multisensor and Multiscale Data Integration Method of TLS and GPR for Three-Dimensional Detailed Virtual Reconstruction

“…In contrast with traditional methods, TLS is generally used to acquire detailed spatial information for reconstructing 3D realistic models because it offers high-resolution dense point clouds with highly automated and non-contacted operation in a short time, such as in the geosciences [1][2][3][4], architecture [5][6][7], archaeology [8,9], agriculture and forestry [10], engineering, and construction industries [11,12]. This technique generalizes dense point clouds with the position information, reflection intensity, and color information that is used for the visualization and quantitative analysis of 3D realistic models.…”