scholarly journals Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest

2021 ◽  
Vol 13 (21) ◽  
pp. 4265
Author(s):  
Cesar Alvites ◽  
Giovanni Santopuoli ◽  
Markus Hollaus ◽  
Norbert Pfeifer ◽  
Mauro Maesano ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Mediterranean Forest ◽  
Main Function ◽  
Managed Forests ◽  
Stem Form ◽  
Promising Tool ◽  
Starting Point ◽  
Standing Trees ◽  
Stand Conditions

Timber assortments are some of the most important goods provided by forests worldwide. To quantify the amount and type of timber assortment is strongly important for socio-economic purposes, but also for accurate assessment of the carbon stored in the forest ecosystems, regardless of their main function. Terrestrial laser scanning (TLS) became a promising tool for timber assortment assessment compared to the traditional surveys, allowing reconstructing the tree architecture directly and rapidly. This study aims to introduce an approach for timber assortment assessment using TLS data in a mixed and multi-layered Mediterranean forest. It consists of five steps: (1) pre-processing, (2) timber-leaf discrimination, (3) stem detection, (4) stem reconstruction, and (5) timber assortment assessment. We assume that stem form drives the stem reconstruction, and therefore, it influences the timber assortment assessment. Results reveal that the timber-leaf discrimination accuracy is 0.98 through the Random Forests algorithm. The overall detection rate for all trees is 84.4%, and all trees with a diameter at breast height larger than 0.30 m are correctly identified. Results highlight that the main factors hindering stem reconstruction are the presence of defects outside the trunk, trees poorly covered by points, and the stem form. We expect that the proposed approach is a starting point for valorising the timber resources from unmanaged/managed forests, e.g., abandoned forests. Further studies to calibrate its performance under different forest stand conditions are furtherly required.

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

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 835
Author(s):  
Ville Luoma ◽  
Tuomas Yrttimaa ◽  
Ville Kankare ◽  
Ninni Saarinen ◽  
Jiri Pyörälä ◽  
...  
Keyword(s):  
Tree Growth ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Stem Volume ◽  
Accurate Information ◽  
Stem Form ◽  
Monitoring Period ◽  
Significant Difference

Tree growth is a multidimensional process that is affected by several factors. There is a continuous demand for improved information on tree growth and the ecological traits controlling it. This study aims at providing new approaches to improve ecological understanding of tree growth by the means of terrestrial laser scanning (TLS). Changes in tree stem form and stem volume allocation were investigated during a five-year monitoring period. In total, a selection of attributes from 736 trees from 37 sample plots representing different forest structures were extracted from taper curves derived from two-date TLS point clouds. The results of this study showed the capability of point cloud-based methods in detecting changes in the stem form and volume allocation. In addition, the results showed a significant difference between different forest structures in how relative stem volume and logwood volume increased during the monitoring period. Along with contributing to providing more accurate information for monitoring purposes in general, the findings of this study showed the ability and many possibilities of point cloud-based method to characterize changes in living organisms in particular, which further promote the feasibility of using point clouds as an observation method also in ecological studies.

scholarly journals Terrestrial Laser Scanning and Ground Truth Data for Characterizing Downed Dead Wood

2020 ◽  
Author(s):  
Tuomas Yrttimaa ◽  
Ninni Saarinen ◽  
Ville Luoma ◽  
Topi Tanhuanpää ◽  
Ville Kankare ◽  
...  
Keyword(s):  
Boreal Forests ◽  
Laser Scanning ◽  
Dead Wood ◽  
Terrestrial Laser Scanning ◽  
Ground Truth ◽  
Point Clouds ◽  
Data Set ◽  
Ground Truth Data ◽  
Standing Trees ◽  
Downed Dead Wood

The feasibility of terrestrial laser scanning (TLS) in characterizing standing trees has been frequently investigated, while less effort has been put in quantifying downed dead wood using TLS. To advance dead wood characterization using TLS, we collected TLS point clouds and downed dead wood information from 20 sample plots (32 m x 32 m in size) located in southern Finland. This data set can be used in developing new algorithms for downed dead wood detection and characterization as well as for understanding spatial patterns of downed dead wood in boreal forests.

scholarly journals Poster on Detecting and Characterizing Dead Wood Using Terrestrial Laser Scanning

2020 ◽  
Author(s):  
Tuomas Yrttimaa ◽  
Ninni Saarinen ◽  
Ville Luoma ◽  
Topi Tanhuanpää ◽  
Ville Kankare ◽  
...  
Keyword(s):  
Forest Ecosystem ◽  
Structural Component ◽  
Laser Scanning ◽  
Dead Wood ◽  
Terrestrial Laser Scanning ◽  
Automatic Method ◽  
Forest Inventories ◽  
Standing Trees ◽  
Downed Dead Wood

Dead wood is a key forest structural component for maintaining biodiversity and storing carbon. Despite its important role in a forest ecosystem, quantifying dead wood alongside standing trees has often neglected when investigating the feasibility of terrestrial laser scanning (TLS) in forest inventories. The objective of this study was therefore to develop an automatic method for detecting and characterizing downed dead wood.

scholarly journals A Novel Approach for the Detection of Standing Tree Stems from Plot-Level Terrestrial Laser Scanning Data

2019 ◽  
Vol 11 (2) ◽  
pp. 211 ◽  
Author(s):  
Wuming Zhang ◽  
Peng Wan ◽  
Tiejun Wang ◽  
Shangshu Cai ◽  
Yiming Chen ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Natural Forests ◽  
Individual Tree ◽  
Urban Scenes ◽  
Novel Approach ◽  
Wide Range ◽  
Standing Trees ◽  
The Mean ◽  
Point Cloud Classification

Tree stem detection is a key step toward retrieving detailed stem attributes from terrestrial laser scanning (TLS) data. Various point-based methods have been proposed for the stem point extraction at both individual tree and plot levels. The main limitation of the point-based methods is their high computing demand when dealing with plot-level TLS data. Although segment-based methods can reduce the computational burden and uncertainties of point cloud classification, its application is largely limited to urban scenes due to the complexity of the algorithm, as well as the conditions of natural forests. Here we propose a novel and simple segment-based method for efficient stem detection at the plot level, which is based on the curvature feature of the points and connected component segmentation. We tested our method using a public TLS dataset with six forest plots that were collected for the international TLS benchmarking project in Evo, Finland. Results showed that the mean accuracies of the stem point extraction were comparable to the state-of-art methods (>95%). The accuracies of the stem mappings were also comparable to the methods tested in the international TLS benchmarking project. Additionally, our method was applicable to a wide range of stem forms. In short, the proposed method is accurate and simple; it is a sensible solution for the stem detection of standing trees using TLS data.

scholarly journals Quantification of occlusions influencing the tree stem curve retrieving from single-scan terrestrial laser scanning data

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Peng Wan ◽  
Tiejun Wang ◽  
Wuming Zhang ◽  
Xinlian Liang ◽  
Andrew K. Skidmore ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Basal Area ◽  
Stem Volume ◽  
Accurate Estimation ◽  
Forest Plot ◽  
Curve Estimation ◽  
Standing Trees ◽  
Occlusion Rate

Abstract Background The stem curve of standing trees is an essential parameter for accurate estimation of stem volume. This study aims to directly quantify the occlusions within the single-scan terrestrial laser scanning (TLS) data, evaluate its correlation with the accuracy of the retrieved stem curves, and subsequently, to assess the capacity of single-scan TLS to estimate stem curves. Methods We proposed an index, occlusion rate, to quantify the occlusion level in TLS data. We then analyzed three influencing factors for the occlusion rate: the percentage of basal area near the scanning center, the scanning distance and the source of occlusions. Finally, we evaluated the effects of occlusions on stem curve estimates from single-scan TLS data. Results The results showed that the correlations between the occlusion rate and the stem curve estimation accuracies were strong (r = 0.60–0.83), so was the correlations between the occlusion rate and its influencing factors (r = 0.84–0.99). It also showed that the occlusions from tree stems were the main factor of the low detection rate of stems, while the non-stem components mainly influenced the completeness of the retrieved stem curves. Conclusions Our study demonstrates that the occlusions significantly affect the accuracy of stem curve retrieval from the single-scan TLS data in a typical-size (32 m × 32 m) forest plot. However, the single-scan mode has the capacity to accurately estimate the stem curve in a small forest plot (< 10 m × 10 m) or a plot with a lower occlusion rate, such as less than 35% in our tested datasets. The findings from this study are useful for guiding the practice of retrieving forest parameters using single-scan TLS data.

Analysis of stand density effects on the stem form of Norway spruce trees and volume miscalculation by traditional form factor equations using terrestrial laser scanning (TLS)

2020 ◽  
Vol 50 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Martin Jacobs ◽  
Andreas Rais ◽  
Hans Pretzsch
Keyword(s):  
Form Factor ◽  
Norway Spruce ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Volume Estimation ◽  
Tree Level ◽  
Stem Volume ◽  
Stem Form ◽  
Stem Wood ◽  
Volume Estimates

Tree and stand volume estimates are relevant for forest inventories, forest sales, and carbon stock evaluations. Forest practice commonly uses generalized stem-wood volume functions; however, such generalized approaches neglect the stem form in detail. Hence, trees of a given species with the same diameter at breast height (d1.3) and height (h) are always assumed to have the same form factor and thus the same volume. This case study focused on stem form variation of Norway spruce (Picea abies (L.) Karst.) due to competition effects. Using terrestrial laser scanning (TLS), we measured the stem shape of 868 trees from a long-term spacing and thinning experiment in Germany. The plots covered a broad density range. We analysed the effect of competition and compared the TLS-determined stem volume estimates with those determined conventionally. TLS-based volume estimations showed that the lower the competition was, the lower the tree volume was with a given d1.3 and h. Commonly used functions underestimated the volume stock overall by 4.2%, disregarding any levels. At plot level, underestimation varied from 0.7% to 7.0%. At tree level, the volume was under- and over-estimated by −10% to +10%, respectively. The more precise the examination was, the more suitable the application of TLS was for enhancing volume estimation.

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