Terrestrial laser scanning for measuring the solid wood volume, including branches, of adult standing trees in the forest environment

2012 ◽  
Vol 89 ◽  
pp. 86-93 ◽  
Author(s):  
Mathieu Dassot ◽  
Aurélie Colin ◽  
Philippe Santenoise ◽  
Meriem Fournier ◽  
Thiéry Constant
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Solid Wood ◽  
Forest Environment ◽  
Wood Volume ◽  
Standing Trees

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 Does Tree Architectural Complexity Influence the Accuracy of Wood Volume Estimates of Single Young Trees by Terrestrial Laser Scanning?

Forests ◽  
2015 ◽  
Vol 6 (12) ◽  
pp. 3847-3867 ◽  
Author(s):  
Carsten Hess ◽  
Anne Bienert ◽  
Werner Härdtle ◽  
Goddert von Oheimb
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Wood Volume ◽  
Volume Estimates

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.

scholarly journals Detecting and characterizing downed dead wood using terrestrial laser scanning

2020 ◽  
Author(s):  
Tuomas Yrttimaa ◽  
Ninni Saarinen ◽  
Ville Luoma ◽  
Topi Tanhuanpää ◽  
Ville Kankare ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Method Development ◽  
Dead Wood ◽  
Terrestrial Laser Scanning ◽  
Detection Accuracy ◽  
Visual Interpretation ◽  
Wood Volume ◽  
Downed Dead Wood ◽  
Forest Conditions

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 with a diameter exceeding 5 cm using multi-scan TLS data. The developed four-stage algorithm included 1) RANSAC-cylinder filtering, 2) point cloud rasterization, 3) raster image segmentation, and 4) dead wood trunk positioning. For each detected trunk, geometry-related quality attributes such as dimensions and volume were automatically determined from the point cloud. For method development and validation, reference data were collected from 20 sample plots representing diverse southern boreal forest conditions. Using the developed method, the downed dead wood trunks were detected with an overall completeness of 33% and correctness of 76%. Up to 92% of the downed dead wood volume were detected at plot level with mean value of 68%. We were able to improve the detection accuracy of individual trunks with visual interpretation of the point cloud, in which case the overall completeness was increased to 72% with mean proportion of detected dead wood volume of 83%. Downed dead wood volume was automatically estimated with an RMSE of 15.0 m3/ha (59.3%), which was reduced to 6,4 m3/ha (25.3%) as visual interpretation was utilized to aid the trunk detection. The reliability of TLS-based dead wood mapping was found to increase as the dimensions of dead wood trunks increased. Dense vegetation caused occlusion and reduced the trunk detection accuracy. Therefore, when collecting the data, attention must be paid to the point cloud quality. Nevertheless, the results of this study strengthen the feasibility of TLS-based approaches in mapping biodiversity indicators by demonstrating an improved performance in quantifying ecologically most valuable downed dead wood in diverse forest conditions.

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 Above Ground Biomass References for Urban Trees from Terrestrial Laser Scanning Data

2021 ◽  
Author(s):  
Daniel Kükenbrink ◽  
Oliver Gardi ◽  
Felix Morsdorf ◽  
Esther Thürig ◽  
Andreas Schellenberger ◽  
...  
Keyword(s):  
Carbon Storage ◽  
Forest Inventory ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Tree Structure ◽  
Urban Trees ◽  
Forest Trees ◽  
Above Ground Biomass ◽  
Wood Volume ◽  
Volume Estimates

&lt;p&gt;Trees supply a multitude of ecosystem services (e.g. carbon storage, suppression of air pollution, oxygen, shade, recreation etc.) not only in forested areas but also in urban landscapes. Many of these services are positively correlated with tree size and structure. The assessment of carbon storage potential via the quantification of above ground biomass (AGB) is of special importance. However, quantification of AGB is difficult and applied allometries are often based on forest trees, which are subject to very different growing conditions, competition and form compared to urban trees. In this contribution, we highlight the potential of terrestrial laser scanning (TLS) techniques to extract high detailed information on tree structure and AGB with a focus on urban trees.&lt;/p&gt;&lt;p&gt;A total of 55 urban trees distributed over eight cities in Switzerland were measured using TLS and traditional forest inventory techniques before they were felled and weighted. Tree structure, volumes and AGB from the TLS point clouds were extracted using Quantitative Structure Modelling (QSM). TLS derived AGB estimates were compared to allometric estimates dependent on diameter at breast height only. The allometric models were established within the Swiss National Forest Inventory and are therefore optimised for forest trees.&lt;/p&gt;&lt;p&gt;TLS derived AGB estimates showed good performance when compared to destructively harvested references with an R&lt;sup&gt;2&lt;/sup&gt; of 0.954 (RMSE = 556 kg), compared to an R&lt;sup&gt;2&lt;/sup&gt; of 0.837 (RMSE = 1159 kg) for allometrically derived AGB estimates. A correlation analysis showed that different TLS derived wood volume estimates as well as trunk diameters and tree crown metrics show high correlation in describing total wood AGB.&lt;/p&gt;&lt;p&gt;The presented results show that TLS based wood volume estimates show high potential to estimate tree AGB independent of tree species, size and form. This allows us to retrieve highly accurate, non-destructive AGB estimates that could be used to establish new allometric equations without the need of extensive destructive harvest.&lt;/p&gt;

scholarly journals Filtering Stems and Branches from Terrestrial Laser Scanning Point Clouds Using Deep 3-D Fully Convolutional Networks

2018 ◽  
Vol 10 (8) ◽  
pp. 1215 ◽  
Author(s):  
Zhouxin Xi ◽  
Chris Hopkinson ◽  
Laura Chasmer
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Visual Assessment ◽  
Common Species ◽  
Branch Points ◽  
Forest Environment ◽  
Individual Tree ◽  
Convolutional Networks ◽  
Fully Convolutional Networks

Terrestrial laser scanning (TLS) can produce precise and detailed point clouds of forest environment, thus enabling quantitative structure modeling (QSM) for accurate tree morphology and wood volume allocation. Applying QSM to plot-scale wood delineation is highly dependent on wood visibility from forest scans. A common problem is to filter wood point from noisy leafy points in the crowns and understory. This study proposed a deep 3-D fully convolution network (FCN) to filter both stem and branch points from complex plot scans. To train the 3-D FCN, reference stem and branch points were delineated semi-automatically for 14 sampled areas and three common species. Among seven testing areas, agreements between reference and model prediction, measured by intersection over union (IoU) and overall accuracy (OA), were 0.89 (stem IoU), 0.54 (branch IoU), 0.79 (mean IoU), and 0.94 (OA). Wood filtering results were further incorporated to a plot-scale QSM to extract individual tree forms, isolated wood, and understory wood from three plot scans with visual assessment. The wood filtering experiment provides evidence that deep learning is a powerful tool in 3-D point cloud processing and parsing.

Sign in / Sign up

Export Citation Format

Share Document