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

<p>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.</p><p>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.</p><p>TLS derived AGB estimates showed good performance when compared to destructively harvested references with an R<sup>2</sup> of 0.954 (RMSE = 556 kg), compared to an R<sup>2</sup> 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.</p><p>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.</p>

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 Measuring the Contribution of Leaves to the Structural Complexity of Urban Tree Crowns with Terrestrial Laser Scanning

2021 ◽  
Vol 13 (14) ◽  
pp. 2773
Author(s):  
Georgios Arseniou ◽  
David W. MacFarlane ◽  
Dominik Seidel
Keyword(s):  
Laser Scanning ◽  
Structural Complexity ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Urban Trees ◽  
Box Dimension ◽  
State University ◽  
Leaf Removal ◽  
Quercus Macrocarpa ◽  
Methodological Considerations

Trees have a fractal-like branching architecture that determines their structural complexity. We used terrestrial laser scanning technology to study the role of foliage in the structural complexity of urban trees. Forty-five trees of three deciduous species, Gleditsia triacanthos, Quercus macrocarpa, Metasequoia glyptostroboides, were sampled on the Michigan State University campus. We studied their structural complexity by calculating the box-dimension (Db) metric from point clouds generated for the trees using terrestrial laser scanning, during the leaf-on and -off conditions. Furthermore, we artificially defoliated the leaf-on point clouds by applying an algorithm that separates the foliage from the woody material of the trees, and then recalculated the Db metric. The Db of the leaf-on tree point clouds was significantly greater than the Db of the leaf-off point clouds across all species. Additionally, the leaf removal algorithm introduced bias to the estimation of the leaf-removed Db of the G. triacanthos and M. glyptostroboides trees. The index capturing the contribution of leaves to the structural complexity of the study trees (the ratio of the Db of the leaf-on point clouds divided by the Db of the leaf-off point clouds minus one), was negatively correlated with branch surface area and different metrics of the length of paths through the branch network of the trees, indicating that the contribution of leaves decreases as branch network complexity increases. Underestimation of the Db of the G. triacanthos trees, after the artificial leaf removal, was related to maximum branch order. These results enhance our understanding of tree structural complexity by disentangling the contribution of leaves from that of the woody structures. The study also highlighted important methodological considerations for studying tree structure, with and without leaves, from laser-derived point clouds.

Single tree species classification from Terrestrial Laser Scanning data for forest inventory

2013 ◽  
Vol 34 (16) ◽  
pp. 2144-2150 ◽  
Author(s):  
Ahlem Othmani ◽  
Lew F.C. Lew Yan Voon ◽  
Christophe Stolz ◽  
Alexandre Piboule
Keyword(s):  
Tree Species ◽  
Forest Inventory ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Species Classification ◽  
Single Tree ◽  
Tree Species Classification

scholarly journals Towards Tree Green Crown Volume: A Methodological Approach Using Terrestrial Laser Scanning

2020 ◽  
Vol 12 (11) ◽  
pp. 1841 ◽  
Author(s):  
Zihui Zhu ◽  
Christoph Kleinn ◽  
Nils Nölke
Keyword(s):  
Laser Scanning ◽  
Methodological Approach ◽  
Terrestrial Laser Scanning ◽  
Urban Trees ◽  
Volume Index ◽  
Convex Hulls ◽  
Tree Crown ◽  
Crown Volume ◽  
Matter Production

Crown volume is a tree attribute relevant in a number of contexts, including photosynthesis and matter production, storm resistance, shadowing of lower layers, habitat for various taxa. While commonly the total crown volume is being determined, for example by wrapping a convex hull around the crown, we present here a methodological approach towards assessing the tree green crown volume (TGCVol), the crown volume with a high density of foliage, which we derive by terrestrial laser scanning in a case study of solitary urban trees. Using the RGB information, we removed the hits on stem and branches within the tree crown and used the remaining leaf hits to determine TGCVol from k-means clustering and convex hulls for the resulting green 3D clusters. We derived a tree green crown volume index (TGCVI) relating the green crown volume to the total crown volume. This TGCVI is a measure of how much a crown is “filled with green” and scale-dependent (a function of specifications of the k-means clustering). Our study is a step towards a standardized assessment of tree green crown volume. We do also address a number of remaining methodological challenges.

scholarly journals Tree structure vs. height from terrestrial laser scanning and quantitative structure models

Silva Fennica ◽  
2014 ◽  
Vol 48 (2) ◽  
Author(s):  
Anssi Krooks ◽  
Sanna Kaasalainen ◽  
Ville Kankare ◽  
Marianna Joensuu ◽  
Pasi Raumonen ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Tree Structure ◽  
Quantitative Structure

scholarly journals A Single-Tree Processing Framework Using Terrestrial Laser Scanning Data for Detecting Forest Regeneration

2018 ◽  
Vol 11 (1) ◽  
pp. 60 ◽  
Author(s):  
Johannes Heinzel ◽  
Christian Ginzler
Keyword(s):  
Forest Inventory ◽  
Forest Regeneration ◽  
Laser Scanning ◽  
Survey Design ◽  
Terrestrial Laser Scanning ◽  
Remote Sensing Data ◽  
Ground Cover ◽  
Absolute Error ◽  
Special Importance ◽  
Individual Trees

Direct assessment of forest regeneration from remote sensing data is a previously little-explored problem. This is due to several factors which complicate object detection of small trees in the understory. Most existing studies are based on airborne laser scanning (ALS) data, which often has insufficient point densities in the understory forest layers. The present study uses plot-based terrestrial laser scanning (TLS) and the survey design was similar to traditional forest inventory practices. Furthermore, a framework of methods was developed to solve the difficulties of detecting understory trees for quantifying regeneration in temperate montane forest. Regeneration is of special importance in our montane study area, since large parts are declared as protection forest against alpine natural hazards. Close to nature forest structures were tackled by separating 3D tree stem detection from overall tree segmentation. In support, techniques from 3D mathematical morphology, Hough transformation and state-of-the-art machine learning were applied. The methodical framework consisted of four major steps. These were the extraction of the tree stems, the estimation of the stem diameters at breast height (DBH), the image segmentation into individual trees and finally, the separation of two groups of regeneration. All methods were fully automated and utilized volumetric 3D image information which was derived from the original point cloud. The total amount of regeneration was split into established regeneration, consisting of trees with a height > 130 cm in combination with a DBH < 12 cm and unestablished regeneration, consisting of trees with a height < 130 cm. Validation was carried out against field-based expert estimates of percentage ground cover, differentiating seven classes that were similar to those used by forest inventory. The mean absolute error (MAE) of our method for established regeneration was 1.11 classes and for unestablished regeneration only 0.27 classes. Considering the metrical distances between the class centres, the MAE amounted 8.08% for established regeneration and 2.23% for unestablished regeneration.

scholarly journals Suitability of Airborne and Terrestrial Laser Scanning for Mapping Tree Crop Structural Metrics for Improved Orchard Management

2020 ◽  
Vol 12 (10) ◽  
pp. 1647 ◽  
Author(s):  
Dan Wu ◽  
Kasper Johansen ◽  
Stuart Phinn ◽  
Andrew Robson
Keyword(s):  
Leaf Area ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Tree Structure ◽  
Crown Height ◽  
Crown Area ◽  
Vertical Leaf ◽  
Fractional Cover ◽  
Crown Volume ◽  
Crown Structure

Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS) systems are useful tools for deriving horticultural tree structure estimates. However, there are limited studies to guide growers and agronomists on different applications of the two technologies for horticultural tree crops, despite the importance of measuring tree structure for pruning practices, yield forecasting, tree condition assessment, irrigation and fertilization optimization. Here, we evaluated ALS data against near coincident TLS data in avocado, macadamia and mango orchards to demonstrate and assess their accuracies and potential application for mapping crown area, fractional cover, maximum crown height, and crown volume. ALS and TLS measurements were similar for crown area, fractional cover and maximum crown height (coefficient of determination (R2) ≥ 0.94, relative root mean square error (rRMSE) ≤ 4.47%). Due to the limited ability of ALS data to measure lower branches and within crown structure, crown volume estimates from ALS and TLS data were less correlated (R2 = 0.81, rRMSE = 42.66%) with the ALS data found to consistently underestimate crown volume. To illustrate the effects of different spatial resolution, capacity and coverage of ALS and TLS data, we also calculated leaf area, leaf area density and vertical leaf area profile from the TLS data, while canopy height, tree row dimensions and tree counts) at the orchard level were calculated from ALS data. Our results showed that ALS data have the ability to accurately measure horticultural crown structural parameters, which mainly rely on top of crown information, and measurements of hedgerow width, length and tree counts at the orchard scale is also achievable. While the use of TLS data to map crown structure can only cover a limited number of trees, the assessment of all crown strata is achievable, allowing measurements of crown volume, leaf area density and vertical leaf area profile to be derived for individual trees. This study provides information for growers and horticultural industries on the capacities and achievable mapping accuracies of standard ALS data for calculating crown structural attributes of horticultural tree crops.

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