Exploring the Variability of Tropical Savanna Tree Structural Allometry with Terrestrial Laser Scanning

Individual tree carbon stock estimates typically rely on allometric scaling relationships established between field-measured stem diameter (DBH) and destructively harvested biomass. The use of DBH-based allometric equations to estimate the carbon stored over larger areas therefore, assumes that tree architecture, including branching and crown structures, are consistent for a given DBH, and that minor variations cancel out at the plot scale. We aimed to explore the degree of structural variation present at the individual tree level across a range of size-classes. We used terrestrial laser scanning (TLS) to measure the 3D structure of each tree in a 1 ha savanna plot, with coincident field-inventory. We found that stem reconstructions from TLS captured both the spatial distribution pattern and the DBH of individual trees with high confidence when compared with manual measurements (R2 = 0.98, RMSE = 0.0102 m). Our exploration of the relationship between DBH, crown size and tree height revealed significant variability in savanna tree crown structure (measured as crown area). These findings question the reliability of DBH-based allometric equations for adequately representing diversity in tree architecture, and therefore carbon storage, in tropical savannas. However, adoption of TLS outside environmental research has been slow due to considerable capital cost and monitoring programs often continue to rely on sub-plot monitoring and traditional allometric equations. A central aspect of our study explores the utility of a lower-cost TLS system not generally used for vegetation surveys. We discuss the potential benefits of alternative TLS-based approaches, such as explicit modelling of tree structure or voxel-based analyses, to capture the diverse 3D structures of savanna trees. Our research highlights structural heterogeneity as a source of uncertainty in savanna tree carbon estimates and demonstrates the potential for greater inclusion of cost-effective TLS technology in national monitoring programs.

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Individual tree extraction from terrestrial laser scanning data via graph pathing

Forest Ecosystems ◽

10.1186/s40663-021-00340-w ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Di Wang ◽

Xinlian Liang ◽

Gislain II Mofack ◽

Olivier Martin-Ducup

Keyword(s):

Laser Scanning ◽

Terrestrial Laser Scanning ◽

Point Clouds ◽

Tree Level ◽

Forest Types ◽

Computationally Efficient ◽

Large Area ◽

Individual Tree ◽

Single Crown ◽

Tree Extraction

Abstract Background Individual tree extraction from terrestrial laser scanning (TLS) data is a prerequisite for tree-scale estimations of forest biophysical properties. This task currently is undertaken through laborious and time-consuming manual assistance and quality control. This study presents a new fully automatic approach to extract single trees from large-area TLS data. This data-driven method operates exclusively on a point cloud graph by path finding, which makes our method computationally efficient and universally applicable to data from various forest types. Results We demonstrated the proposed method on two openly available datasets. First, we achieved state-of-the-art performance on locating single trees on a benchmark dataset by significantly improving the mean accuracy by over 10% especially for difficult forest plots. Second, we successfully extracted 270 trees from one hectare temperate forest. Quantitative validation resulted in a mean Intersection over Union (mIoU) of 0.82 for single crown segmentation, which further led to a relative root mean square error (RMSE%) of 21.2% and 23.5% for crown area and tree volume estimations, respectively. Conclusions Our method allows automated access to individual tree level information from TLS point clouds. The proposed method is free from restricted assumptions of forest types. It is also computationally efficient with an average processing time of several seconds for one million points. It is expected and hoped that our method would contribute to TLS-enabled wide-area forest qualifications, ranging from stand volume and carbon stocks modelling to derivation of tree functional traits as part of the global ecosystem understanding.

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Reliable Estimates of Merchantable Timber Volume from Terrestrial Laser Scanning

Remote Sensing ◽

10.3390/rs13183610 ◽

2021 ◽

Vol 13 (18) ◽

pp. 3610

Author(s):

Dimitrios Panagiotidis ◽

Azadeh Abdollahnejad

Keyword(s):

Laser Scanning ◽

Accurate Determination ◽

Laser Scanner ◽

Terrestrial Laser Scanning ◽

Tree Height ◽

Tree Level ◽

Consensus Method ◽

Field Methods ◽

Forest Inventories ◽

Random Sampling Consensus

Simple and accurate determination of merchantable tree height is needed for accurate estimations of merchantable volume. Conventional field methods of forest inventory can lead to biased estimates of tree height and diameter, especially in complex forest structures. Terrestrial laser scanner (TLS) data can be used to determine merchantable height and diameter at different heights with high accuracy and detail. This study focuses on the use of the random sampling consensus method (RANSAC) for generating the length and diameter of logs to estimate merchantable volume at the tree level using Huber’s formula. For this study, we used two plots; plot A contained deciduous trees and plot B consisted of conifers. Our results demonstrated that the TLS-based outputs for stem modelling using the RANSAC method performed very well with low bias (0.02 for deciduous and 0.01 for conifers) and a high degree of accuracy (97.73% for deciduous and 96.14% for conifers). We also found a high correlation between the proposed method and log length (−0.814 for plot A and −0.698 for plot B), which is an important finding because this information can be used to determine the optimum log properties required for analyzing stem curvature changes at different heights. Furthermore, the results of this study provide insight into the applicability and ergonomics during data collection from forest inventories solely from terrestrial laser scanning, thus reducing the need for field reference data.

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Deriving Individual-Tree Biomass from Effective Crown Data Generated by Terrestrial Laser Scanning

Remote Sensing ◽

10.3390/rs11232793 ◽

2019 ◽

Vol 11 (23) ◽

pp. 2793

Author(s):

Yujie Zheng ◽

Weiwei Jia ◽

Qiang Wang ◽

Xu Huang

Keyword(s):

Laser Scanning ◽

Three Dimensional ◽

Terrestrial Laser Scanning ◽

Tree Height ◽

Biomass Estimation ◽

Tree Biomass ◽

Crown Height ◽

Individual Tree ◽

Cloud Data ◽

Biomass Equations

Biomass reflects the state of forest management and is critical for assessing forest benefits and carbon storage. The effective crown is the region above the lower limit of the forest crown that includes the maximum vertical distribution density of branches and leaves; this component plays an important role in tree growth. Adding the effective crown to biomass equations can enhance the accuracy of the derived biomass. Six sample plots in a larch plantation (ranging in area from 0.06 ha to 0.12 ha and in number of trees from 63 to 96) at the Mengjiagang forest farm in Huanan County, Jiamusi City, Heilongjiang Province, China, were analyzed in this study. Terrestrial laser scanning (TLS) was used to obtain three-dimensional point cloud data on the trees, from which crown parameters at different heights were extracted. These parameters were used to determine the position of the effective crown. Moreover, effective crown parameters were added to biomass equations with tree height as the sole variable to improve the accuracy of the derived individual-tree biomass estimates. The results showed that the minimum crown contact height was very similar to the effective crown height, and an increase in model accuracy was apparent (with R a 2 increasing from 0.846 to 0.910 and root-mean-square error (RMSE) decreasing from 0.372 kg to 0.286 kg). The optimal model for deriving biomass included tree height, crown length from minimum contact height, crown height from minimum contact height, and crown surface area from minimum contact height. The novelty of the article is that it improves the fit of individual-tree biomass models by adding crown-related variables and investigates how the accuracy of biomass estimation can be enhanced by using remote sensing methods without obtaining diameter at breast height.

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THE EFFECT OF WIND ON TREE STEM PARAMETER ESTIMATION USING TERRESTRIAL LASER SCANNING

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iii-8-117-2016 ◽

2016 ◽

Vol III-8 ◽

pp. 117-122 ◽

Cited By ~ 2

Author(s):

M. T. Vaaja ◽

J.-P. Virtanen ◽

M. Kurkela ◽

V. Lehtola ◽

J. Hyyppä ◽

...

Keyword(s):

Parameter Estimation ◽

Laser Scanning ◽

Terrestrial Laser Scanning ◽

Tree Height ◽

Individual Tree ◽

Finnish Meteorological Institute ◽

Wind Speeds ◽

Forest Inventories ◽

Level Data ◽

Tree Stem

The 3D measurement technique of terrestrial laser scanning (TLS) in forest inventories has shown great potential for improving the accuracy and efficiency of both individual tree and plot level data collection. However, the effect of wind has been poorly estimated in the error analysis of TLS tree measurements although it causes varying deformations to the trees. In this paper, we evaluated the effect of wind on tree stem parameter estimation at different heights using TLS. The data consists of one measured Scots pine captured from three different scanning directions with two different scanning resolutions, 6.3 mm and 3.1 mm at 10 m. The measurements were conducted under two different wind speeds, approximately 3 m/s and 9 m/s, as recorded by a nearby weather station of the Finnish Meteorological Institute. Our results show that the wind may cause both the underestimation and overestimation of tree diameter when using TLS. The duration of the scanning is found to have an impact for the measured shape of the tree stem under 9 m/s wind conditions. The results also indicate that a 9 m/s wind does not have a significant effect on the stem parameters of the lower part of a tree (<28% of the tree height). However, as the results imply, the wind conditions should be taken into account more comprehensively in analysis of TLS tree measurements, especially if multiple scans from different positions are registered together. In addition, TLS could potentially be applied to indirectly measure wind speed by observing the tree stem movement.

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Influence of Site-Specific Conditions on Estimation of Forest above Ground Biomass from Airborne Laser Scanning

Forests ◽

10.3390/f11030268 ◽

2020 ◽

Vol 11 (3) ◽

pp. 268

Author(s):

Jan Novotný ◽

Barbora Navrátilová ◽

Růžena Janoutová ◽

Filip Oulehle ◽

Lucie Homolová

Keyword(s):

Laser Scanning ◽

Tree Height ◽

Airborne Laser Scanning ◽

Allometric Equations ◽

Spruce Forest ◽

Individual Tree ◽

Detection Rates ◽

Site Specific ◽

Tree Detection ◽

Airborne Laser

Forest aboveground biomass (AGB) is an important variable in assessing carbon stock or ecosystem functioning, as well as for forest management. Among methods of forest AGB estimation laser scanning attracts attention because it allows for detailed measurements of forest structure. Here we evaluated variables that influence forest AGB estimation from airborne laser scanning (ALS), specifically characteristics of ALS inputs and of a derived canopy height model (CHM), and role of allometric equations (local vs. global models) relating tree height, stem diameter (DBH), and crown radius. We used individual tree detection approach and analyzed forest inventory together with ALS data acquired for 11 stream catchments with dominant Norway spruce forest cover in the Czech Republic. Results showed that the ALS input point densities (4–18 pt/m2) did not influence individual tree detection rates. Spatial resolution of the input CHM rasters had a greater impact, resulting in higher detection rates for CHMs with pixel size 0.5 m than 1.0 m for all tree height categories. In total 12 scenarios with different allometric equations for estimating stem DBH from ALS-derived tree height were used in empirical models for AGB estimation. Global DBH models tend to underestimate AGB in young stands and overestimate AGB in mature stands. Using different allometric equations can yield uncertainty in AGB estimates of between 16 and 84 tons per hectare, which in relative values corresponds to between 6% and 37% of the mean AGB per catchment. Therefore, allometric equations (mainly for DBH estimation) should be applied with care and we recommend, if possible, to establish one’s own site-specific models. If that is not feasible, the global allometric models developed here, from a broad variety of spruce forest sites, can be potentially applicable for the Central European region.

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Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle

Forests ◽

10.3390/f10050415 ◽

2019 ◽

Vol 10 (5) ◽

pp. 415 ◽

Cited By ~ 11

Author(s):

Mohammad Imangholiloo ◽

Ninni Saarinen ◽

Lauri Markelin ◽

Tomi Rosnell ◽

Roope Näsi ◽

...

Keyword(s):

Laser Scanning ◽

Hyperspectral Imagery ◽

Digital Terrain Model ◽

Tree Height ◽

Point Clouds ◽

Tree Density ◽

Tree Canopy ◽

Tree Level ◽

Species Classification ◽

Individual Tree

Seedling stands are mainly inventoried through field measurements, which are typically laborious, expensive and time-consuming due to high tree density and small tree size. In addition, operationally used sparse density airborne laser scanning (ALS) and aerial imagery data are not sufficiently accurate for inventorying seedling stands. The use of unmanned aerial vehicles (UAVs) for forestry applications is currently in high attention and in the midst of quick development and this technology could be used to make seedling stand management more efficient. This study was designed to investigate the use of UAV-based photogrammetric point clouds and hyperspectral imagery for characterizing seedling stands in leaf-off and leaf-on conditions. The focus was in retrieving tree density and the height in young seedling stands in the southern boreal forests of Finland. After creating the canopy height model from photogrammetric point clouds using national digital terrain model based on ALS, the watershed segmentation method was applied to delineate the tree canopy boundary at individual tree level. The segments were then used to extract tree heights and spectral information. Optimal bands for calculating vegetation indices were analysed and used for species classification using the random forest method. Tree density and the mean tree height of the total and spruce trees were then estimated at the plot level. The overall tree density was underestimated by 17.5% and 20.2% in leaf-off and leaf-on conditions with the relative root mean square error (relative RMSE) of 33.5% and 26.8%, respectively. Mean tree height was underestimated by 20.8% and 7.4% (relative RMSE of 23.0% and 11.5%, and RMSE of 0.57 m and 0.29 m) in leaf-off and leaf-on conditions, respectively. The leaf-on data outperformed the leaf-off data in the estimations. The results showed that UAV imagery hold potential for reliably characterizing seedling stands and to be used to supplement or replace the laborious field inventory methods.

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Estimating Individual Tree Height and Diameter at Breast Height (DBH) from Terrestrial Laser Scanning (TLS) Data at Plot Level

Forests ◽

10.3390/f9070398 ◽

2018 ◽

Vol 9 (7) ◽

pp. 398 ◽

Cited By ~ 27

Author(s):

Guangjie Liu ◽

Jinliang Wang ◽

Pinliang Dong ◽

Yun Chen ◽

Zhiyuan Liu

Keyword(s):

Laser Scanning ◽

Terrestrial Laser Scanning ◽

Tree Height ◽

Individual Tree ◽

Diameter At Breast Height ◽

Breast Height

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THE EFFECT OF WIND ON TREE STEM PARAMETER ESTIMATION USING TERRESTRIAL LASER SCANNING

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-iii-8-117-2016 ◽

2016 ◽

Vol III-8 ◽

pp. 117-122 ◽

Cited By ~ 6

Author(s):

M. T. Vaaja ◽

J.-P. Virtanen ◽

M. Kurkela ◽

V. Lehtola ◽

J. Hyyppä ◽

...

Keyword(s):

Parameter Estimation ◽

Laser Scanning ◽

Terrestrial Laser Scanning ◽

Tree Height ◽

Individual Tree ◽

Finnish Meteorological Institute ◽

Wind Speeds ◽

Forest Inventories ◽

Level Data ◽

Tree Stem

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Developing Allometric Equations for Teak Plantations Located in the Coastal Region of Ecuador from Terrestrial Laser Scanning Data

Forests ◽

10.3390/f10121050 ◽

2019 ◽

Vol 10 (12) ◽

pp. 1050 ◽

Cited By ~ 2

Author(s):

Fernando J. Aguilar ◽

Abderrahim Nemmaoui ◽

Alberto Peñalver ◽

José R. Rivas ◽

Manuel A. Aguilar

Keyword(s):

Laser Scanning ◽

Coastal Region ◽

Terrestrial Laser Scanning ◽

Tree Height ◽

Tree Level ◽

Stem Volume ◽

Automatic Data ◽

Allometric Models ◽

Teak Plantations ◽

Tree Stem

Traditional studies aimed at developing allometric models to estimate dry above-ground biomass (AGB) and other tree-level variables, such as tree stem commercial volume (TSCV) or tree stem volume (TSV), usually involves cutting down the trees. Although this method has low uncertainty, it is quite costly and inefficient since it requires a very time-consuming field work. In order to assist in data collection and processing, remote sensing is allowing the application of non-destructive sampling methods such as that based on terrestrial laser scanning (TLS). In this work, TLS-derived point clouds were used to digitally reconstruct the tree stem of a set of teak trees (Tectona grandis Linn. F.) from 58 circular reference plots of 18 m radius belonging to three different plantations located in the Coastal Region of Ecuador. After manually selecting the appropriate trees from the entire sample, semi-automatic data processing was performed to provide measurements of TSCV and TSV, together with estimates of AGB values at tree level. These observed values were used to develop allometric models, based on diameter at breast height (DBH), total tree height (h), or the metric DBH2 × h, by applying a robust regression method to remove likely outliers. Results showed that the developed allometric models performed reasonably well, especially those based on the metric DBH2 × h, providing low bias estimates and relative RMSE values of 21.60% and 16.41% for TSCV and TSV, respectively. Allometric models only based on tree height were derived from replacing DBH by h in the expression DBH2 x h, according to adjusted expressions depending on DBH classes (ranges of DBH). This finding can facilitate the obtaining of variables such as AGB (carbon stock) and commercial volume of wood over teak plantations in the Coastal Region of Ecuador from only knowing the tree height, constituting a promising method to address large-scale teak plantations monitoring from the canopy height models derived from digital aerial stereophotogrammetry.

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Airborne laser scanning applied to eucalyptus stand inventory at individual tree level

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2018001200010 ◽

2018 ◽

Vol 53 (12) ◽

pp. 1373-1382 ◽

Cited By ~ 1

Author(s):

Diogo Nepomuceno Cosenza ◽

Vicente Paulo Soares ◽

Helio Garcia Leite ◽

José Marinaldo Gleriani ◽

Cibele Hummel do Amaral ◽

...

Keyword(s):

Laser Scanning ◽

Large Scale ◽

Tree Height ◽

Point Clouds ◽

Equation System ◽

Airborne Laser Scanning ◽

Tree Level ◽

Individual Tree ◽

Local Maxima ◽

Airborne Laser

Abstract: The objective of this work was to evaluate the application of airborne laser scanning (ALS) to a large-scale eucalyptus stand inventory by the method of individual trees, as well as to propose a new method to estimate tree diameter as a function of the height obtained from point clouds. The study was carried out in a forest area of 1,681 ha, consisting of eight eucalyptus stands with ages varying from four to seven years. After scanning, tree heights were obtained using the local maxima algorithm, and total wood stock by summing up individual volumes. To determine tree diameters, regressions fit using data measured in the inventory plots were used. The results were compared with the estimates obtained from field sampling. The equation system proposed is adequate to be applied to the tree height data derived from ALS point clouds. The tree individualization approach by local maxima filters is efficient to estimate number of trees and wood stock from ALS data, as long as the results are previously calibrated with field data.

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