scholarly journals Forest aboveground volume assessments with terrestrial laser scanning: a ground-truth validation experiment in temperate, managed forests

2021 ◽  
Author(s):  
Miro Demol ◽  
Kim Calders ◽  
Hans Verbeeck ◽  
Bert Gielen
Keyword(s):  
Laser Scanning ◽  
Basic Density ◽  
Terrestrial Laser Scanning ◽  
Ground Truth ◽  
Stem Volume ◽  
Calibration Data ◽  
Ground Truth Data ◽  
Allometric Models ◽  
Volumetric Errors ◽  
Validation Experiment

Abstract Background and Aims Quantifying the Earth’s forest aboveground biomass (AGB) is indispensable for effective climate action and developing forest policy. Yet, current allometric scaling models (ASM) to estimate AGB suffer several drawbacks related to model selection and calibration data traceability uncertainties. Terrestrial laser scanning (TLS) offers a promising non-destructive alternative. Tree volume is reconstructed from TLS point clouds with Quantitative Structure Models (QSM) and converted to AGB with wood basic density. Earlier studies have found overall TLS-derived forest volume estimates to be accurate, but highlighted problems for reconstructing finer branches. Our objective was to evaluate TLS for estimating tree volumes by comparison with reference volumes and volumes from ASMs. Methods We quantified the woody volume of 65 trees in Belgium (77 – 2.800 L; Pinus sylvestris, Fagus sylvatica, Larix decidua, Fraxinus excelsior) with QSMs and destructive reference measurements. We tested a volume expansion factor (VEF) approach by multiplying the solid and merchantable volume from QSM with literature VEF values. Key Results Stem volume was reliably estimated with TLS. Total volume was overestimated by +21% using original QSMs, by +9% and -12% using two sets of VEF-augmented QSMs, and by -7.3% using best-available allometric models. The most accurate method differed per site, and the prediction errors for each method varied considerably between sites. Conclusions VEF-augmented QSMs were only slightly better than original QSMs for estimating tree volume for common species in temperate forests. Despite satisfying estimates with ASMs, the model choice was a large source of uncertainty, and species-specific models did not always exist. Therefore, we advocate for further improving tree volume reconstructions with QSMs, especially for fine branches, instead of collecting more ground-truth data to calibrate VEF and allometric models. Promising developments such as improved coregistration and smarter filtering approaches are ongoing to further constrain volumetric errors in TLS-derived estimates.

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

Forests ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 1050 ◽  
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.

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.

ESTIMATING SINGLE TREE STEM AND BRANCH BIOMASS USING TERRESTRIAL LASER SCANNING

2015 ◽  
Vol 77 (26) ◽  
Author(s):  
Nurliyana Izzati Ishak ◽  
Md Afif Abu Bakar ◽  
Muhammad Zulkarnain Abdul Rahman ◽  
Abd Wahid Rasib ◽  
Kasturi Devi Kanniah ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Stem Volume ◽  
Biomass Estimation ◽  
Forest Plot ◽  
Individual Tree ◽  
Matching Process ◽  
Branch Biomass ◽  
Individual Trees ◽  
Tree Stem

This paper presents a novel non-destructive approach for individual tree stem and branch biomass estimation using terrestrial laser scanning data. The study area is located at the Royal Belum Reserved Forest area, Gerik, Perak. Each forest plot was designed with a circular shape and contains several scanning locations to ensure good visibility of each tree. Unique tree signage was located on trees with diameter at breast height (DBH) of 10cm and above.  Extractions of individual trees were done manually and the matching process with the field collected tree properties were relied on the tree signage and tree location as collected by total station. Individual tree stems were reconstructed based on cylinder models from which the total stem volume was calculated. Biomass of individual tree stems was calculated by multiplying stem volume with specific wood density. Biomass of individual was estimated using similar concept of tree stem with the volume estimated from alpha-hull shape. The root mean squared errors (RMSE) of estimated biomass are 50.22kg and 27.20kg for stem and branch respectively. 

Nondestructive Tree Stem and Crown Volume Allometry in Hybrid Poplar Plantations Derived from Terrestrial Laser Scanning

2020 ◽  
Vol 66 (6) ◽  
pp. 737-746
Author(s):  
Francesco Chianucci ◽  
Nicola Puletti ◽  
Mirko Grotti ◽  
Carlotta Ferrara ◽  
Achille Giorcelli ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Stem Volume ◽  
Tree Crown ◽  
Crown Volume ◽  
Tree Inventory ◽  
Entry Models ◽  
Poplar Plantations ◽  
Volume Estimates ◽  
Tree Stem

Abstract Accurate and frequently updated tree volume estimates are required for poplar plantations, which are characterized by fast growth rate and short rotation. In this study, we tested the potential of terrestrial laser scanning (TLS) as a reliable method for developing nondestructive tree volume allometries in poplar plantations. The trial was conducted in Italy, where 4- to 10-year-old hybrid plantations were sampled to develop tree crown volume allometry in leaf-on conditions, tree stem volume, and height-diameter allometries in leaf-off conditions. We tested one-entry models based on diameter and two-entry models based on both diameter and height. Model performance was assessed by residual analysis. Results indicate that TLS can provide accurate models of tree stem and crown volume, with percentage of root-mean-square error of about 20 percent and 15 percent, respectively. The inclusion of height does not bring relevant improvement in the models, so that only diameter can be used to predict tree stem and crown volume. The TLS-measured stem volume estimates agreed with an available formula derived from harvesting. We concluded that TLS is a reliable method for developing nondestructive volume allometries in poplar plantations and holds great potential to enhance conventional tree inventory and monitoring. Study Implications: Terrestrial laser scanning (TLS) is a technique that allows nondestructive measurement of the three-dimensional structure of a tree with high precision and low cost. The ability of TLS to measure both tree crown volume and tree position can be effective to test optimal spacing requirements and also to test innovative schemes such as mixed or polycyclic poplar plantations. The spatially explicit nature of TLS measurements allows better integration with different remotely sensed sensors, which can be used in combination with TLS, enabling a multiscale assessment of poplar plantation structure with different levels of detail, enhancing conventional tree inventory and supporting effective management strategies.

Weighted Spherical Sampling of Point Clouds for Forested Scenes

2020 ◽  
Vol 86 (10) ◽  
pp. 619-625 ◽  
Author(s):  
Alex Fafard ◽  
Ali Rouzbeh Kargar ◽  
Jan van Aardt
Keyword(s):  
Laser Scanning ◽  
Elevation Angle ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Sampling Bias ◽  
Volume Measurement ◽  
Stem Volume ◽  
Spherical Coordinate ◽  
Volume Assessment

Terrestrial laser scanning systems are characterized by a sampling pattern which varies in point density across the hemisphere. Additionally, close objects are over-sampled relative to objects that are farther away. These two effects compound to potentially bias the three-dimensional statistics of measured scenes. Previous methods of sampling have resulted in a loss of structural coherence. In this article, a method of sampling is proposed to optimally sample points while preserving the structure of a scene. Points are sampled along a spherical coordinate system, with probabilities modulated by elevation angle and squared distance from the origin. The proposed approach is validated through visual comparison and stem-volume assessment in a challenging mangrove forest in Micronesia. Compared to several well-known sampling techniques, the proposed approach reduces sampling bias and shows strong performance in stem-reconstruction measurement. The proposed sampling method matched or exceeded the stem-volume measurement accuracy across a variety of tested decimation levels. On average it achieved 3.0% higher accuracy at estimating stem volume than the closest competitor. This approach shows promise for improving the evaluation of terrestrial laser-scanning data in complex scenes.

scholarly journals AUTOMATED STRUCTURAL FOREST CHANGES USING LIDAR POINT CLOUDS AND GIS ANALYSES

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 603-608
Author(s):  
A. Novo ◽  
H. González-Jorge ◽  
J. Martínez-Sánchez ◽  
J. M. Fernández-Alonso ◽  
H. Lorenzo
Keyword(s):  
Spatial Data ◽  
Forest Structure ◽  
Laser Scanning ◽  
Structural Model ◽  
Canopy Cover ◽  
Ground Truth ◽  
Point Clouds ◽  
Forest Community ◽  
Structural Behaviour ◽  
Ground Truth Data

Abstract. Forest spatial structure describes the relationships among different species in the same forest community. Automation in the monitoring of the structural forest changes and forest mapping is one of the main utilities of applications of modern geoinformatics methods. The obtaining objective information requires the use of spatial data derived from photogrammetry and remote sensing. This paper investigates the possibility of applying light detection and ranging (LiDAR) point clouds and geographic information system (GIS) analyses for automated mapping and detection changes in vegetation structure during a year of study. The research was conducted in an area of the Ourense Province (NWSpain). The airborne laser scanning (ALS) data, acquired in August 2019 and June of 2020, reveal detailed changes in forest structure. Based on ALS data the vegetation parameters will be analysed.To study the structural behaviour of the tree vegetation, the following parameters are used in each one of the sampling areas: (1) Relationship between the tree species present and their stratification; (2) Vegetation classification in fuel types; (3) Biomass (Gi); (4) Number of individuals per area; and (5) Canopy cover fraction (CCF). Besides, the results were compared with the ground truth data recollected in the study area.The development of a quantitative structural model based on Aerial Laser Scanning (ALS) point clouds was proposed to accurately estimate tree attributes automatically and to detect changes in forest structure. Results of statistical analysis of point cloud show the possibility to use UAV LiDAR data to characterize changes in the structure of vegetation.

scholarly journals LOW COST MULTI-SENSOR ROBOT LASER SCANNING SYSTEM AND ITS ACCURACY INVESTIGATIONS FOR INDOOR MAPPING APPLICATION

2017 ◽  
Vol XLII-2/W8 ◽  
pp. 83-85 ◽  
Author(s):  
C. Chen ◽  
X. Zou ◽  
M. Tian ◽  
J. Li ◽  
W. Wu ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Laser Scanning ◽  
Low Cost ◽  
Laser Scanner ◽  
Ground Truth ◽  
Measurement Unit ◽  
Scanning System ◽  
Ground Truth Data ◽  
Multiple Sensor ◽  
Laser Scanning System

In order to solve the automation of 3D indoor mapping task, a low cost multi-sensor robot laser scanning system is proposed in this paper. The multiple-sensor robot laser scanning system includes a panorama camera, a laser scanner, and an inertial measurement unit and etc., which are calibrated and synchronized together to achieve simultaneously collection of 3D indoor data. Experiments are undertaken in a typical indoor scene and the data generated by the proposed system are compared with ground truth data collected by a TLS scanner showing an accuracy of 99.2% below 0.25 meter, which explains the applicability and precision of the system in indoor mapping applications.

scholarly journals RIGOROUS STRIP ADJUSTMENT OF AIRBORNE LASERSCANNING DATA BASED ON THE ICP ALGORITHM

2015 ◽  
Vol II-3/W5 ◽  
pp. 73-80 ◽  
Author(s):  
P. Glira ◽  
N. Pfeifer ◽  
C. Briese ◽  
C. Ressl
Keyword(s):  
Measurement Errors ◽  
Laser Scanning ◽  
Ground Truth ◽  
Point Clouds ◽  
Redundant Information ◽  
Ground Truth Data ◽  
Icp Algorithm ◽  
Airborne Laser ◽  
Fully Automatic

Airborne Laser Scanning (ALS) is an efficient method for the acquisition of dense and accurate point clouds over extended areas. To ensure a gapless coverage of the area, point clouds are collected strip wise with a considerable overlap. The redundant information contained in these overlap areas can be used, together with ground-truth data, to re-calibrate the ALS system and to compensate for systematic measurement errors. This process, usually denoted as <i>strip adjustment</i>, leads to an improved georeferencing of the ALS strips, or in other words, to a higher data quality of the acquired point clouds. We present a fully automatic strip adjustment method that (a) uses the original scanner and trajectory measurements, (b) performs an on-the-job calibration of the entire ALS multisensor system, and (c) corrects the trajectory errors individually for each strip. Like in the Iterative Closest Point (ICP) algorithm, correspondences are established iteratively and directly between points of overlapping ALS strips (avoiding a time-consuming segmentation and/or interpolation of the point clouds). The suitability of the method for large amounts of data is demonstrated on the basis of an ALS block consisting of 103 strips.

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.

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