scholarly journals Assessment of the Influence of Survey Design and Processing Choices on the Accuracy of Tree Diameter at Breast Height (DBH) Measurements Using UAV-Based Photogrammetry

Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 43
Author(s):  
Bruno Miguez Moreira ◽  
Gabriel Goyanes ◽  
Pedro Pina ◽  
Oleg Vassilev ◽  
Sandra Heleno
Keyword(s):  
Survey Design ◽  
Point Clouds ◽  
Biomass Estimation ◽  
Structural Parameter ◽  
Tree Diameter ◽  
Forested Area ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
3D Point Clouds ◽  
Mean Square Errors

This work provides a systematic evaluation of how survey design and computer processing choices (such as the software used or the workflow/parameters chosen) influence unmanned aerial vehicle (UAV)-based photogrammetry retrieval of tree diameter at breast height (DBH), an important 3D structural parameter in forest inventory and biomass estimation. The study areas were an agricultural field located in the province of Málaga, Spain, where a small group of olive trees was chosen for the UAV surveys, and an open woodland area in the outskirts of Sofia, the capital of Bulgaria, where a 10 ha area grove, composed mainly of birch trees, was overflown. A DJI Phantom 4 Pro quadcopter UAV was used for the image acquisition. We applied structure from motion (SfM) to generate 3D point clouds of individual trees, using Agisoft and Pix4D software packages. The estimation of DBH in the point clouds was made using a RANSAC-based circle fitting tool from the TreeLS R package. All trees modeled had their DBH tape-measured on the ground for accuracy assessment. In the first study site, we executed many diversely designed flights, to identify which parameters (flying altitude, camera tilt, and processing method) gave us the most accurate DBH estimations; then, the resulting best settings configuration was used to assess the replicability of the method in the forested area in Bulgaria. The best configuration tested (flight altitudes of about 25 m above tree canopies, camera tilt 60°, forward and side overlaps of 90%, Agisoft ultrahigh processing) resulted in root mean square errors (RMSEs; %) of below 5% of the tree diameters in the first site and below 12.5% in the forested area. We demonstrate that, when carefully designed methodologies are used, SfM can measure the DBH of single trees with very good accuracy, and to our knowledge, the results presented here are the best achieved so far using (above-canopy) UAV-based photogrammetry.

scholarly journals Estimating Structure and Biomass of a Secondary Atlantic Forest in Brazil Using Fourier Transforms of Vertical Profiles Derived from UAV Photogrammetry Point Clouds

2020 ◽  
Vol 12 (21) ◽  
pp. 3560 ◽  
Author(s):  
André Almeida ◽  
Fabio Gonçalves ◽  
Gilson Silva ◽  
Rodolfo Souza ◽  
Robert Treuhaft ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Atlantic Forest ◽  
Fourier Transforms ◽  
Basal Area ◽  
Point Clouds ◽  
Tree Density ◽  
Vertical Profiles ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
3D Point Clouds

Knowing the aboveground biomass (AGB) stock of tropical forests is one of the main requirements to guide programs for reducing emissions from deforestation and forest degradation (REDD+). Traditional 3D products generated with digital aerial photogrammetry (DAP) have shown great potential in estimating AGB, tree density, diameter at breast height, height, and basal area in forest ecosystems. However, these traditional products explore only a small part of the structural information contained in the 3D data, thus not leveraging the full potential of the data for inventory purposes. In this study, we tested the performance of 3D products derived from DAP and a technique based on Fourier transforms of vertical profiles of vegetation to estimate AGB, tree density, diameter at breast height, height, and basal area in a secondary fragment of Atlantic Forest located in northeast Brazil. Field measurements were taken in 30 permanent plots (0.25 ha each) to estimate AGB. At the time of the inventory, we also performed a digital aerial mapping of the entire forest fragment with an unmanned aerial vehicle (UAV). Based on the 3D point clouds and the digital terrain model (DTM) obtained by DAP, vertical vegetation profiles were produced for each plot. Using traditional structure metrics and metrics derived from Fourier transforms of profiles, regression models were fit to estimate AGB, tree density, diameter at breast height, height, and basal area. The 3D DAP point clouds represented the forest canopy with a high level of detail, regardless of the vegetation density. The metrics based on the Fourier transform of profiles were selected as predictors in all models produced. The best model for AGB explained 93% (R2 = 0.93) of the biomass variation at the plot level, with an RMS error of 9.3 Mg ha−1 (22.5%). Similar results were obtained in the models fit for the tree density, diameter at breast height, height, and basal area, with R2 values above 0.90 and RMS errors of less than 18%. The use of Fourier transforms of profiles with 3D products obtained by DAP demonstrated a high potential for estimating AGB and other forest variables of interest in secondary tropical forests, highlighting the value of UAV as a low-cost tool to assist the implementation of REDD+ projects in developing countries like Brazil.

scholarly journals Canopy Parameter Estimation of Citrus grandis var. Longanyou Based on LiDAR 3D Point Clouds

2021 ◽  
Vol 13 (9) ◽  
pp. 1859
Author(s):  
Xiangyang Liu ◽  
Yaxiong Wang ◽  
Feng Kang ◽  
Yang Yue ◽  
Yongjun Zheng
Keyword(s):  
Convex Hull ◽  
Clustering Algorithm ◽  
Plant Protection ◽  
Point Clouds ◽  
Biomass Estimation ◽  
Reconstruction Method ◽  
Volume Calculation ◽  
Alpha Shape ◽  
3D Point Clouds ◽  
Canopy Volume

The characteristic parameters of Citrus grandis var. Longanyou canopies are important when measuring yield and spraying pesticides. However, the feasibility of the canopy reconstruction method based on point clouds has not been confirmed with these canopies. Therefore, LiDAR point cloud data for C. grandis var. Longanyou were obtained to facilitate the management of groves of this species. Then, a cloth simulation filter and European clustering algorithm were used to realize individual canopy extraction. After calculating canopy height and width, canopy reconstruction and volume calculation were realized using six approaches: by a manual method and using five algorithms based on point clouds (convex hull, CH; convex hull by slices; voxel-based, VB; alpha-shape, AS; alpha-shape by slices, ASBS). ASBS is an innovative algorithm that combines AS with slices optimization, and can best approximate the actual canopy shape. Moreover, the CH algorithm had the shortest run time, and the R2 values of VCH, VVB, VAS, and VASBS algorithms were above 0.87. The volume with the highest accuracy was obtained from the ASBS algorithm, and the CH algorithm had the shortest computation time. In addition, a theoretical but preliminarily system suitable for the calculation of the canopy volume of C. grandis var. Longanyou was developed, which provides a theoretical reference for the efficient and accurate realization of future functional modules such as accurate plant protection, orchard obstacle avoidance, and biomass estimation.

scholarly journals UAV-BASED AUTOMATIC TREE GROWTH MEASUREMENT FOR BIOMASS ESTIMATION

2016 ◽  
Vol XLI-B8 ◽  
pp. 685-688
Author(s):  
M. Karpina ◽  
M. Jarząbek-Rychard ◽  
P. Tymków ◽  
A. Borkowski
Keyword(s):  
Tree Growth ◽  
Point Clouds ◽  
In Situ Measurements ◽  
Unmanned Aircraft ◽  
Volume Estimation ◽  
Biomass Estimation ◽  
Test Field ◽  
3D Point Clouds ◽  
Growth Estimation

Manual in-situ measurements of geometric tree parameters for the biomass volume estimation are time-consuming and economically non-effective. Photogrammetric techniques can be deployed in order to automate the measurement procedure. The purpose of the presented work is an automatic tree growth estimation based on Unmanned Aircraft Vehicle (UAV) imagery. The experiment was conducted in an agriculture test field with scots pine canopies. The data was collected using a Leica Aibotix X6V2 platform equipped with a Nikon D800 camera. Reference geometric parameters of selected sample plants were measured manually each week. In situ measurements were correlated with the UAV data acquisition. The correlation aimed at the investigation of optimal conditions for a flight and parameter settings for image acquisition. The collected images are processed in a state of the art tool resulting in a generation of dense 3D point clouds. The algorithm is developed in order to estimate geometric tree parameters from 3D points. Stem positions and tree tops are identified automatically in a cross section, followed by the calculation of tree heights. The automatically derived height values are compared to the reference measurements performed manually. The comparison allows for the evaluation of automatic growth estimation process. The accuracy achieved using UAV photogrammetry for tree heights estimation is about 5cm.

scholarly journals Comparison of Three Algorithms to Estimate Tree Stem Diameter from Terrestrial Laser Scanner Data

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 599 ◽  
Author(s):  
Ravaglia ◽  
Fournier ◽  
Bac ◽  
Véga ◽  
Côté ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Stem Diameter ◽  
Trunk Diameter ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
Forest Inventories ◽  
Laser Scanners ◽  
Step Algorithm ◽  
Coniferous Plantations

Terrestrial laser scanners provide accurate and detailed point clouds of forest plots, which can be used as an alternative to destructive measurements during forest inventories. Various specialized algorithms have been developed to provide automatic and objective estimates of forest attributes from point clouds. The STEP (Snakes for Tuboid Extraction from Point cloud) algorithm was developed to estimate both stem diameter at breast height and stem diameters along the bole length. Here, we evaluate the accuracy of this algorithm and compare its performance with two other state-of-the-art algorithms that were designed for the same purpose (i.e., the CompuTree and SimpleTree algorithms). We tested each algorithm against point clouds that incorporated various degrees of noise and occlusion. We applied these algorithms to three contrasting test sites: (1) simulated scenes of coniferous stands in Newfoundland (Canada), (2) test sites of deciduous stands in Phalsbourg (France), and (3) coniferous plantations in Quebec, Canada. In most cases, the STEP algorithm predicted diameter at breast height with higher R2 and lower RMSE than the other two algorithms. The STEP algorithm also achieved greater accuracy when estimating stem diameter in occluded and noisy point clouds, with mean errors in the range of 1.1 cm to 2.28 cm. The CompuTree and SimpleTree algorithms respectively produced errors in the range of 2.62 cm to 6.1 cm and 1.03 cm to 3.34 cm, respectively. Unlike CompuTree or SimpleTree, the STEP algorithm was not able to estimate trunk diameter in the uppermost portions of the trees. Our results show that the STEP algorithm is more adapted to extract DBH and stem diameter automatically from occluded and noisy point clouds. Our study also highlights that SimpleTree and CompuTree require data filtering and results corrections. Conversely, none of these procedures were applied for the implementation of the STEP algorithm.

Biomass of jack pine and mixed hardwood stands in northeastern New Brunswick

1976 ◽  
Vol 6 (4) ◽  
pp. 441-447 ◽  
Author(s):  
David A. MacLean ◽  
Ross W. Wein
Keyword(s):  
New Brunswick ◽  
Tree Species ◽  
Biomass Accumulation ◽  
Jack Pine ◽  
Tree Crown ◽  
Tree Diameter ◽  
Stem Biomass ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
Fire Origin

Biomass accumulation in 12 jack pine and 11 mixed hardwood stands of fire origin ranging in age from 7 to 57 years is presented. Logarithmic equations relating aboveground tree, crown, and stem biomass to tree diameter at breast height are given for eight tree species.

scholarly journals VALIDATING A WORKFLOW FOR TREE INVENTORY UPDATING WITH 3D POINT CLOUDS OBTAINED BY MOBILE LASER SCANNING

2018 ◽  
Vol XLII-2 ◽  
pp. 1163-1168
Author(s):  
J. Wang ◽  
R. Lindenbergh
Keyword(s):  
Tree Species ◽  
Laser Scanning ◽  
Spatial Information ◽  
Open Data ◽  
Point Clouds ◽  
Urban Trees ◽  
Biomass Estimation ◽  
Species Classification ◽  
3D Point Clouds ◽  
Tree Inventory

Urban trees are an important component of our environment and ecosystem. Trees are able to combat climate change, clean the air and cool the streets and city. Tree inventory and monitoring are of great interest for biomass estimation and change monitoring. Conventionally, parameters of trees are manually measured and documented in situ, which is not efficient regarding labour and costs. Light Detection And Ranging (LiDAR) has become a well-established surveying technique for the acquisition of geo-spatial information. Combined with automatic point cloud processing techniques, this in principle enables the efficient extraction of geometric tree parameters. In recent years, studies have investigated to what extend it is possible to perform tree inventories using laser scanning point clouds. Give the availability of a city of Delft Open data tree repository, we are now able to present, validate and extend a workflow to automatically obtain tree data from tree location until tree species. The results of a test over 47 trees show that the proposed methods in the workflow are able to individual urban trees. The tree species classification results based on the extracted tree parameters show that only one tree was wrongly classified using k-means clustering.

scholarly journals ABOVEGROUND DENDROMASS ESTIMATION OF JUVENILE PAULOWNIA SP.

2017 ◽  
Vol 1 (24) ◽  
Author(s):  
Tatiana Stankova ◽  
Veselka Gyuleva ◽  
Dimitar Dimitrov ◽  
Hristina Hristova ◽  
Ekaterina Andonova
Keyword(s):  
Regression Models ◽  
Goodness Of Fit ◽  
Tree Height ◽  
Early Growth ◽  
Biomass Estimation ◽  
Allometric Relationships ◽  
Tree Diameter ◽  
Breast Height ◽  
Ornamental Trees ◽  
Total Tree

Species of the genus Paulownia have been introduced to Bulgaria since the beginning of the XXthcentury and their multipurpose uses - as ornamental trees, for wood and biomass production- have been tested ever since. We present a study, which examines the early growth of four Paulowniaclones at southern locations in Bulgaria and derives biometric models for dendromass estimationof juvenile Paulownia trees.The data originated from two experimental plantations established on nursery land using one-yearoldin vitro propagated plant material. Forty six, 1 to 3 year-old saplings from two clones of P. tomentosaand two P. elongata × P. fortunei hybrids were sampled. Their stem biomass was modeledas a function of the breast height tree diameter and total tree height or the stem diameter aloneand a set of goodness-of-fit criteria was applied to select the most adequate among the 29 testedformulations. The regression models were fitted in log-transformed form to the logarithm of thestem biomass and MM correction factor for bias was applied to the back-transformed predictiondata. Two allometric relationships were derived, which adequately assess stem dendromass ofyoung Paulownia sp. from easily measurable tree characteristics. Both models are applicable forstem biomass estimation of juvenile Paulownia trees of diameter up to 5 cm and total height upto 3.5 m.

scholarly journals A Self-Assembly Portable Mobile Mapping System for Archeological Reconstruction Based on VSLAM-Photogrammetric Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3952 ◽  
Author(s):  
* ◽  
*
Keyword(s):  
Self Assembly ◽  
Average Distance ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Models ◽  
Data Capture ◽  
Information Modeling ◽  
3D Point Clouds ◽  
Mean Square Errors

Three Dimensional (3D) models are widely used in clinical applications, geosciences, cultural heritage preservation, and engineering; this, together with new emerging needs such as building information modeling (BIM) develop new data capture techniques and devices with a low cost and reduced learning curve that allow for non-specialized users to employ it. This paper presents a simple, self-assembly device for 3D point clouds data capture with an estimated base price under €2500; furthermore, a workflow for the calculations is described that includes a Visual SLAM-photogrammetric threaded algorithm that has been implemented in C++. Another purpose of this work is to validate the proposed system in BIM working environments. To achieve it, in outdoor tests, several 3D point clouds were obtained and the coordinates of 40 points were obtained by means of this device, with data capture distances ranging between 5 to 20 m. Subsequently, those were compared to the coordinates of the same targets measured by a total station. The Euclidean average distance errors and root mean square errors (RMSEs) ranging between 12–46 mm and 8–33 mm respectively, depending on the data capture distance (5–20 m). Furthermore, the proposed system was compared with a commonly used photogrammetric methodology based on Agisoft Metashape software. The results obtained demonstrate that the proposed system satisfies (in each case) the tolerances of ‘level 1’ (51 mm) and ‘level 2’ (13 mm) for point cloud acquisition in urban design and historic documentation, according to the BIM Guide for 3D Imaging (U.S. General Services).

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