scholarly journals Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan

2022 ◽  
Vol 106 ◽  
pp. 102658
Author(s):  
Katsuto Shimizu ◽  
Tomohiro Nishizono ◽  
Fumiaki Kitahara ◽  
Keiko Fukumoto ◽  
Hideki Saito
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Coniferous Forests ◽  
Individual Tree ◽  
Aerial Vehicle

Retrieving individual tree heights from a point cloud generated with optical imagery from an unmanned aerial vehicle (UAV)

2020 ◽  
Vol 50 (10) ◽  
pp. 1012-1024
Author(s):  
Meimei Wang ◽  
Jiayuan Lin
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Point Cloud ◽  
Laser Scanning ◽  
Tree Height ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Surface Model ◽  
Individual Tree ◽  
Aerial Vehicle ◽  
The Mean

Individual tree height (ITH) is one of the most important vertical structure parameters of a forest. Field measurement and laser scanning are very expensive for large forests. In this paper, we propose a cost-effective method to acquire ITHs in a forest using the optical overlapping images captured by an unmanned aerial vehicle (UAV). The data sets, including a point cloud, a digital surface model (DSM), and a digital orthorectified map (DOM), were produced from the UAV imagery. The canopy height model (CHM) was obtained by subtracting the digital elevation model (DEM) from the DSM removed of low vegetation. Object-based image analysis was used to extract individual tree crowns (ITCs) from the DOM, and ITHs were initially extracted by overlaying ITC outlines on the CHM. As the extracted ITHs were generally slightly shorter than the measured ITHs, a linear relationship was established between them. The final ITHs of the test site were retrieved by inputting extracted ITHs into the linear regression model. As a result, the coefficient of determination (R2), the root mean square error (RMSE), the mean absolute error (MAE), and the mean relative error (MRE) of the retrieved ITHs against the measured ITHs were 0.92, 1.08 m, 0.76 m, and 0.08, respectively.

scholarly journals Three-Dimensional Digital Documentation of Cultural Heritage Site Based on the Convergence of Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry

2019 ◽  
Vol 8 (2) ◽  
pp. 53 ◽  
Author(s):  
Young Jo ◽  
Seonghyuk Hong
Keyword(s):  
Cultural Heritage ◽  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Three Dimensional Model ◽  
Positional Accuracy ◽  
Heritage Sites ◽  
Aerial Vehicle ◽  
Digital Documentation

Three-dimensional digital technology is important in the maintenance and monitoring of cultural heritage sites. This study focuses on using a combination of terrestrial laser scanning and unmanned aerial vehicle (UAV) photogrammetry to establish a three-dimensional model and the associated digital documentation of the Magoksa Temple, Republic of Korea. Herein, terrestrial laser scanning and UAV photogrammetry was used to acquire the perpendicular geometry of the buildings and sites, where UAV photogrammetry yielded higher planar data acquisition rate in upper zones, such as the roof of a building, than terrestrial laser scanning. On comparing the two technologies’ accuracy based on their ground control points, laser scanning was observed to provide higher positional accuracy than photogrammetry. The overall discrepancy between the two technologies was found to be sufficient for the generation of convergent data. Thus, the terrestrial laser scanning and UAV photogrammetry data were aligned and merged post conversion into compatible extensions. A three-dimensional (3D) model, with planar and perpendicular geometries, based on the hybrid data-point cloud was developed. This study demonstrates the potential for using the integration of terrestrial laser scanning and UAV photogrammetry in 3D digital documentation and spatial analysis of cultural heritage sites.

scholarly journals THREE-DIMENSIONAL DIGITAL DOCUMENTATION OF HERITAGE SITES USING TERRESTRIAL LASER SCANNING AND UNMANNED AERIAL VEHICLE PHOTOGRAMMETRY

2017 ◽  
Vol XLII-2/W5 ◽  
pp. 395-398 ◽  
Author(s):  
Y. H. Jo ◽  
J.Y. Kim
Keyword(s):  
Cultural Heritage ◽  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Heritage Sites ◽  
Ground Control Points ◽  
Aerial Vehicle ◽  
Digital Documentation ◽  
Absolute Coordinate System

Three-dimensional digital documentation is an important technique for the maintenance and monitoring of cultural heritage sites. This study focuses on the three-dimensional digital documentation of the Magoksa Temple, Republic of Korea, using a combination of terrestrial laser scanning and unmanned aerial vehicle (UAV) photogrammetry. Terrestrial laser scanning mostly acquired the vertical geometry of the buildings. In addition, the digital orthoimage produced by UAV photogrammetry had higher horizontal data acquisition rate than that produced by terrestrial laser scanning. Thus, the scanning and UAV photogrammetry were merged by matching 20 corresponding points and an absolute coordinate system was established using seven ground control points. The final, complete threedimensional shape had perfect horizontal and vertical geometries. This study demonstrates the potential of integrating terrestrial laser scanning and UAV photogrammetry for three-dimensional digital documentation. This new technique is expected to contribute to the three-dimensional digital documentation and spatial analysis of cultural heritage sites.

scholarly journals The Feasibility of Modelling the Crown Profile of Larix olgensis Using Unmanned Aerial Vehicle Laser Scanning Data

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5555 ◽  
Author(s):  
Ying Quan ◽  
Mingze Li ◽  
Zhen Zhen ◽  
Yuanshuo Hao ◽  
Bin Wang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
Low Cost ◽  
Pearson Correlation ◽  
Point Clouds ◽  
Larix Olgensis ◽  
Individual Tree ◽  
Profile Fitting ◽  
Aerial Vehicle ◽  
Individual Trees

Unmanned aerial vehicle (UAV) laser scanning, as an emerging form of near-ground light detection and ranging (LiDAR) remote sensing technology, is widely used for crown structure extraction due to its flexibility, convenience, and high point density. Herein, we evaluated the feasibility of using a low-cost UAV-LiDAR system to extract the fine-scale crown profile of Larix olgensis. Specifically, individual trees were isolated from LiDAR point clouds and then stratified from the point clouds of segmented individual tree crowns at 0.5 m intervals to obtain the width percentiles of each layer as profile points. Four equations (the parabola, Mitscherlich, power, and modified beta equations) were then applied to model the profiles of the entire and upper crown. The results showed that a region-based hierarchical cross-section analysis algorithm can successfully delineate 77.4% of the field-measured trees in high-density (>2400 trees/ha) forest stands. The crown profile generated with the 95th width percentile was adequate when compared with the predicted value of the existing field-based crown profile model (the Pearson correlation coefficient (ρ) was 0.864, root mean square error (RMSE) = 0.3354 m). The modified beta equation yielded slightly better results than the other equations for crown profile fitting and explained 85.9% of the variability in the crown radius for the entire crown and 87.8% of this variability for the upper crown. Compared with the cone and 3D convex hull volumes, the crown volumes predicted by our profile models had significantly smaller errors. The results revealed that the crown profile can be well described by using UAV-LiDAR, providing a novel way to obtain crown profile information without destructive sampling and showing the potential of the use of UAV-LiDAR in future forestry investigations and monitoring.

scholarly journals Individual Tree Diameter Estimation in Small-Scale Forest Inventory Using UAV Laser Scanning

2020 ◽  
Vol 13 (1) ◽  
pp. 24
Author(s):  
Yuanshuo Hao ◽  
Faris Rafi Almay Widagdo ◽  
Xin Liu ◽  
Ying Quan ◽  
Lihu Dong ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Random Effects ◽  
Forest Inventory ◽  
Point Cloud ◽  
Laser Scanning ◽  
Small Scale ◽  
Individual Tree ◽  
Scanning Angle ◽  
Tree Diameter ◽  
Aerial Vehicle

Unmanned aerial vehicle laser scanning (UAVLS) systems present a relatively new means of remote sensing and are increasingly applied in the field of forest ecology and management. However, one of the most essential parameters in forest inventory, tree diameter at breast height (DBH), cannot be directly extracted from aerial point cloud data due to the limitations of scanning angle and canopy obstruction. Therefore, in this study DBH-UAVLS point cloud estimation models were established using a generalized nonlinear mixed-effects (NLME) model. The experiments were conducted using Larix olgensis as the subject species, and a total of 8364 correctly delineated trees from UAVLS data within 118 plots across 11 sites were used for DBH modeling. Both tree- and plot-level metrics were obtained using light detection and ranging (LiDAR) and were used as the models’ independent predictors. The results indicated that the addition of site-level random effects significantly improved the model fitting. Compared with nonparametric modeling approaches (random forest and k-nearest neighbors) and uni- or multivariable weighted nonlinear least square regression through leave-one-site-out cross-validation, the NLME model with local calibration achieved the lowest root mean square error (RMSE) values (1.94 cm) and the most stable prediction across different sites. Using the site in a random-effects model improved the transferability of LiDAR-based DBH estimation. The best linear unbiased predictor (BLUP), used to conduct local model calibration, led to an improvement in the models’ performance as the number of field measurements increased. The research provides a baseline for unmanned aerial vehicle (UAV) small-scale forest inventories and might be a reasonable alternative for operational forestry.

scholarly journals 3D AIR POLLUTION COMPUTATIONAL FLUID MODELLING DATA ANALYSIS USING TERRESTRIAL LASER SCANNING (TLS) AND UNMANNED AERIAL VEHICLE (UAV) APPROACH

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 451-456
Author(s):  
N. Ridzuan ◽  
U. Ujang ◽  
S. Azri ◽  
T. L. Choon
Keyword(s):  
Air Pollution ◽  
Data Acquisition ◽  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
Cfd Simulation ◽  
Terrestrial Laser Scanning ◽  
Suitable Model ◽  
Suitability Analysis ◽  
Building Model ◽  
Aerial Vehicle

Abstract. Air pollution is a global event that can harm the environment and people. It is recommended that effective management be implemented to allow for the sustainable development of a specific area. The 3D building model is employed in the study to support air pollution modelling for this purpose. A proper mode of data acquisition is required to produce the building model. Many data acquisition (Terrestrial Laser Scanning and Unmanned Aerial Vehicle) approaches can be utilized, but the most appropriate one for the use in outdoor air pollution is needed. This is because it can assist in providing precise data for the modelling of a 3D building while maintaining the shape and geometry of the real-world structure. The accurate data can support modelling of surrounding air pollution concerning wind data and surrounding conditions, where different generated structures can influence the flow of the pollutants. The suitable model can be determined by using suitability analysis and with the implementation of Computational Fluid Dynamics (CFD) simulation. However, from these, no specific technique is chosen because the generated models presented incomplete model. Hence, it is suggested to combine both techniques to acquire building data as the missing surfaces from each technique can be completed by another technique. Thus, this study provides a good reference for responsible agencies or researchers in selecting the best technique for modelling the building model in air pollution-related studies.

scholarly journals 3D modelling of beach topography changes caused by the tombolo phenomenon using terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry on the example of the city of Sopot

2020 ◽  
Vol 40 (5) ◽  
pp. 675-685 ◽  
Author(s):  
Cezary Specht ◽  
Pawel S. Dabrowski ◽  
Mariusz Specht
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Cross Sections ◽  
Laser Scanning ◽  
Morphological Changes ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
3D Modelling ◽  
Sea Bottom ◽  
Aerial Vehicle ◽  
The City

Abstract In 2011, a yacht marina was built in Sopot (the largest holiday resort in Poland), which initiated the formation of a local shallowing of the bottom related to the tombolo effect. The building of the marina led to disturbances in the transmission of bottom deposits along the coast, which resulted from waves and the shift of the beach coastline by approx. 50 m towards the sea. Its effects include progressive morphological changes in the shore and the sea bottom, which will lead to the formation of a peninsula between the shore and the marina in the future. This paper presents the results of a comparative analysis of the accuracy of 3D modelling of the tombolo phenomenon in the onshore part of the beach using both point clouds obtained by terrestrial laser scanning methods and photogrammetric methods based on unmanned aerial vehicle photographs. The methods subjected to assessment include both those for land modelling and for determining the coastline course and its changes. The analysis results prove the existence of sub-metre differences in the imaged relief and the coastline course, which were demonstrated using an analysis of land cross-sections. The possibilities and limitations of both methods are demonstrated as well.

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