Under-Canopy UAV Laser Scanning Providing Canopy Height and Stem Volume Accurately

The automation of forest field reference data collection has been an intensive research objective for laser scanning scientists ever since the invention of terrestrial laser scanning more than two decades ago. In this study, we demonstrated that an under-canopy UAV laser scanning system utilizing a rotating laser scanner can alone provide accurate estimates of canopy height and stem volume for the majority of trees in a boreal forest. We mounted a rotating laser scanner based on a Velodyne VLP-16 sensor onboard a manually piloted UAV. The UAV was commanded with the help of a live video feed from the onboard camera. Since the system was based on a rotating laser scanner providing varying view angles, all important elements such as treetops, branches, trunks, and ground could be recorded with laser hits. In an experiment including two different forest structures, namely sparse and obstructed canopy, we showed that our system can measure the heights of individual trees with a bias of −20 cm and a standard error of 40 cm in the sparse forest and with a bias of −65 cm and a standard error of 1 m in the obstructed forest. The accuracy of the obtained tree height estimates was equivalent to airborne above-canopy UAV surveys conducted in similar forest conditions or even at the same sites. The higher underestimation and higher inaccuracy in the obstructed site can be attributed to three trees with a height exceeding 25 m and the reduced point density of these tree tops due to occlusion and the limited ranging capacity of the scanner. Additionally, we used our system to estimate the stem volumes of individual trees with a standard error at the level of 10%. This level of error is equivalent to the error obtained when merging above-canopy UAV laser scanner data with terrestrial point cloud data. The results show that we do not necessarily need a combination of terrestrial point clouds and point clouds collected using above-canopy UAV systems in order to accurately estimate the heights and the volumes of individual trees in reference data collection.

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Under-Canopy UAV Laser Scanning Providing Canopy Height and Stem Volume Accurately

10.20944/preprints202104.0003.v1 ◽

2021 ◽

Author(s):

Juha Hyyppä ◽

Xiaowei Yu ◽

Teemu Hakala ◽

Harri Kaartinen ◽

Antero Kukko ◽

...

Keyword(s):

Data Collection ◽

Standard Error ◽

Laser Scanning ◽

Laser Scanner ◽

Point Clouds ◽

Canopy Height ◽

Stem Volume ◽

Scanning System ◽

Individual Trees ◽

Laser Scanning System

Automation of forest field reference data collection has been an intensive research objective for laser scanning scientists ever since the invention of terrestrial laser scanning more than two decades ago. Recently, it has been proposed that such automated data collection providing both the tree heights and stem curves would require a combination of above-canopy UAV point clouds and terrestrial point clouds. In this study, we demonstrate that an under-canopy UAV laser scanning system utilizing a rotating laser scanner can alone provide accurate estimates of the canopy height and the stem volume for the majority of the trees in a boreal forest. To this end, we mounted a rotating laser scanner based on a Velodyne VLP-16 sensor onboard a manually piloted UAV. The UAV was commanded with the help of a live video feed from the onboard camera of the UAV. Since the system was based on a rotating laser scanner providing varying view angles, all important elements such as treetops, branches, trunks, and ground could be recorded with laser hits. In an experiment including two different forest structures, namely sparse and obstructed canopy, we showed that our system can measure the heights of individual trees with a bias of -20 cm and a standard error of 40 cm in the sparse forest and with a bias of -65 cm and a standard error of 1 m in the obstructed forest. The accuracy of the obtained tree height estimates was equivalent to airborne above-canopy UAV surveys conducted in similar forest conditions. The higher underestimation and higher inaccuracy in the obstructed site can be attributed to three trees with a height exceeding 25 m and the applied laser scanning system VLP-16 that had a limited height measurement capacity when it comes to trees taller than 25 m. Additionally, we used our system to estimate the stem volumes of individual trees with a standard error at the level of 10%. This level of error is equivalent to the error obtained when merging above-canopy UAV laser scanner data with terrestrial point cloud data. Future research is needed for testing new sensors, for implementing autonomous operation inside canopies through collision avoidance and navigation through canopies, and for developing robust methods that work also with more complex forest structure. The results show that we do not necessarily need a combination of terrestrial point clouds and point clouds collected using above-canopy UAV systems in order to accurately estimate the heights and the volumes of individual trees.

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Comparison of Backpack, Handheld, Under-Canopy UAV, and Above-Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests

Remote Sensing ◽

10.3390/rs12203327 ◽

2020 ◽

Vol 12 (20) ◽

pp. 3327 ◽

Cited By ~ 1

Author(s):

Eric Hyyppä ◽

Xiaowei Yu ◽

Harri Kaartinen ◽

Teemu Hakala ◽

Antero Kukko ◽

...

Keyword(s):

Data Collection ◽

Point Cloud ◽

Laser Scanning ◽

Reference Data ◽

Tree Height ◽

Tree Level ◽

Stem Volume ◽

Point Cloud Data ◽

Cloud Data ◽

Individual Trees

In this work, we compared six emerging mobile laser scanning (MLS) technologies for field reference data collection at the individual tree level in boreal forest conditions. The systems under study were an in-house developed AKHKA-R3 backpack laser scanner, a handheld Zeb-Horizon laser scanner, an under-canopy UAV (Unmanned Aircraft Vehicle) laser scanning system, and three above-canopy UAV laser scanning systems providing point clouds with varying point densities. To assess the performance of the methods for automated measurements of diameter at breast height (DBH), stem curve, tree height and stem volume, we utilized all of the six systems to collect point cloud data on two 32 m-by-32 m test sites classified as sparse (n = 42 trees) and obstructed (n = 43 trees). To analyze the data collected with the two ground-based MLS systems and the under-canopy UAV system, we used a workflow based on our recent work featuring simultaneous localization and mapping (SLAM) technology, a stem arc detection algorithm, and an iterative arc matching algorithm. This workflow enabled us to obtain accurate stem diameter estimates from the point cloud data despite a small but relevant time-dependent drift in the SLAM-corrected trajectory of the scanner. We found out that the ground-based MLS systems and the under-canopy UAV system could be used to measure the stem diameter (DBH) with a root mean square error (RMSE) of 2–8%, whereas the stem curve measurements had an RMSE of 2–15% that depended on the system and the measurement height. Furthermore, the backpack and handheld scanners could be employed for sufficiently accurate tree height measurements (RMSE = 2–10%) in order to estimate the stem volumes of individual trees with an RMSE of approximately 10%. A similar accuracy was obtained when combining stem curves estimated with the under-canopy UAV system and tree heights extracted with an above-canopy flying laser scanning unit. Importantly, the volume estimation error of these three MLS systems was found to be of the same level as the error corresponding to manual field measurements on the two test sites. To analyze point cloud data collected with the three above-canopy flying UAV systems, we used a random forest model trained on field reference data collected from nearby plots. Using the random forest model, we were able to estimate the DBH of individual trees with an RMSE of 10–20%, the tree height with an RMSE of 2–8%, and the stem volume with an RMSE of 20–50%. Our results indicate that ground-based and under-canopy MLS systems provide a promising approach for field reference data collection at the individual tree level, whereas the accuracy of above-canopy UAV laser scanning systems is not yet sufficient for predicting stem attributes of individual trees for field reference data with a high accuracy.

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ANALYSIS OF THE POSSIBILITIES OF USING LOW-COST SCANNING SYSTEM IN 3D MODELING

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b3-261-2016 ◽

2016 ◽

Vol XLI-B3 ◽

pp. 261-267

Author(s):

M. Kedzierski ◽

D. Wierzbickia ◽

A. Fryskowska ◽

B. Chlebowska

Keyword(s):

3D Modeling ◽

Point Cloud ◽

Laser Scanning ◽

Low Cost ◽

Comparative Method ◽

Research Work ◽

Laser Scanner ◽

Method Comparison ◽

Point Clouds ◽

Scanning System

The laser scanning technique is still a very popular and fast growing method of obtaining information on modeling 3D objects. The use of low-cost miniature scanners creates new opportunities for small objects of 3D modeling based on point clouds acquired from the scan. The same, the development of accuracy and methods of automatic processing of this data type is noticeable. The article presents methods of collecting raw datasets in the form of a point-cloud using a low-cost ground-based laser scanner FabScan. As part of the research work 3D scanner from an open source FabLab project was constructed. In addition, the results for the analysis of the geometry of the point clouds obtained by using a low-cost laser scanner were presented. Also, some analysis of collecting data of different structures (made of various materials such as: glass, wood, paper, gum, plastic, plaster, ceramics, stoneware clay etc. and of different shapes: oval and similar to oval and prism shaped) have been done. The article presents two methods used for analysis: the first one - visual (general comparison between the 3D model and the real object) and the second one - comparative method (comparison between measurements on models and scanned objects using the mean error of a single sample of observations). The analysis showed, that the low-budget ground-based laser scanner FabScan has difficulties with collecting data of non-oval objects. Items built of glass painted black also caused problems for the scanner. In addition, the more details scanned object contains, the lower the accuracy of the collected point-cloud is. Nevertheless, the accuracy of collected data (using oval-straight shaped objects) is satisfactory. The accuracy, in this case, fluctuates between ± 0,4 mm and ± 1,0 mm whereas when using more detailed objects or a rectangular shaped prism the accuracy is much more lower, between 2,9 mm and ± 9,0 mm. Finally, the publication presents the possibility (for the future expansion of research) of modernization FabScan by the implementation of a larger amount of camera-laser units. This will enable spots the registration , that are less visible.

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A CALIBRATION METHOD OF TWO MOBILE LASER SCANNING SYSTEM UNITS FOR RAILWAY MEASUREMENT

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b1-2020-277-2020 ◽

2020 ◽

Vol XLIII-B1-2020 ◽

pp. 277-283

Author(s):

K. Yamamoto ◽

T. Chen ◽

N. Yabuki

Keyword(s):

Laser Scanning ◽

Laser Scanner ◽

Point Clouds ◽

Calibration Method ◽

Railway Vehicle ◽

Scanning System ◽

Mean Square ◽

Least Mean Square ◽

Linear Type ◽

Laser Scanning System

Abstract. This paper proposes a methodology to calibrate the laser scanner of a Mobile Laser Scanning System (MLS) with the trajectory of the other MLS, both of which are installed directly above the top of both rails. Railway vehicle laser scanners systems of MLS are able to obtain 3D scanning map of the rail environment. In order to adapt the actual site condition of the maintenance works, we propose a calibration method with non-linear Least Mean Square calculation which use point clouds around poles along rails and sleepers of rails as cylindrical and planner constraints. The accuracy of 0.006 m between two laser point clouds can be achieved with this method. With the common planar and cylinder condition Leven-Marquardt method has been applied for this method. This method can execute without a good initial value for the extrinsic parameter and can shorten the processing time compared with the linear type of Least Mean Square method.

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ANALYSIS OF THE POSSIBILITIES OF USING LOW-COST SCANNING SYSTEM IN 3D MODELING

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b3-261-2016 ◽

2016 ◽

Vol XLI-B3 ◽

pp. 261-267

Author(s):

M. Kedzierski ◽

D. Wierzbickia ◽

A. Fryskowska ◽

B. Chlebowska

Keyword(s):

3D Modeling ◽

Point Cloud ◽

Laser Scanning ◽

Low Cost ◽

Comparative Method ◽

Research Work ◽

Laser Scanner ◽

Method Comparison ◽

Point Clouds ◽

Scanning System

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Development, Calibration and Evaluation of a Portable and Direct Georeferenced Laser Scanning System for Kinematic 3D Mapping

Journal of Applied Geodesy ◽

10.1515/jag-2015-0011 ◽

2015 ◽

Vol 9 (4) ◽

Cited By ~ 4

Author(s):

Erik Heinz ◽

Christian Eling ◽

Markus Wieland ◽

Lasse Klingbeil ◽

Heiner Kuhlmann

Keyword(s):

Laser Scanning ◽

Attitude Determination ◽

Low Cost ◽

Laser Scanner ◽

Point Clouds ◽

Scanning System ◽

Planar Surfaces ◽

Laser Scanners ◽

Scanning Geometry ◽

Laser Scanning System

AbstractIn recent years, kinematic laser scanning has become increasingly popular because it offers many benefits compared to static laser scanning. The advantages include both saving of time in the georeferencing and a more favorable scanning geometry. Often mobile laser scanning systems are installed on wheeled platforms, which may not reach all parts of the object. Hence, there is an interest in the development of portable systems, which remain operational even in inaccessible areas. The development of such a portable laser scanning system is presented in this paper. It consists of a lightweight direct georeferencing unit for the position and attitude determination and a small low-cost 2D laser scanner. This setup provides advantages over existing portable systems that employ heavy and expensive 3D laser scanners in a profiling mode.A special emphasis is placed on the system calibration, i. e. the determination of the transformation between the coordinate frames of the direct georeferencing unit and the 2D laser scanner. To this end, a calibration field is used, which consists of differently orientated georeferenced planar surfaces, leading to estimates for the lever arms and boresight angles with an accuracy of mm and one-tenth of a degree. Finally, point clouds of the mobile laser scanning system are compared with georeferenced point clouds of a high-precision 3D laser scanner. Accordingly, the accuracy of the system is in the order of cm to dm. This is in good agreement with the expected accuracy, which has been derived from the error propagation of previously estimated variance components.

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LOW-COST WHEELED ROBOT-BORNE LASER SCANNING SYSTEM FOR INDOOR AND OUTDOOR 3D MAPPING APPLICATION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w13-1155-2019 ◽

2019 ◽

Vol XLII-2/W13 ◽

pp. 1155-1159

Author(s):

W. Wu ◽

C. Chen ◽

Y. Cong ◽

Z. Dong ◽

J. Li ◽

...

Keyword(s):

Laser Scanning ◽

Low Cost ◽

Laser Scanner ◽

Point Clouds ◽

Measurement Unit ◽

Scanning System ◽

Outdoor Scenes ◽

Wheeled Robot ◽

Laser Scanning System ◽

Indoor And Outdoor

<p><strong>Abstract.</strong> Aiming to accomplish automatic and real-time three-dimensional mapping in both indoor and outdoor scenes, a low-cost wheeled robot-borne laser scanning system is proposed in this paper. The system includes a laser scanner, an inertial measurement unit, a modified turtlebot3 two-wheel differential chassis and etc. To achieve a globally consistent map, the system performs global trajectory optimization after detecting the loop closure. Experiments are undertaken in two typical indoor/outdoor scenes that is an underground car park and a road environment in the campus of Wuhan University. The point clouds acquired by the proposed system are quantitatively evaluated by comparing the derived point clouds with the ground truth data collected by a RIEGL VZ 400 laser scanner. The results present an accuracy of 90% points below 0.1 meter error in the tested scene, showing that its applicability and potential in indoor and mapping applications.</p>

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Revealing Changes in the Stem Form and Volume Allocation in Diverse Boreal Forests Using Two-Date Terrestrial Laser Scanning

Forests ◽

10.3390/f12070835 ◽

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.

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