scholarly journals ABSOLUTE 3D ACCURACY ASSESSMENT OF UAS LIDAR SURVEYING

2021 ◽  
Vol XLIV-M-3-2021 ◽  
pp. 105-111
Author(s):  
H. A. Lassiter ◽  
B. Wilkinson ◽  
A. Gonzalez Perez ◽  
C. Kelly
Keyword(s):  
Data Collection ◽  
Point Cloud ◽  
Accuracy Assessment ◽  
Absolute Error ◽  
Ground Control ◽  
Error Budget ◽  
Ground Survey ◽  
Vertical Accuracy ◽  
Aerial Systems

Abstract. Surveying an area with small, unoccupied aerial systems (UAS) equipped with a lidar mapping payload—absent permanent, stable, geometrical reference surfaces—demands accurate, repeatable data collection procedures. While relative error within a single UAS lidar dataset may reveal itself in strip misalignment, absolute error (particularly horizontal error) can prove more difficult to detect, casting doubt upon the quality of both individual surveys and time change analyses of multiple surveys of the area. To gain insight on the UAS lidar error budget, this study presents an analysis of multiple UAS lidar surveys over a set of accurately surveyed geometric checkpoints. Each flight’s trajectory was processed multiple times using multiple static GNSS base observations, both autonomous and set over surveyed monuments, at varying distances from the study site. Custom algorithms were used to mensurate the geometric targets detected in each UAS lidar survey's point cloud, allowing for precise comparison of both absolute horizontal and vertical accuracy of each survey against the rigorous ground survey. The results of the analysis suggest that high horizontal accuracy can be achieved under a variety of conditions, whereas vertical accuracy is sensitive to the quality of ground control. and a discussion of the results explores the ultimate goal of isolating and understanding the sources and magnitudes of error in the UAS lidar error budget.

scholarly journals COMPARISON OF UAS-BASED PHOTOGRAMMETRY SOFTWARE FOR 3D POINT CLOUD GENERATION: A SURVEY OVER A HISTORICAL SITE

2017 ◽  
Vol IV-4/W4 ◽  
pp. 55-61 ◽  
Author(s):  
F. Alidoost ◽  
H. Arefi
Keyword(s):  
Point Cloud ◽  
Accuracy Assessment ◽  
Point Clouds ◽  
Surface Model ◽  
Geospatial Information ◽  
Software Packages ◽  
Comparison Results ◽  
3D City Modelling ◽  
Time Acquisition

Nowadays, Unmanned Aerial System (UAS)-based photogrammetry offers an affordable, fast and effective approach to real-time acquisition of high resolution geospatial information and automatic 3D modelling of objects for numerous applications such as topography mapping, 3D city modelling, orthophoto generation, and cultural heritages preservation. In this paper, the capability of four different state-of-the-art software packages as 3DSurvey, Agisoft Photoscan, Pix4Dmapper Pro and SURE is examined to generate high density point cloud as well as a Digital Surface Model (DSM) over a historical site. The main steps of this study are including: image acquisition, point cloud generation, and accuracy assessment. The overlapping images are first captured using a quadcopter and next are processed by different software to generate point clouds and DSMs. In order to evaluate the accuracy and quality of point clouds and DSMs, both visual and geometric assessments are carry out and the comparison results are reported.

Application of Postprocessing Kinematic Methods with UAS Remote Sensing in Forest Ecosystems

2021 ◽  
Author(s):  
Zachary M Miller ◽  
Joseph Hupy ◽  
Aishwarya Chandrasekaran ◽  
Guofan Shao ◽  
Songlin Fei
Keyword(s):  
Remote Sensing ◽  
Data Collection ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Control Points ◽  
Gps Technology ◽  
Ground Control Points ◽  
Forested Areas ◽  
Rapid Deployment ◽  
Aerial Systems

Abstract Unmanned Aerial Systems (UAS) serve as an excellent remote-sensing platform to fulfill an aerial imagery data collection niche previously unattainable in forestry by satellites and manned aircraft. However, for UAS-derived data to be spatially representative, a precise network of ground control points (GCP) is often required, which can be tedious and limit the logistical benefits of UAS rapid deployment capabilities, especially in densely forested areas. Therefore, methods for efficient data collection without GCPs are highly desired in UAS remote sensing. Here, we demonstrate the use of postprocessing kinematic (PPK) technology to obtain subcentimeter precision in datasets of forested areas without the need for placing GCPs. We evaluated two key measures, positional variability and time efficiency, of the PPK technology by comparing them to traditional GCP methods. Results show that PPK displays consistently higher positional precision than traditional GCP approaches. Moreover, PPK surveys and processing take less time to complete than traditional GCP methods and require fewer logistical steps, especially in image acquisition. The time and resource savings with PPK as compared to GCP processing are undeniable. We conclude that PPK technology provides a practical means to produce precise aerial forest surveys. Study Implications Unmanned Aerial Systems (UAS) have enormous potential for lowering costs and streamlining practices in the forestry management and research community. Despite this potential, however, UAS forestry applications have been limited in scope and precision because of a reliance on using ground-based GPS technology to survey ground control points (GCP), which are time intensive and require an open view of the sky. Such a need for a ground-based GCP survey, along with forest canopy serving to limit and scatter incoming GPS signals, diminishes the potential for rapid deployment and precision mapping offered by UAS. Fortunately, Postprocessing-Kinematic (PPK) GPS technology lowers these barriers by providing the means to seamlessly gather highly precise UAS imagery without needing to conduct time-intensive ground-based surveys. This study compares the precision and time-effectiveness between traditional GCP marker surveys and PPK correction methods.

scholarly journals Impact of UAV Surveying Parameters on Mixed Urban Landuse Surface Modelling

2020 ◽  
Vol 9 (11) ◽  
pp. 656
Author(s):  
Muhammad Hamid Chaudhry ◽  
Anuar Ahmad ◽  
Qudsia Gulzar
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Accuracy Assessment ◽  
Computational Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
High Computational Cost

Unmanned Aerial Vehicles (UAVs) as a surveying tool are mainly characterized by a large amount of data and high computational cost. This research investigates the use of a small amount of data with less computational cost for more accurate three-dimensional (3D) photogrammetric products by manipulating UAV surveying parameters such as flight lines pattern and image overlap percentages. Sixteen photogrammetric projects with perpendicular flight plans and a variation of 55% to 85% side and forward overlap were processed in Pix4DMapper. For UAV data georeferencing and accuracy assessment, 10 Ground Control Points (GCPs) and 18 Check Points (CPs) were used. Comparative analysis was done by incorporating the median of tie points, the number of 3D point cloud, horizontal/vertical Root Mean Square Error (RMSE), and large-scale topographic variations. The results show that an increased forward overlap also increases the median of the tie points, and an increase in both side and forward overlap results in the increased number of point clouds. The horizontal accuracy of 16 projects varies from ±0.13m to ±0.17m whereas the vertical accuracy varies from ± 0.09 m to ± 0.32 m. However, the lowest vertical RMSE value was not for highest overlap percentage. The tradeoff among UAV surveying parameters can result in high accuracy products with less computational cost.

scholarly journals Improvement of 3D Power Line Extraction from Multiple Low-Cost UAV Imagery Using Wavelet Analysis

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 700 ◽  
Author(s):  
Anna Fryskowska
Keyword(s):  
Point Cloud ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Power Line ◽  
Power Lines ◽  
Remotely Sensed Data ◽  
Processing Algorithms

Three-dimensional (3D) mapping of power lines is very important for power line inspection. Many remotely-sensed data products like light detection and ranging (LiDAR) have been already studied for power line surveys. More and more data are being obtained via photogrammetric measurements. This increases the need for the implementation of advanced processing techniques. In recent years, there have been several developments in visualisation techniques using UAV (unmanned aerial vehicle) platform photography. The most modern of such imaging systems have the ability to generate dense point clouds. However, image-based point cloud accuracy is very often various (unstable) and dependent on the radiometric quality of images and the efficiency of image processing algorithms. The main factor influencing the point cloud quality is noise. Such problems usually arise with data obtained via low-cost UAV platforms. Therefore, generated point clouds representing power lines are usually incomplete and noisy. To obtain a complete and accurate 3D model of power lines and towers, it is necessary to develop improved data processing algorithms. The experiment tested the algorithms on power lines with different voltages. This paper presents the wavelet-based method of processing data acquired with a low-cost UAV camera. The proposed, original method involves the application of algorithms for coarse filtration and precise filtering. In addition, a new way of calculating the recommended flight height was proposed. At the end, the accuracy assessment of this two-stage filtration process was examined. For this, point quality indices were proposed. The experimental results show that the proposed algorithm improves the quality of low-cost point clouds. The proposed methods improve the accuracy of determining the parameters of the lines by more than twice. About 10% of noise is reduced by using the wavelet-based approach.

scholarly journals Positional Accuracy Assessment of Lidar Point Cloud from NAIP/3DEP Pilot Project

2020 ◽  
Vol 12 (12) ◽  
pp. 1974 ◽  
Author(s):  
Minsu Kim ◽  
Seonkyung Park ◽  
Jeffrey Irwin ◽  
Collin McCormick ◽  
Jeffrey Danielson ◽  
...  
Keyword(s):  
Error Analysis ◽  
Point Cloud ◽  
Accuracy Assessment ◽  
Point Clouds ◽  
Absolute Error ◽  
Airborne Lidar ◽  
Conjugate Points ◽  
Geometric Feature ◽  
Intersection Points ◽  
The U.S

The Leica Geosystems CountryMapper hybrid system has the potential to collect data that satisfy the U.S. Geological Survey (USGS) National Geospatial Program (NGP) and 3D Elevation Program (3DEP) and the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) requirements in a single collection. This research will help 3DEP determine if this sensor has the potential to meet current and future 3DEP topographic lidar collection requirements. We performed an accuracy analysis and assessment on the lidar point cloud produced from CountryMapper. The boresighting calibration and co-registration by georeferencing correction based on ground control points are assumed to be performed by the data provider. The scope of the accuracy assessment is to apply the following variety of ways to measure the accuracy of the delivered point cloud to obtain the error statistics. Intraswath uncertainty from a flat surface was computed to evaluate the point cloud precision. Intraswath difference between opposite scan directions and the interswath overlap difference were evaluated to find boresighting or any systematic errors. Absolute vertical accuracy over vegetated and non-vegetated areas were also assessed. Both horizontal and vertical absolute errors were assessed using the 3D absolute error analysis methodology of comparing conjugate points derived from geometric features. A three-plane feature makes a single unique intersection point. Intersection points were computed from ground-based lidar and airborne lidar point clouds for comparison. The difference between two intersection points form one error vector. The geometric feature-based error analysis was applied to intraswath, interswath, and absolute error analysis. The CountryMapper pilot data appear to satisfy the accuracy requirements suggested by the USGS lidar specification, based upon the error analysis results. The focus of this research was to demonstrate various conventional accuracy measures and novel 3D accuracy techniques using two different error computation methods on the CountryMapper airborne lidar point cloud.

scholarly journals Geometric Targets for UAS Lidar

2019 ◽  
Vol 11 (24) ◽  
pp. 3019 ◽  
Author(s):  
Benjamin Wilkinson ◽  
H. Andrew Lassiter ◽  
Amr Abd-Elrahman ◽  
Raymond R. Carthy ◽  
Peter Ifju ◽  
...  
Keyword(s):  
Point Cloud ◽  
Accuracy Assessment ◽  
Point Clouds ◽  
Geospatial Data ◽  
Precise Location ◽  
Position Uncertainty ◽  
Rural Settings ◽  
Aerial Systems ◽  
Viable Method ◽  
Different Levels

Lidar from small unoccupied aerial systems (UAS) is a viable method for collecting geospatial data associated with a wide variety of applications. Point clouds from UAS lidar require a means for accuracy assessment, calibration, and adjustment. In order to carry out these procedures, specific locations within the point cloud must be precisely found. To do this, artificial targets may be used for rural settings, or anywhere there is a lack of identifiable and measurable features in the scene. This paper presents the design of lidar targets for precise location based on geometric structure. The targets and associated mensuration algorithm were tested in two scenarios to investigate their performance under different point densities, and different levels of algorithmic rigor. The results show that the targets can be accurately located within point clouds from typical scanning parameters to <2 cm σ , and that including observation weights in the algorithm based on propagated point position uncertainty leads to more accurate results.

scholarly journals The Effect of Environmental Conditions on the Quality of UAS Orthophoto-Maps in the Coastal Environment

2021 ◽  
Vol 10 (1) ◽  
pp. 18
Author(s):  
Michaela Doukari ◽  
Stelios Katsanevakis ◽  
Nikolaos Soulakellis ◽  
Konstantinos Topouzelis
Keyword(s):  
Environmental Conditions ◽  
Accuracy Assessment ◽  
Marine Conservation ◽  
Unmanned Aerial Systems ◽  
Remotely Sensed Data ◽  
Rough Sea Surface ◽  
Thematic Accuracy ◽  
Aerial Systems ◽  
Remote Sensing Methods

Marine conservation and management require detailed and accurate habitat mapping, which is usually produced by collecting data using remote sensing methods. In recent years, unmanned aerial systems (UAS) are used for marine data acquisition, as they provide detailed and reliable information through very high-resolution orthophoto-maps. However, as for all remotely sensed data, it is important to study and understand the accuracy and reliability of the produced maps. In this study, the effect of different environmental conditions on the quality of UAS orthophoto-maps was examined through a positional and thematic accuracy assessment. Selected objects on the orthophoto-maps were also assessed as to their position, shape, and extent. The accuracy assessment results showed significant errors in the different maps and objects. The accuracy of the classified images varied between 2.1% and 27%. Seagrasses were under-classified, while the mixed substrate class was overclassified when environmental conditions were not optimal. The highest misclassifications were caused due to sunglint presence in combination with a rough sea-surface. A change detection workflow resulted in detecting misclassifications of up to 45%, on orthophoto-maps that had been generated under non-optimal environmental conditions. The results confirmed the importance of optimal conditions for the acquisition of reliable marine information using UAS.

scholarly journals PERFORMANCE EVALUATION OF sUAS EQUIPPED WITH VELODYNE HDL-32E LiDAR SENSOR

2017 ◽  
Vol XLII-2/W6 ◽  
pp. 171-177 ◽  
Author(s):  
G. Jozkow ◽  
P. Wieczorek ◽  
M. Karpina ◽  
A. Walicka ◽  
A. Borkowski
Keyword(s):  
Point Cloud ◽  
Accuracy Assessment ◽  
Laser Scanner ◽  
Point Clouds ◽  
Theoretical Point ◽  
Absolute Accuracy ◽  
Trajectory Reconstruction ◽  
Planar Surfaces ◽  
Reconstruction Quality

The Velodyne HDL-32E laser scanner is used more frequently as main mapping sensor in small commercial UASs. However, there is still little information about the actual accuracy of point clouds collected with such UASs. This work evaluates empirically the accuracy of the point cloud collected with such UAS. Accuracy assessment was conducted in four aspects: impact of sensors on theoretical point cloud accuracy, trajectory reconstruction quality, and internal and absolute point cloud accuracies. Theoretical point cloud accuracy was evaluated by calculating 3D position error knowing errors of used sensors. The quality of trajectory reconstruction was assessed by comparing position and attitude differences from forward and reverse EKF solution. Internal and absolute accuracies were evaluated by fitting planes to 8 point cloud samples extracted for planar surfaces. In addition, the absolute accuracy was also determined by calculating point 3D distances between LiDAR UAS and reference TLS point clouds. Test data consisted of point clouds collected in two separate flights performed over the same area. Executed experiments showed that in tested UAS, the trajectory reconstruction, especially attitude, has significant impact on point cloud accuracy. Estimated absolute accuracy of point clouds collected during both test flights was better than 10&amp;thinsp;cm, thus investigated UAS fits mapping-grade category.

scholarly journals INVESTIGATION INTO THE USE OF ACTION CAMERAS IN THE DOCUMENTATION OF ARCHITECTURAL DETAILS &ndash; THE CASE STUDY OF A BAROQUE CHAMBER

2018 ◽  
Vol XLII-2 ◽  
pp. 667-674 ◽  
Author(s):  
J. Markiewicz ◽  
S. Łapiński ◽  
M. Pilarska ◽  
R. Bieńkowski ◽  
A. Kaliszewska
Keyword(s):  
Point Cloud ◽  
Low Cost ◽  
Point Clouds ◽  
Distortion Correction ◽  
Ground Control ◽  
Architectural Elements ◽  
Ground Control Points ◽  
Analysis Quality

In this paper the possibility of using the Xiaomi 4K action cameras as a low-cost sensor for the generation of high resolution documentation of architecture and architectural elements in the field of Cultural Heritage was analysed. For that purpose a series of images was acquired together with tachometric measurements to determine the ground control points. Additionally TLS data was collected, which was treated as a reference. For the purpose of point cloud generation the Structure-from-motion (SfM) and Multi- View Stereo (MVS) approaches were used. The following parameters of the collected data and the resulting documentation were tested: the interior orientation parameters analysis, quality of the Xiaomi built-in Lenses Distortion Correction; the accuracy of the orientation on ground control and check points, the point cloud density; the flatness of the walls; the discrepancies between point clouds derived from the low-cost cameras and TLS data, shape of the architectural details based on cross-section analysis. After the analysis of the obtained results it can be concluded that the Xiaomi 4K low-cost sensors are well suited for the purpose of documentation of architecture and architectural details. All the data for the presented investigation were acquired at the baroque residence of the Bieliński Palace in Otwock Wielki in Poland.

Estimating Earthwork Volumes Through Use of Unmanned Aerial Systems

2017 ◽  
Vol 2630 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Xi Wang ◽  
Zamaan Al-Shabbani ◽  
Roy Sturgill ◽  
Adam Kirk ◽  
Gabriel B. Dadi
Keyword(s):  
Point Cloud ◽  
Cloud Model ◽  
Survey Methods ◽  
Three Dimensional ◽  
Unmanned Aerial Systems ◽  
Construction Sites ◽  
Practical Applications ◽  
Ground Survey ◽  
Three Dimensional Models ◽  
Aerial Systems

Unmanned aerial systems (UASs) and unmanned aerial vehicles (UAVs) have become increasingly attractive for numerous surveying applications in civil engineering, agriculture, and many other fields. The unmanned systems and vehicles are capable of performing photogrammetric data acquisition with equipped digital cameras that allows for converting images to highly precise, georeferenced three-dimensional models. However, more studies are needed to demonstrate practical applications of UAS systems and UAVs on construction sites. In this project, UAS systems and UAVs and digital photogrammetry technology are introduced to estimate the earthwork volume of a highway extension project. The georeferenced images were processed by the photogrammetry software, Pix4Dmapper, which is a tool for converting images into an accurate and applicable three-dimensional point cloud model. Progress models were created over the course of several weeks. The volume of earth was computed by comparing the point cloud of the progress models after model processing. To ensure reliability, the accuracy of the UAS and UAV photogrammetry was verified by comparison with conventional ground survey methods and the results from different flights. The project presents the feasibility and effectiveness of using UAS systems and UAVs in estimating earthwork volumes on the basis of the results of an accuracy test and the efficiency of the survey.

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