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 Measuring Height Characteristics of Sagebrush (Artemisia sp.) Using Imagery Derived from Small Unmanned Aerial Systems (sUAS)

Drones ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 6 ◽  
Author(s):  
Ryan G. Howell ◽  
Ryan R. Jensen ◽  
Steven L. Petersen ◽  
Randy T. Larsen
Keyword(s):  
Data Storage ◽  
Accuracy Assessment ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Surface Model ◽  
Sage Grouse ◽  
Double Pass ◽  
Single Pass ◽  
3D Point Clouds ◽  
Aerial Systems

In situ measurements of sagebrush have traditionally been expensive and time consuming. Currently, improvements in small Unmanned Aerial Systems (sUAS) technology can be used to quantify sagebrush morphology and community structure with high resolution imagery on western rangelands, especially in sensitive habitat of the Greater sage-grouse (Centrocercus urophasianus). The emergence of photogrammetry algorithms to generate 3D point clouds from true color imagery can potentially increase the efficiency and accuracy of measuring shrub height in sage-grouse habitat. Our objective was to determine optimal parameters for measuring sagebrush height including flight altitude, single- vs. double- pass, and continuous vs. pause features. We acquired imagery using a DJI Mavic Pro 2 multi-rotor Unmanned Aerial Vehicle (UAV) equipped with an RGB camera, flown at 30.5, 45, 75, and 120 m and implementing single-pass and double-pass methods, using continuous flight and paused flight for each photo method. We generated a Digital Surface Model (DSM) from which we derived plant height, and then performed an accuracy assessment using on the ground measurements taken at the time of flight. We found high correlation between field measured heights and estimated heights, with a mean difference of approximately 10 cm (SE = 0.4 cm) and little variability in accuracy between flights with different heights and other parameters after statistical correction using linear regression. We conclude that higher altitude flights using a single-pass method are optimal to measure sagebrush height due to lower requirements in data storage and processing time.

scholarly journals Assessing the Ability of Image Based Point Clouds Captured from a UAV to Measure the Terrain in the Presence of Canopy Cover

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 284 ◽  
Author(s):  
Luke Wallace ◽  
Chris Bellman ◽  
Bryan Hally ◽  
Jaime Hernandez ◽  
Simon Jones ◽  
...  
Keyword(s):  
Ground Surface ◽  
Canopy Cover ◽  
Weather Conditions ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Image Capture ◽  
Terrain Model ◽  
Processing Strategies ◽  
Aerial Systems

Point clouds captured from Unmanned Aerial Systems are increasingly relied upon to provide information describing the structure of forests. The quality of the information derived from these point clouds is dependent on a range of variables, including the type and structure of the forest, weather conditions and flying parameters. A key requirement to achieve accurate estimates of height based metrics describing forest structure is a source of ground information. This study explores the availability and reliability of ground surface points available within point clouds captured in six forests of different structure (canopy cover and height), using three image capture and processing strategies, consisting of nadir, oblique and composite nadir/oblique image networks. The ground information was extracted through manual segmentation of the point clouds as well as through the use of two commonly used ground filters, LAStools lasground and the Cloth Simulation Filter. The outcomes of these strategies were assessed against ground control captured with a Total Station. Results indicate that a small increase in the number of ground points captured (between 0 and 5% of a 10 m radius plot) can be achieved through the use of a composite image network. In the case of manually identified ground points, this reduced the root mean square error (RMSE) error of the terrain model by between 1 and 11 cm, with greater reductions seen in plots with high canopy cover. The ground filters trialled were not able to exploit the extra information in the point clouds and inconsistent results in terrain RMSE were obtained across the various plots and imaging network configurations. The use of a composite network also provided greater penetration into the canopy, which is likely to improve the representation of mid-canopy elements.

scholarly journals SPECIAL ASPECTS OF THE PARAMETERS ASSESSMENT OF COMMUNICATION CHANNELS OF UNMANNED AERIAL SYSTEMS CLASSI AND II

2020 ◽  
pp. 41-48
Author(s):  
V. Ilienko ◽  
O. Isachenko ◽  
A. Los ◽  
M. Gerashchenko ◽  
S. Rudnichenko
Keyword(s):  
Communication Channels ◽  
Armed Forces ◽  
Test Methods ◽  
Control Site ◽  
Standard Test ◽  
Class I ◽  
Unmanned Aerial Systems ◽  
Electronic Warfare ◽  
Aerial Systems

Considering the lack of standard test methods for communication channels of modern unmanned aerial systems (UAS) class I and II, according to the UAS classification of the Armed Forces of Ukraine, it was decided to work out the basic approaches for determining indicators, conditions and procedure for conducting tests in this direction. The suggested methodological recommendations will improve the quality of the parameters and characteristics assessment for communication channels of UAS I and II classes. One of the distinctive trends in the development of modern forms and methods of conducting armed combat at all stages of the armed conflict is the widespread use of the UASs by opposing parties. UASs are capable of significant increasing the effectiveness of accomplishing aerial reconnaissance tasks, organizing electronic warfare, and providing real-time delivery of target pinpointing to fire means for the destruction of enemy’s manpower and material. A distinctive feature of UAS is that its external crew, as a rule, accomplish its mission at a considerable distance from the objects of attack. This fact significantly reduces the security risks and threats associated with performing combat missions under conditions of active enemy counteraction. Due to this feature, considerable attention is paid to the development of a reliable communication system that would be able to ensure task accomplishment at the maximum distance from command and control site. During the tests of UAS Class I and II, the specialists of the State Scientific Research Institute of Armament and Military Equipment Testing and Certification used testing methods of radio channels assessment, which will allow to improve the quality of UAS research of this type and give the manufacturers recommendations for increasing their capabilities.

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 Thematic Accuracy Quality Control by Means of a Set of Multinomials

2019 ◽  
Vol 9 (20) ◽  
pp. 4240 ◽  
Author(s):  
Francisco J. Ariza-López ◽  
José Rodríguez-Avi ◽  
María V. Alba-Fernández ◽  
José L. García-Balboa
Keyword(s):  
Quality Control ◽  
Hypothesis Test ◽  
Accuracy Assessment ◽  
Confusion Matrix ◽  
Multinomial Distribution ◽  
Remotely Sensed Data ◽  
Error Matrix ◽  
Quality Specifications ◽  
Control Column ◽  
Thematic Accuracy

The error matrix has been adopted as both the “de facto” and the “de jure” standard way to report on the thematic accuracy assessment of any remotely sensed data product. This perspective assumes that the error matrix can be considered as a set of values following a unique multinomial distribution. However, the assumption of the underlying statistical model falls down when true reference data are available for quality control. To overcome this problem, a new method for thematic accuracy quality control is proposed, which uses a multinomial approach for each category and is called QCCS (quality control column set). The main advantage is that it allows us to state a set of quality specifications for each class and to test if they are fulfilled. These requirements can be related to the percentage of correctness in the classification for a particular class but also to the percentage of possible misclassifications or confusions between classes. In order to test whether such specifications are achieved or not, an exact multinomial test is proposed for each category. Furthermore, if a global hypothesis test is desired, the Bonferroni correction is proposed. All these new approaches allow a more flexible way of understanding and testing thematic accuracy quality control compared with the classical methods based on the confusion matrix. For a better understanding, a practical example of an application is included for classification with four categories.

scholarly journals Direct-Visual-Operation Support System for Unmanned Construction

2020 ◽  
Vol 14 (1) ◽  
pp. 105-112
Author(s):  
Shohei Yamaguchi ◽  
Yoshihiro Sato ◽  
Shota Funaki ◽  
Atsutoshi Kurihara ◽  
Satoru Nakamura ◽  
...  
Keyword(s):  
Support System ◽  
Unmanned Aerial Systems ◽  
Work Efficiency ◽  
Conventional System ◽  
Construction Sites ◽  
Switching Operation ◽  
Head Mounted Display ◽  
Construction Machine ◽  
Aerial Systems

Introduction: Unmanned construction through direct visual operation is performed to ensure the safety of workers at construction sites. In direct visual operation, although the equipment is simple and easy to install, the work efficiency and accuracy are reduced because of the lack of view and perspective obtained from boarding a construction machine. For solving this problem, images sent from multiple cameras, Unmanned Aerial Systems (UASs) attached to the construction equipment and the images obtained from boarding a construction machine, as well as blind spots are confirmed by displaying them on the monitor at hand. However, the working efficiency is lowered by the restrictions on the utilization range of the camera monitor, switching operation of the camera, and gaze movement between the construction machine and the monitor. Methods: For solving the problem of low work efficiency and accuracy of the conventional system, this paper proposes a support system for a direct visual operation that does not require monitor installation and gaze movement and enables intuitive camera switching operation by using a transmissive Head Mounted Display (HMD) and a stereo camera robot. Results and Conclusion: The results of the experiment conducted using a remote-controlled backhoe show that unskilled operators can perform the same quality of work as skilled operators, and work efficiency and accuracy was improved by 44.2% and 37.8%, respectively compared to the conventional system. This confirms the usefulness of the proposed system, especially for unskilled operators.

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 Evaluating the Effectiveness of Unmanned Aerial Systems (UAS) for Collecting Thematic Map Accuracy Assessment Reference Data in New England Forests

Forests ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 24 ◽  
Author(s):  
Benjamin T. Fraser ◽  
Russell G. Congalton
Keyword(s):  
New England ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Unmanned Aerial Systems ◽  
Complex Environments ◽  
Thematic Map ◽  
Object Based ◽  
Aerial Systems ◽  
Map Accuracy Assessment ◽  
Map Accuracy

Thematic mapping provides today’s analysts with an essential geospatial science tool for conveying spatial information. The advancement of remote sensing and computer science technologies has provided classification methods for mapping at both pixel-based and object-based analysis, for increasingly complex environments. These thematic maps then serve as vital resources for a variety of research and management needs. However, to properly use the resulting thematic map as a decision-making support tool, an assessment of map accuracy must be performed. The methods for assessing thematic accuracy have coalesced into a site-specific multivariate analysis of error, measuring uncertainty in relation to an established reality known as reference data. Ensuring statistical validity, access and time constraints, and immense costs limit the collection of reference data in many projects. Therefore, this research proposes evaluating the feasibility of adopting the low-cost, flexible, high-resolution sensor-capable Unmanned Aerial Systems (UAS, UAV, or Drone) platform for collecting reference data to use in thematic map accuracy assessments for complex environments. This pilot study analyzed 377.57 ha of New England forests, over six University of New Hampshire woodland properties, to compare the similarity between UAS-derived orthomosaic samples and ground-based continuous forest inventory (CFI) plot classifications of deciduous, mixed, and coniferous forest cover types. Using an eBee Plus fixed-wing UAS, 9173 images were acquired and used to create six comprehensive orthomosaics. Agreement between our UAS orthomosaics and ground-based sampling forest compositions reached 71.43% for pixel-based classification and 85.71% for object-based classification reference data methods. Despite several documented sources of uncertainty or error, this research demonstrated that UAS are capable of highly efficient and effective thematic map accuracy assessment reference data collection. As UAS hardware, software, and implementation policies continue to evolve, the potential to meet the challenges of accurate and timely reference data collection will only increase.

scholarly journals ANALYSIS OF THE CURRENT STATE, CHARACTERISTICS AND PROSPECTS OF DEVELOPMENT OF EXPLOSIVE ORDNANCE DETECTION SENSORS MOUNTED ON UNMANNED AERIAL SYSTEMS

2021 ◽  
pp. 80-90
Author(s):  
S. Molochko ◽  
V. Bashynskyi ◽  
O. Kalamurza ◽  
V. Zhurakhov
Keyword(s):  
Navigation System ◽  
High Efficiency ◽  
Unmanned Aerial Systems ◽  
Unmanned Aerial System ◽  
Thermal Imager ◽  
Metal Detector ◽  
Current State ◽  
Modern Economic ◽  
Aerial Systems

In recent years, the international community has become increasingly aware of the scale and severity of the problems posed by landmines and explosive remnants of war, including unexploded ordnance, gradually agreeing that this is a global problem that requires international concerted actions [1]. Significant excess of pace of development and intensity of mines use in comparison with the means of demining determine the urgency of the problem of ensuring the required level of their technical perfection. At the same time, special attention should be paid to ensuring the required level of quality of demining processes, reducing to a minimum level of explosive threats and cost of demining [2]. In modern economic conditions, the high efficiency of UXO detection in a certain area with relatively minimal cost of material and human resources is of great importance. The article analyzes the possibility of detecting explosive ordnance using a thermal imager, hyperspectral camera, magnetometer, metal detector which are installed on an unmanned aerial system (UAS). In addition, there was given consideration to the properties of sensors for detecting explosive ordnance which will ensure their full use during humanitarian demining: performance, transportability, survivability, reliability, failure-free, durability, maintainability, storage ability, cost effectiveness. Explosive ordnance detection sensors mounted on UAS must have their own navigation system or be connected to an on-board navigation system that links information from the sensors to the terrain. It must be possible to determine the coordinates of any object after landing an UAS and process information from the sensors. The calculations were made regarding the effectiveness of actions for searching and detecting explosive ordnance using an unmanned aerial system.

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