Unmanned Aerial Systems Technology Research Articles

Meta-Analysis Assessing Potential of Drone Remote Sensing in Estimating Plant Traits Related to Nitrogen Use Efficiency

Unmanned Aerial Systems (UASs) are increasingly vital in precision agriculture, offering detailed, real-time insights into plant health across multiple spectral domains. However, this technology’s precision in estimating plant traits associated with Nitrogen Use Efficiency (NUE), and the factors affecting this precision, are not well-documented. This review examines the capabilities of UASs in assessing NUE in crops. Our analysis specifically highlights how different growth stages critically influence NUE and biomass assessments in crops and reveals a significant impact of specific signal processing techniques and sensor types on the accuracy of remote sensing data. Optimized flight parameters and precise sensor calibration are underscored as key for ensuring the reliability and validity of collected data. Additionally, the review delves into how different canopy structures, like planophile and erect leaf orientations, uniquely influence spectral data interpretation. The study also recognizes the untapped potential of image texture features in UAV-based remote sensing for detailed analysis of canopy micro-architecture. Overall, this research not only underscores the transformative impact of UAS technology on agricultural productivity and sustainability but also demonstrates its potential in providing more accurate and comprehensive insights for effective crop health and nutrient management strategies.

Factors Influencing the Cost of Utilizing Unmanned Aerial Systems for Construction Monitoring

Unmanned Aerial Systems (UAS) have emerged as a promising technology for construction monitoring due to their ability to collect data efficiently and provide valuable insights. However, the cost implications associated with the use of UAS in construction monitoring remain a significant concern. This research aims to investigate the factors that influence the cost of utilizing unmanned aerial systems for construction monitoring. By analyzing various cost-related factors such as equipment, training, data processing, and regulatory compliance, this study seeks to provide valuable insights into the financial considerations involved in adopting UAS technology for construction monitoring. The findings of this research can help project stakeholders make informed decisions and optimize cost-efficiency when implementing UAS in construction monitoring practices.

From Selection to Design: Diverse Perspectives of Human Factors Issues in Unmanned Aerial Systems

Unmanned Aerial Systems (UASs) serve many roles in the broader defense space- with mission sets like reconnaissance, remote delivery, and supporting other aircraft operations. In the future of UASs, human factors professionals serve a broad role in advocating for the users in the design process. This discussion panel will involve individuals with different experiences working with UAS technologies and its introduction to the end user. The panel will consist of the following topics: capturing user feedback, control station design for supervisory control, selection of operators as this technology grows, and broad issues in public policy. The panelists with a variety of civilian and military experience will highlight their day-to-day role as well as what they see as upcoming topics worth researching in this domain.

Unmanned Aerial Systems as a Driving Force in the Digital Information Age

Unmanned Aerial Systems (UAS), while no longer viewed as a disruptive technology, are still in their infancy regarding how this form of technology fits within the digital information age. This commentary review examines the history of UAS technology and how the rapid growth of UAS driven primarily by hardware in the form of centralized controllers, IMUs, and GPS, getting smaller, lighter, and cheaper. While the growth of UAS demonstrates itself as an outcome of the modern digital age, we argue that it now has the potential to drive the information age forward in four primary areas: cloud-based technology, Internet of Things, Artificial Intelligence, and Big Data.

Advanced Landslide Prediction Utilising Unmanned Aerial Vehicle (UAV)

Slope stability involves developing a terrain slope profile and determining the geometry of the failure surface to compute the slope factor of safety. Terrain capture and reconstruction traditionally has been expensive, time consuming and manpower intensive. This innovative method utilizing unmanned aerial system technology alongside the advancement in graphics processing can be proven as more effective and cost efficient. This research aims to develop a method to forecast the occurrence of landslide by utilizing drone technology. The objectives are to obtain data on terrain slope, create 3D model of the land, then perform analysis on the slope stability. Drone technology equipped with high accuracy GPS system captures high resolution aerial images of a land area for mapping. The data obtained is uploaded into computer software to generate the 3D model of the land. Then, the critical details such as contours or the elevations can be extracted. This information is transferred into an alternative software such as GeoStudio to analyze the stability of slope. Thus, the results can be used to predict the level of safety of the terrain slope and taken for further safety measures involving the particular area.

Enriching BIM with Unmanned Aerial Systems Data for Enhancing Construction Management Operations

The use of an unmanned aerial system (UAS) in construction project management (CPM) is an emerging methodology aimed at improving the performance of project management practices. Despite the different functions that an UAS offers, which are well covered in various sources ranging from isolated exploratory works to ad hoc case studies, construction practitioners still demonstrate little interest in UAS technology. The underwhelming interest is rooted in a lack of an understanding of the value of the data collected using UASs and their potential to enrich Building Information Modelling (BIM). This research presents the details of the UAS developed to check the accuracy of work performed, along with the generation of the corresponding progress payment reports as well as referencing and tracking information in real time, for a residential project. This study also discusses combining the data generated from the UAS and 5D BIM to develop a smart construction site. The UAS–BIM combination enables the project stakeholders to be fully informed of the work’s progress and quality to avoid mistakes that could lead to extra costs and delays. The paper identified the main obstacles to applying the UAS via interviews with the project managers and tradespersons involved in the selected project. Assuredly, a digital culture is essential for a smart construction site to shift the project team from a passive data user to a more proactive analyzer to improve performance and site safety. Other obstacles include ethical reservations, legal requirements, liability risks, weather conditions, and the continuation of using an UAS in non-open-air construction environments.

High-throughput plant phenotyping for improved turfgrass breeding applications

Turfgrasses are used extensively throughout the world, and there is a steadfast demand to develop turfgrass varieties with improved abiotic and biotic stress tolerances that will perform well with limited management inputs. Modern breeding programs incorporate advanced breeding strategies such as DNA sequencing and high-throughput phenotyping with traditional breeding strategies to identify and select germplasm and genes of interest. Molecular biology methods and DNA sequencing technology have rapidly increased in recent years, and, as a result, plant phenotyping is currently a bottleneck in the process of advancing breeding programs. Recent advances in remote sensing technology have offered improved, non-destructive plant phenotyping approaches such as visible light imaging, spectral imaging, infrared thermal imaging, range sensing, and fluorescence imaging. Integrated mobile and time efficient platforms are being developed, coupling remote sensing with robotics and unmanned aerial systems technology for high-throughput plant phenotyping applications across large field spaces. Modern turfgrass breeding programs will continue to research, develop, and implement remote sensing technologies to assess larger numbers of genotypes and identify elite germplasm. All together, these efforts will improve cultivar development efficiency and aid plant breeders in developing improved turfgrass cultivars to meet current and future demands of the turfgrass industry. This review provides an overview of ground- and aerial-based plant phenotyping platforms, with particular emphasis placed on applications to turfgrass breeding practices. Similarly, imaging technologies that have been used in various plant breeding programs are discussed, with indications as to how those technologies could be applicable to turfgrass breeding programs.

Unmanned aerial systems in search and rescue applications with their path planning: a review

In recent days, the Unmanned Aerial Systems (UAS) is an emerging technology rapidly across many warfare’s and enable new civilian domains which include real-time monitoring, security, border surveillance, wildlife surveys, providing wireless coverage, weather monitoring, smart farming, surveying, search and rescue, products delivery, farming, and civil structure inspection. Initially, there were many challenges in the design and control of UAS as it lacks an onboard pilot for navigation. Now the condition is improved with the implementation of artificial intelligence techniques in path planning and their coordination. Unmanned Aerial vehicles (UAV) in UAS technology open up new potentials in a variety of fields. This paper presents a review of recent literature, starting with the introduction about the UAS and its types, components, developments, potential applications of UAV in search and rescue and the paper completes with a summary of the different path planning methods used in UAS.

Toys or Tools? Utilization of Unmanned Aerial Systems in Mosquito and Vector Control Programs.

Organized mosquito control programs (MCP) in the United States have been protecting public health since the early 1900s. These programs utilize integrated mosquito management for surveillance and control measures to enhance quality of life and protect the public from mosquito-borne diseases. Because much of the equipment and insecticides are developed for agriculture, MCP are left to innovate and adapt what is available to accomplish their core missions. Unmanned aerial systems (UAS) are one such innovation that are quickly being adopted by MCP. The advantages of UAS are no longer conjectural. In addition to locating mosquito larval habitats, UAS affords MCP real-time imagery, improved accuracy of aerial insecticide applications, mosquito larval detection and sampling. UAS are also leveraged for applying larvicides to water in habitats that range in size from multi-acre wetlands to small containers in urban settings. Employing UAS can reduce staff exposure to hazards and the impact associated with the use of heavy equipment in sensitive habitats. UAS are utilized by MCP nationally and their use will continue to increase as technology advances and regulations change. Current impediments include a dearth of major UAS manufacturers of equipment that is tailor-made for mosquito control, pesticides that are optimized for application via UAS and regulations that limit the access of UAS to national airspace. This manuscript highlights the strengths and weaknesses of UAS within MCP, provides an update on systems and methods used, and charts the future direction of UAS technology within MCP tasked with public health protection.

Identification of Wind-Induced Hazard Zones Impacting UAS Bridge Inspection

Unmanned Aerial Systems (UAS) continue to grow in both popularity and utility within the national airspace system. The use of commercial UAS for civil inspection, specifically that of bridge structures, is becoming commonplace among practitioners and academics alike. The development of an integrated bridge-inspection hazard model provides a way for UAS operators to prepare for and respond to changing environmental conditions that could otherwise prevent a successful UAS flight. The interaction of wind-induced airflow with bridge surfaces creates an aerodynamic wake that can result in hazardous conditions for a UAS platform operating in close proximity. An analysis of this airflow surrounding an overpass bridge using computational fluid dynamic (CFD) models shows where these hazardous areas exist, based on initial wind conditions, existing functionality of UAS platforms, and mitigating systems that exist within current UAS technology. Altering the initial conditions by modifying wind velocities allows for a baseline understanding of which areas surrounding an overpass bridge structure are not suitable for successful UAS flight. Hazard zones range from severe, moderate, and mild, to no appreciable hazard. Moderate to extreme hazard zones are located in areas where high levels of wind shear, vorticity, or general turbulence exist, making UAS operations difficult. This study develops a practical model that may be utilized by UAS operators to better understand and potentially avoid unsafe flight environments during bridge structure inspections.

Determining the Optimal Number of Ground Control Points for Varying Study Sites through Accuracy Evaluation of Unmanned Aerial System-Based 3D Point Clouds and Digital Surface Models

The rapid development of drone technologies, such as unmanned aerial systems (UASs) and unmanned aerial vehicles (UAVs), has led to the widespread application of three-dimensional (3D) point clouds and digital surface models (DSMs). Due to the number of UAS technology applications across many fields, studies on the verification of the accuracy of image processing results have increased. In previous studies, the optimal number of ground control points (GCPs) was determined for a specific area of a study site by increasing or decreasing the amount of GCPs. However, these studies were mainly conducted in a single study site, and the results were not compared with those from various study sites. In this study, to determine the optimal number of GCPs for modeling multiple areas, the accuracy of 3D point clouds and DSMs were analyzed in three study sites with different areas according to the number of GCPs. The results showed that the optimal number of GCPs was 12 for small and medium sites (7 and 39 ha) and 18 for the large sites (342 ha) based on the overall accuracy. If these results are used for UAV image processing in the future, accurate modeling will be possible with minimal effort in GCPs.

Performance of an aerially applied liquid Bacillus thuringiensis var. israelensis formulation (strain AM65-52) against mosquitoes in mixed saltmarsh-mangrove systems and fine-scale mapping of mangrove canopy cover using affordable drone-based imagery.

In the Australian southeast, the saltmarsh mosquito Aedes vigilax (Skuse) is the focus of area-wide larviciding campaigns employing the biological agent Bacillus thuringiensis var. israelensis (Bti). Although generally effective, frequent inundating tides and considerable mangrove cover can make control challenging. Here, we describe the efficacy and persistence of an aqueous Bti suspension (potency: 1200 International Toxic Units; strain AM65-52) within a mixed saltmarsh-mangrove system and the use of affordable unmanned aerial systems (UAS) to identify and map problematic levels of mangrove canopy cover. High mangrove canopy density (>40% cover) reduced product deposition by 75.2% (0.01 ± 0.002 μL cm-2 versus 0.05 ± 0.006 μL cm-2 ), larval mortality by 27.7% (60.7 ± 4.1% versus 84.0 ± 2.4%), and ground level Bti concentrations by 32.03% (1144 ± 462.6 versus 1683 ± 447.8 spores mL-1 ) relative to open saltmarsh. Persistence of product post-application was found to be low (80.6% loss at 6 h) resulting in negligible additional losses to tidal inundation 24 h post-application. UAS surveys accurately identified areas of high mangrove cover using both standard and multispectral imagery, although derived index values for this vegetation class were only moderately correlated with ground measurements (R2 = 0.17-0.38) at their most informative scales. These findings highlight the complex operational challenges that affect coastal mosquito control in heterogeneous environments. The problem is exacerbated by continued mangrove transgression into saltmarsh habitat in the region. Emerging UAS technology can help operators optimize treatments by accurately identifying and mapping challenging canopy cover using both standard and multispectral imaging. © 2020 Society of Chemical Industry.

Upscaling UAS Paradigm to UltraLight Aircrafts: A Low-Cost Multi-Sensors System for Large Scale Aerial Photogrammetry

The use of unmanned aerial systems (UASs) has rapidly grown in many civil applications since the early 2010s. Nowadays, a large variety of reliable low-cost UAS sensors and controllers are available. However, contrary to ultralight aircrafts (ULAs), UASs have a too small operational range to efficiently cover large areas. Flight regulations prevailing in many countries further reduced this operational range; in particular, the “within visual line of sight” rule. This study presents a new system for image acquisition and high-quality photogrammetry of large scale areas (>10 km²). It was developed by upscaling the UAS paradigm, i.e., low-cost sensors and controllers, little (or no) on-board active stabilization, and adequate structure from motion photogrammetry, to an ULA platform. Because the system is low-cost (good quality-price ratio of UAS technologies), multi-sensors (large variety of available UAS sensors) and versatile (high ULA operational flexibility and more lenient regulation than for other platforms), the possible applications are numerous in miscellaneous research domains. The system was described in detail and illustrated from the flight and images acquisition to the photogrammetric routine. The system was successfully used to acquire high resolution and high quality RGB and multispectral images, and produced precisely georeferenced digital elevation model (DEM) and orthophotomosaics for a forested area of 1200 ha. The system can potentially carry any type of sensors. The system compatibility with any sensor can be tested, in terms of image quality and flight plan, with the proposed method. This study also highlighted a major technical limitation of the low-cost thermal infrared cameras: the too high integration time with respect to the flight speed of most UASs and ULAs. By providing the complete information required for reproducing the system, the authors seek to encourage its implementation in different geographical locations and scientific contexts, as well as, its combination with other sensors, in particular, laser imaging detection and ranging (LiDAR) and hyperspectral.

A Systematic Review of the Factors Influencing the Estimation of Vegetation Aboveground Biomass Using Unmanned Aerial Systems

Interest in the use of unmanned aerial systems (UAS) to estimate the aboveground biomass (AGB) of vegetation in agricultural and non-agricultural settings is growing rapidly but there is no standardized methodology for planning, collecting and analyzing UAS data for this purpose. We synthesized 46 studies from the peer-reviewed literature to provide the first-ever review on the subject. Our analysis showed that spectral and structural data from UAS imagery can accurately estimate vegetation biomass in a variety of settings, especially when both data types are combined. Vegetation-height metrics are useful for trees, while metrics of variation in structure or volume are better for non-woody vegetation. Multispectral indices using NIR and red-edge wavelengths normally have strong relationships with AGB but RGB-based indices often outperform them in models. Including measures of image texture can improve model accuracy for vegetation with heterogeneous canopies. Vegetation growth structure and phenological stage strongly influence model accuracy and the selection of useful metrics and should be considered carefully. Additional factors related to the study environment, data collection and analytical approach also impact biomass estimation and need to be considered throughout the workflow. Our review shows that UASs provide a capable tool for fine-scale, spatially explicit estimations of vegetation AGB and are an ideal complement to existing ground- and satellite-based approaches. We recommend future studies aimed at emerging UAS technologies and at evaluating the effect of vegetation type and growth stages on AGB estimation.

Mapping foodscapes and sagebrush morphotypes with unmanned aerial systems for multiple herbivores

The amount and composition of phytochemicals in forage plants influences habitat quality for wild herbivores. However, evaluating forage quality at fine resolutions across broad spatial extents (i.e., foodscapes) is challenging. Unmanned aerial systems (UAS) provide an avenue for bridging this gap in spatial scale. We evaluated the potential for UAS technology to accurately predict nutritional quality of sagebrush (Artemisia spp.) across landscapes. We mapped seasonal forage quality across two sites in Idaho, USA, with different mixtures of species but similar structural morphotypes of sagebrush. We classified the sagebrush at both study sites using structural features of shrubs with object-based image analysis and machine learning and linked this classification to field measurements of phytochemicals to interpolate a foodscape for each phytochemical with regression kriging. We compared fine-scale landscape patterns of phytochemicals between sites and seasons. Classification accuracy for morphotypes was high at both study sites (81–87%). Forage quality was highly variable both within and among sagebrush morphotypes. Coumarins were the most accurately mapped (r2 = 0.57–0.81), whereas monoterpenes were the most variable and least explained. Patches with higher crude protein were larger and more connected in summer than in winter. UAS allowed for a rapid collection of imagery for mapping foodscapes based on the phytochemical composition of sagebrush at fine scales but relatively broad extents. However, results suggest that a more advanced sensor (e.g., hyperspectral camera) is needed to map mixed species of sagebrush or to directly measure forage quality.

Developing a Competency Learning Model for Students of Unmanned Aerial Systems

Over the past decade, Unmanned Aerial Systems (UAS), along with commercial UAS pilots, have become an established and increasingly regulated industry. Unfortunately, in the U.S. the number of near misses and incidents involving unsafe UAS operations is increasing dramatically. Additionally, industries looking to adopt UAS technologies not only require trained professionals to ensure safe and legal operations but may look for competencies that go well beyond the minimum regulatory requirements. To date, research regarding the higher order learning outcomes and competencies that are expected of UAS university graduates is lacking. Therefore, this research attempts to provide perspective of the core competencies that industry organizations may desire in a UAS graduate and, by extension, in a UAS professional. This paper describes the methods used to identify core UAS competencies, and presents a UAS Competency Learning Model that may help educators better prepare graduates for successful industry careers. Researchers utilized a multi-phase process over an 18-month period using both quantitative and qualitative methods, which included literature reviews, surveys, interviews, focus groups, and attendance at UAS industry events. Ultimately, from this research emerged the following six UAS competencies: Leadership, Technical Excellence, Safety and Ethics, Analytical Thinking, Teamwork, and Entrepreneurship.

How people make sense of drones used for atmospheric science (and other purposes): hopes, concerns, and recommendations

Unmanned aerial systems (UAS) can advance understanding of the atmosphere and improve weather prediction, but public perceptions of drone technologies need to be assessed to ensure successful societal integration. Our qualitative study examines public perceptions of UAS technology, and the associated risks and benefits, for such civilian purposes. We examine how people form perceptions, and discuss the implications of these perceptions for UAS design and regulation. Our study finds the public to be favorable toward UAS used for “noble” purposes. Participant views are informed by popular media, personal experiences, comparisons between technologies, and consideration of the trustworthiness of the users, regulators, and technology itself.

Validating UAS-Based Photogrammetry with Traditional Topographic Methods for Surveying Dune Ecosystems in the Spanish Mediterranean Coast

In the past few years, unmanned aerial systems (UAS) have achieved great popularity for civil uses. One of the present main uses of these devices is low-cost aerial photogrammetry, being especially useful in coastal environments. In this work, a high-resolution 3D model of a beach section in Guardamar del Segura (Spain) has been produced by employing a low maximum takeoff mass (MTOM) UAS, in combination with the use of structure-from-motion (SfM) techniques. An unprecedented extensive global navigation satellite system (GNSS) survey was simultaneously carried out to statistically validate the model by employing 1238 control points for that purpose. The results show good accuracy, obtaining a vertical root mean square error (RMSE) mean value of 0.121 m and a high point density, close to 30 pt/m2, with similar or even higher quality than most coastal surveys performed with classical techniques. UAS technology permits the acquisition of topographic data with low time-consuming surveys at a high temporal frequency. Coastal managers can implement this methodology into their workflow to study the evolution of complex, highly anthropized dune-beach systems such as the one presented in this study, obtaining more accurate surveys at lower costs.

Integrating resilience engineering and UAS technology into construction safety planning and control

PurposeThe purpose of this paper is to present an exploratory study in order to understand the contributions of the resilience engineering (RE) concept and the use of unmanned aerial systems (UASs) technology to support the safety planning and control (SPC) process.Design/methodology/approachA case study on a construction project was conducted and involved the following steps: diagnosis of the SPC process; development of a safety monitoring protocol using UASs; and field tests to monitor safety performance using UASs and data analysis.FindingsIn terms of its theoretical contribution, this work presents a conceptual framework explaining how the RE and the UASs can contribute to the SPC process. Also, this paper provides, as a practical contribution, a protocol for safety monitoring with UASs integrated into the safety routine, highlighting the tasks that can be checked and unsafe conditions and safety/production conflicts identified through monitoring.Practical implicationsThis study can be used to support and stimulate the construction managers who wish to adopt the RE concepts and UAS technology to improve safety management.Social implicationsAn efficient SPC process can improve the work conditions at construction sites, contributing with the reduction of accidents rates.Originality/valueThe paper highlights the need to adopt new approaches, as RE concepts and UAS technology to support the SPC process, in order to improve safety conditions at construction sites.

LIGHTER-THAN-AIR (LTA) UNMANNED AERIAL SYSTEM (UAS) CARRIER CONCEPT FOR SURVAILLANCE AND DISASTER MANAGEMENT

Unmanned aerial systems (UAS) has many advantages in the fields of SURVAILLANCE and disaster management compared to space-borne observation, manned missions and in situ methods. The reasons include cost effectiveness, operational safety, and mission efficiency. This has in turn underlined the importance of UAS technology and highlighted a growing need in a more robust and efficient unmanned aerial vehicles to serve specific needs in SURVAILLANCE and disaster management. This paper first gives an overview on the framework for SURVAILLANCE particularly in applications of border control and disaster management and lists several phases of SURVAILLANCE and service descriptions. Based on this overview and SURVAILLANCE phases descriptions, we show the areas and services in which UAS can have significant advantage over traditional methods.