Topical Collection "Feature Papers of Drones"

Editors

Dr. Pablo Rodríguez-Gonzálvez
E-Mail Website
Collection Editor
Department of Mining Technology, Topography and Structures, University of León, Avda. Astorga, s/n, 24401 Ponferrada, Spain
Interests: photogrammetry; drones; laser scanning; radiometric calibration; remote sensing; RGB-D sensors; 3D modeling; mobile mapping; metrology; verification; inspection; quality control
Special Issues and Collections in MDPI journals

Topical Collection Information

Dear Colleagues,

As editors of Drones, we are glad to announce a topical collection entitled “Feature papers of Drones”. This topical collection will be a compilation of articles, communications, and review articles from top researchers describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (aerial, terrestrial, or water/underwater). We welcome the submission of manuscripts from editorial board members and outstanding scholars invited by the editorial board and the editorial office.

Prof. Dr. Diego González-Aguilera
Dr. Pablo Rodríguez-Gonzálvez
Collection Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (32 papers)

2021

Jump to: 2020

Article
A Single-Copter UWB-Ranging-Based Localization System Extendable to a Swarm of Drones
Drones 2021, 5(3), 85; https://doi.org/10.3390/drones5030085 (registering DOI) - 30 Aug 2021
Viewed by 68
Abstract
This paper presents a single-copter localization system as a first step towards a scalable multihop drone swarm localization system. The drone was equipped with ultrawideband (UWB) transceiver modules, which can be used for communication, as well as distance measurement. The location of the [...] Read more.
This paper presents a single-copter localization system as a first step towards a scalable multihop drone swarm localization system. The drone was equipped with ultrawideband (UWB) transceiver modules, which can be used for communication, as well as distance measurement. The location of the drone was detected based on fixed anchor points using a single type of UWB transceiver. Our aim is to create a swarm localization system that enables drones to switch their role between an active swarm member and an anchor node to enhance the localization of the whole swarm. To this end, this paper presents our current baseline localization system and its performance regarding single-drone localization with fixed anchors and its integration into our current modular quadcopters, which was designed to be easily extendable to a swarm localization system. The distance between each drone and the anchors was measured periodically, and a specially tailored gradient descent algorithm was used to solve the resulting nonlinear optimization problem. Additional copter and wireless-specific adaptations were performed to enhance the robustness. The system was tested with a Vicon system as a position reference and showed a high precision of 0.2 m with an update rate of <10 Hz. Additionally, the system was integrated into the FINken copters of the SwarmLab and evaluated in multiple outdoor scenarios. These scenarios showed the generic usability of the approach, even though no accurate precision measurement was possible. Full article
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Review
Application of Drone Technologies in Surface Water Resources Monitoring and Assessment: A Systematic Review of Progress, Challenges, and Opportunities in the Global South
Drones 2021, 5(3), 84; https://doi.org/10.3390/drones5030084 (registering DOI) - 28 Aug 2021
Viewed by 163
Abstract
Accurate and timely information on surface water quality and quantity is critical for various applications, including irrigation agriculture. In-field water quality and quantity data from unmanned aerial vehicle systems (UAVs) could be useful in closing spatial data gaps through the generation of near-real-time, [...] Read more.
Accurate and timely information on surface water quality and quantity is critical for various applications, including irrigation agriculture. In-field water quality and quantity data from unmanned aerial vehicle systems (UAVs) could be useful in closing spatial data gaps through the generation of near-real-time, fine resolution, spatially explicit information required for water resources accounting. This study assessed the progress, opportunities, and challenges in mapping and modelling water quality and quantity using data from UAVs. To achieve this research objective, a systematic review was adopted. The results show modest progress in the utility of UAVs, especially in the global south. This could be attributed, in part, to high costs, a lack of relevant skills, and the regulations associated with drone procurement and operational costs. The progress is further compounded by a general lack of research focusing on UAV application in water resources monitoring and assessment. More importantly, the lack of robust and reliable water quantity and quality data needed to parameterise models remains challenging. However, there are opportunities to advance scientific inquiry for water quality and quantity accounting by integrating UAV data and machine learning. Full article
Article
Numerical Fluid Dynamics Simulation for Drones’ Chemical Detection
Drones 2021, 5(3), 69; https://doi.org/10.3390/drones5030069 - 29 Jul 2021
Viewed by 378
Abstract
The risk associated with chemical, biological, radiological, nuclear, and explosive (CBRNe) threats in the last two decades has grown as a result of easier access to hazardous materials and agents, potentially increasing the chance for dangerous events. Consequently, early detection of a threat [...] Read more.
The risk associated with chemical, biological, radiological, nuclear, and explosive (CBRNe) threats in the last two decades has grown as a result of easier access to hazardous materials and agents, potentially increasing the chance for dangerous events. Consequently, early detection of a threat following a CBRNe event is a mandatory requirement for the safety and security of human operators involved in the management of the emergency. Drones are nowadays one of the most advanced and versatile tools available, and they have proven to be successfully used in many different application fields. The use of drones equipped with inexpensive and selective detectors could be both a solution to improve the early detection of threats and, at the same time, a solution for human operators to prevent dangerous situations. To maximize the drone’s capability of detecting dangerous volatile substances, fluid dynamics numerical simulations may be used to understand the optimal configuration of the detectors positioned on the drone. This study serves as a first step to investigate how the fluid dynamics of the drone propeller flow and the different sensors position on-board could affect the conditioning and acquisition of data. The first consequence of this approach may lead to optimizing the position of the detectors on the drone based not only on the specific technology of the sensor, but also on the type of chemical agent dispersed in the environment, eventually allowing to define a technological solution to enhance the detection process and ensure the safety and security of first responders. Full article
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Article
Simulation and Characterization of Wind Impacts on sUAS Flight Performance for Crash Scene Reconstruction
Drones 2021, 5(3), 67; https://doi.org/10.3390/drones5030067 - 23 Jul 2021
Viewed by 447
Abstract
Small unmanned aircraft systems (sUASs) have emerged as promising platforms for the purpose of crash scene reconstruction through structure-from-motion (SfM) photogrammetry. However, auto crashes tend to occur under adverse weather conditions that usually pose increased risks of sUAS operation in the sky. Wind [...] Read more.
Small unmanned aircraft systems (sUASs) have emerged as promising platforms for the purpose of crash scene reconstruction through structure-from-motion (SfM) photogrammetry. However, auto crashes tend to occur under adverse weather conditions that usually pose increased risks of sUAS operation in the sky. Wind is a typical environmental factor that can cause adverse weather, and sUAS responses to various wind conditions have been understudied in the past. To bridge this gap, commercial and open source sUAS flight simulation software is employed in this study to analyze the impacts of wind speed, direction, and turbulence on the ability of sUAS to track the pre-planned path and endurance of the flight mission. This simulation uses typical flight capabilities of quadcopter sUAS platforms that have been increasingly used for traffic incident management. Incremental increases in wind speed, direction, and turbulence are conducted. Average 3D error, standard deviation, battery use, and flight time are used as statistical metrics to characterize the wind impacts on flight stability and endurance. Both statistical and visual analytics are performed. Simulation results suggest operating the simulated quadcopter type when wind speed is less than 11 m/s under light to moderate turbulence levels for optimal flight performance in crash scene reconstruction missions, measured in terms of positional accuracy, required flight time, and battery use. Major lessons learned for real-world quadcopter sUAS flight design in windy conditions for crash scene mapping are also documented. Full article
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Article
A Hybrid Approach for Autonomous Collision-Free UAV Navigation in 3D Partially Unknown Dynamic Environments
Drones 2021, 5(3), 57; https://doi.org/10.3390/drones5030057 - 08 Jul 2021
Viewed by 504
Abstract
In the past decades, unmanned aerial vehicles (UAVs) have emerged in a wide range of applications. Owing to the advances in UAV technologies related to sensing, computing, power, etc., it has become possible to carry out missions autonomously. A key component to achieving [...] Read more.
In the past decades, unmanned aerial vehicles (UAVs) have emerged in a wide range of applications. Owing to the advances in UAV technologies related to sensing, computing, power, etc., it has become possible to carry out missions autonomously. A key component to achieving this goal is the development of safe navigation methods, which is the main focus of this work. A hybrid navigation approach is proposed to allow safe autonomous operations in three-dimensional (3D) partially unknown and dynamic environments. This method combines a global path planning algorithm, namely RRT-Connect, with a reactive control law based on sliding mode control to provide quick reflex-like reactions to newly detected obstacles. The performance of the suggested approach is validated using simulations. Full article
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Article
Computational Study of the Propeller Position Effects in Wing-Mounted, Distributed Electric Propulsion with Boundary Layer Ingestion in a 25 kg Remotely Piloted Aircraft
Drones 2021, 5(3), 56; https://doi.org/10.3390/drones5030056 - 30 Jun 2021
Viewed by 615
Abstract
Distributed electric propulsion and boundary layer ingestion are two attractive technologies to reduce the power consumption of fixed wing aircraft. Through careful distribution of the propulsive system elements, higher aerodynamic and propulsive efficiency can be achieved, as well as a lower risk of [...] Read more.
Distributed electric propulsion and boundary layer ingestion are two attractive technologies to reduce the power consumption of fixed wing aircraft. Through careful distribution of the propulsive system elements, higher aerodynamic and propulsive efficiency can be achieved, as well as a lower risk of total loss of aircraft due to foreign object damage. When used on the wing, further reductions of the bending moment on the wing root can even lead to reductions of its structural weight, thus mitigating the expected increase of operating empty weight due to the extra components needed. While coupling these technologies in fixed-wing aircraft is being actively studied in the big aircraft segment, it is also an interesting approach for increasing the efficiency even for aircraft with maximum take-off masses as low as 25 kg, such as the A3 open subcategory for civil drones from EASA. This paper studies the effect of changing the propellers’ position in the aerodynamic performance parameters of a distributed electric propulsion with boundary layer ingestion system in a 25 kg fixed-wing aircraft, as well as in the performance of the propellers. The computational results show the trade-offs between the aerodynamic efficiency and the propeller efficiency when the vertical position is varied. Full article
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Article
A Multilevel Architecture for Autonomous UAVs
Drones 2021, 5(3), 55; https://doi.org/10.3390/drones5030055 - 30 Jun 2021
Viewed by 560
Abstract
In this paper, a multilevel architecture able to interface an on-board computer with a generic UAV flight controller and its radio receiver is proposed. The computer board exploits the same standard communication protocol of UAV flight controllers and can easily access additional data, [...] Read more.
In this paper, a multilevel architecture able to interface an on-board computer with a generic UAV flight controller and its radio receiver is proposed. The computer board exploits the same standard communication protocol of UAV flight controllers and can easily access additional data, such as: (i) inertial sensor measurements coming from a multi-sensor board; (ii) global navigation satellite system (GNSS) coordinates; (iii) streaming video from one or more cameras; and (iv) operator commands from the remote control. In specific operating scenarios, the proposed platform is able to act as a “cyber pilot” which replaces the role of a human UAV operator, thus simplifying the development of complex tasks such as those based on computer vision and artificial intelligence (AI) algorithms which are typically employed in autonomous flight operations. Full article
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Concept Paper
Unmanned Autogyro for Mars Exploration: A Preliminary Study
Drones 2021, 5(2), 53; https://doi.org/10.3390/drones5020053 - 18 Jun 2021
Viewed by 551
Abstract
Starting from the Martian environment, we examine all the necessary requirements for a UAV and outline the architecture of a gyroplane optimized for scientific research and support for (future) Mars explorers, highlighting its advantages and criticalities. After a careful trade-off between different vehicles [...] Read more.
Starting from the Martian environment, we examine all the necessary requirements for a UAV and outline the architecture of a gyroplane optimized for scientific research and support for (future) Mars explorers, highlighting its advantages and criticalities. After a careful trade-off between different vehicles suitable for a typical mission, some parameters are established to optimize the size and performance. In the second part, the project of the Spider gyroplane and the methodology used to balance the longitudinal masses are presented; in the third part, the parameters of the aerodynamic forces acting on the aircraft are highlighted to be able to focus them during the fluid dynamics simulations. Full article
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Article
Efficient Reactive Obstacle Avoidance Using Spirals for Escape
Drones 2021, 5(2), 51; https://doi.org/10.3390/drones5020051 - 07 Jun 2021
Viewed by 824
Abstract
The usage of unmanned aerial vehicles (UAV) has increased in recent years and new application scenarios have emerged. Some of them involve tasks that require a high degree of autonomy, leading to increasingly complex systems. In order for a robot to be autonomous, [...] Read more.
The usage of unmanned aerial vehicles (UAV) has increased in recent years and new application scenarios have emerged. Some of them involve tasks that require a high degree of autonomy, leading to increasingly complex systems. In order for a robot to be autonomous, it requires appropriate perception sensors that interpret the environment and enable the correct execution of the main task of mobile robotics: navigation. In the case of UAVs, flying at low altitude greatly increases the probability of encountering obstacles, so they need a fast, simple, and robust method of collision avoidance. This work covers the problem of navigation in unknown scenarios by implementing a simple, yet robust, environment-reactive approach. The implementation is done with both CPU and GPU map representations to allow wider coverage of possible applications. This method searches for obstacles that cross a cylindrical safety volume, and selects an escape point from a spiral for avoiding the obstacle. The algorithm is able to successfully navigate in complex scenarios, using both a high and low-power computer, typically found aboard UAVs, relying only on a depth camera with a limited FOV and range. Depending on the configuration, the algorithm can process point clouds at nearly 40 Hz in Jetson Nano, while checking for threats at 10 kHz. Some preliminary tests were conducted with real-world scenarios, showing both the advantages and limitations of CPU and GPU-based methodologies. Full article
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Article
On the Dominant Factors of Civilian-Use Drones: A Thorough Study and Analysis of Cross-Group Opinions Using a Triple Helix Model (THM) with the Analytic Hierarchy Process (AHP)
Drones 2021, 5(2), 46; https://doi.org/10.3390/drones5020046 - 26 May 2021
Viewed by 943
Abstract
This study explores the experts’ opinions during the consultation stage before law-making for civilian drones. A thorough literature study is first undertaken to have the set of influencing factors that should be suitable for the investigation from the perspective of designing and selecting [...] Read more.
This study explores the experts’ opinions during the consultation stage before law-making for civilian drones. A thorough literature study is first undertaken to have the set of influencing factors that should be suitable for the investigation from the perspective of designing and selecting civilian drones. Several rounds of surveys using the Delphi method, followed by an analytic hierarchy process (AHP), are performed to conform to the organized tree structure of constructs and factors and to obtain the knowledge about the opinions of the expert groups, with the expert sample being intentionally partitioned into three opinion groups at the beginning: academia (A), industry (I), and research institutes (R). Doing so facilitates a “mind-mining” process using the triple helix model (THM), while the opinions across the groups can also be visualized and compared. This exploits a new set of knowledge for the design and selection of civilian drones on a scientific yet empirical basis, and the observed differences and similarities among the groups may benefit their future negotiations to propose the drafts for regulating the design, manufacturing, and uses of civilian drones. As several significant implications and insights are also drawn and gained from the abovementioned results eventually, some possible research directions are worthwhile. The proposed hybrid methodological flow is another novelty. Full article
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Article
Monitoring Dynamic Braided River Habitats: Applicability and Efficacy of Aerial Photogrammetry from Manned Aircraft versus Unmanned Aerial Systems
Drones 2021, 5(2), 39; https://doi.org/10.3390/drones5020039 - 17 May 2021
Viewed by 927
Abstract
Despite growing interest in using lightweight unmanned aerial systems (UASs) for ecological research and conservation, review of the operational aspects of these evolving technologies is limited in the scientific literature. To derive an objective framework for choosing among technologies we calculated efficiency measures [...] Read more.
Despite growing interest in using lightweight unmanned aerial systems (UASs) for ecological research and conservation, review of the operational aspects of these evolving technologies is limited in the scientific literature. To derive an objective framework for choosing among technologies we calculated efficiency measures and conducted a data envelopment productivity frontier analysis (DEA) to compare the efficacy of using manned aircraft (Cessna with Aviatrix triggered image capture using a 50 mm lens) and UAS (Mavic Pro 2) for photogrammetric monitoring of restoration efforts in dynamic braided rivers in Southern New Zealand. Efficacy assessment was based on the technological, logistical, administrative, and economic requirements of pre (planning), peri (image acquiring) and post (image processing) phases. The results reveal that the technological and logistic aspects of UASs were more efficient than manned aircraft flights. Administratively, the first deployment of UASs is less efficient but was very flexible for subsequent deployment. Manned aircraft flights were more productive in terms of the number of acquired images, but the ground resolution of those images was lower compared with those from UASs. Frontier analysis confirmed that UASs would be economical for regular monitoring of habitats—and even more so if research personnel are trained to fly the UASs. Full article
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Article
Comparing UAS LiDAR and Structure-from-Motion Photogrammetry for Peatland Mapping and Virtual Reality (VR) Visualization
Drones 2021, 5(2), 36; https://doi.org/10.3390/drones5020036 - 09 May 2021
Cited by 2 | Viewed by 1114
Abstract
The mapping of peatland microtopography (e.g., hummocks and hollows) is key for understanding and modeling complex hydrological and biochemical processes. Here we compare unmanned aerial system (UAS) derived structure-from-motion (SfM) photogrammetry and LiDAR point clouds and digital surface models of an ombrotrophic bog, [...] Read more.
The mapping of peatland microtopography (e.g., hummocks and hollows) is key for understanding and modeling complex hydrological and biochemical processes. Here we compare unmanned aerial system (UAS) derived structure-from-motion (SfM) photogrammetry and LiDAR point clouds and digital surface models of an ombrotrophic bog, and we assess the utility of these technologies in terms of payload, efficiency, and end product quality (e.g., point density, microform representation, etc.). In addition, given their generally poor accessibility and fragility, peatlands provide an ideal model to test the usability of virtual reality (VR) and augmented reality (AR) visualizations. As an integrated system, the LiDAR implementation was found to be more straightforward, with fewer points of potential failure (e.g., hardware interactions). It was also more efficient for data collection (10 vs. 18 min for 1.17 ha) and produced considerably smaller file sizes (e.g., 51 MB vs. 1 GB). However, SfM provided higher spatial detail of the microforms due to its greater point density (570.4 vs. 19.4 pts/m2). Our VR/AR assessment revealed that the most immersive user experience was achieved from the Oculus Quest 2 compared to Google Cardboard VR viewers or mobile AR, showcasing the potential of VR for natural sciences in different environments. We expect VR implementations in environmental sciences to become more popular, as evaluations such as the one shown in our study are carried out for different ecosystems. Full article
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Article
UAV-Based Classification of Cercospora Leaf Spot Using RGB Images
Drones 2021, 5(2), 34; https://doi.org/10.3390/drones5020034 - 05 May 2021
Viewed by 916
Abstract
Plant diseases can impact crop yield. Thus, the detection of plant diseases using sensors that can be mounted on aerial vehicles is in the interest of farmers to support decision-making in integrated pest management and to breeders for selecting tolerant or resistant genotypes. [...] Read more.
Plant diseases can impact crop yield. Thus, the detection of plant diseases using sensors that can be mounted on aerial vehicles is in the interest of farmers to support decision-making in integrated pest management and to breeders for selecting tolerant or resistant genotypes. This paper investigated the detection of Cercospora leaf spot (CLS), caused by Cercospora beticola in sugar beet using RGB imagery. We proposed an approach to tackle the CLS detection problem using fully convolutional neural networks, which operate directly on RGB images captured by a UAV. This efficient approach does not require complex multi- or hyper-spectral sensors, but provides reliable results and high sensitivity. We provided a detection pipeline for pixel-wise semantic segmentation of CLS symptoms, healthy vegetation, and background so that our approach can automatically quantify the grade of infestation. We thoroughly evaluated our system using multiple UAV datasets recorded from different sugar beet trial fields. The dataset consisted of a training and a test dataset and originated from different fields. We used it to evaluate our approach under realistic conditions and analyzed its generalization capabilities to unseen environments. The obtained results correlated to visual estimation by human experts significantly. The presented study underlined the potential of high-resolution RGB imaging and convolutional neural networks for plant disease detection under field conditions. The demonstrated procedure is particularly interesting for applications under practical conditions, as no complex and cost-intensive measuring system is required. Full article
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Article
Communication Aware UAV Swarm Surveillance Based on Hierarchical Architecture
Drones 2021, 5(2), 33; https://doi.org/10.3390/drones5020033 - 30 Apr 2021
Cited by 1 | Viewed by 1005
Abstract
Multi-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science mission, modern warfare surveillance, and disaster rescuing. This paper proposes a decentralized UAV swarm persistent monitoring strategy in realizing continuous sensing coverage and network service. A two-layer (high altitude and low [...] Read more.
Multi-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science mission, modern warfare surveillance, and disaster rescuing. This paper proposes a decentralized UAV swarm persistent monitoring strategy in realizing continuous sensing coverage and network service. A two-layer (high altitude and low altitude) UAV teaming hierarchical structure is adopted in realizing the accurate object tracking in the area of interest (AOI). By introducing the UAV communication channel model in its path planning, both centralized and decentralized control schemes would be evaluated in the waypoint tracking simulation. The UAV swarm network service and object tracking are measured by metrics of communication link quality and waypoints tracking accuracy. UAV swarm network connectivity are evaluated over different aspects, such as stability and volatility. The comparison of proposed algorithms is presented with simulations. The result shows that the decentralized scheme outperforms the centralized scheme in the mission of persistent surveillance, especially on maintaining the stability of inner UAV swarm network while tracking moving objects. Full article
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Article
Assessing the Potential of Remotely-Sensed Drone Spectroscopy to Determine Live Coral Cover on Heron Reef
Drones 2021, 5(2), 29; https://doi.org/10.3390/drones5020029 - 17 Apr 2021
Viewed by 906
Abstract
Coral reefs, as biologically diverse ecosystems, hold significant ecological and economic value. With increased threats imposed on them, it is increasingly important to monitor reef health by developing accessible methods to quantify coral cover. Discriminating between substrate types has previously been achieved with [...] Read more.
Coral reefs, as biologically diverse ecosystems, hold significant ecological and economic value. With increased threats imposed on them, it is increasingly important to monitor reef health by developing accessible methods to quantify coral cover. Discriminating between substrate types has previously been achieved with in situ spectroscopy but has not been tested using drones. In this study, we test the ability of using point-based drone spectroscopy to determine substrate cover through spectral unmixing on a portion of Heron Reef, Australia. A spectral mixture analysis was conducted to separate the components contributing to spectral signatures obtained across the reef. The pure spectra used to unmix measured data include live coral, algae, sand, and rock, obtained from a public spectral library. These were able to account for over 82% of the spectral mixing captured in each spectroscopy measurement, highlighting the benefits of using a public database. The unmixing results were then compared to a categorical classification on an overlapping mosaicked drone image but yielded inconclusive results due to challenges in co-registration. This study uniquely showcases the potential of using commercial-grade drones and point spectroscopy in mapping complex environments. This can pave the way for future research, by increasing access to repeatable, effective, and affordable technology. Full article
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Article
Biomimetic Drones Inspired by Dragonflies Will Require a Systems Based Approach and Insights from Biology
Drones 2021, 5(2), 24; https://doi.org/10.3390/drones5020024 - 27 Mar 2021
Viewed by 2469
Abstract
Many drone platforms have matured to become nearly optimal flying machines with only modest improvements in efficiency possible. “Chimera” craft combine fixed wing and rotary wing characteristics while being substantially less efficient than both. The increasing presence of chimeras suggests that their mix [...] Read more.
Many drone platforms have matured to become nearly optimal flying machines with only modest improvements in efficiency possible. “Chimera” craft combine fixed wing and rotary wing characteristics while being substantially less efficient than both. The increasing presence of chimeras suggests that their mix of vertical takeoff, hover, and more efficient cruise is invaluable to many end users. We discuss the opportunity for flapping wing drones inspired by large insects to perform these mixed missions. Dragonflies particularly are capable of efficiency in all modes of flight. We will explore the fundamental principles of dragonfly flight to allow for a comparison between proposed flapping wing technological solutions and a flapping wing organism. We chart one approach to achieving the next step in drone technology through systems theory and an appreciation of how biomimetics can be applied. New findings in dynamics of flapping, practical actuation technology, wing design, and flight control are presented and connected. We show that a theoretical understanding of flight systems and an appreciation of the detail of biological implementations may be key to achieving an outcome that matches the performance of natural systems. We assert that an optimal flapping wing drone, capable of efficiency in all modes of flight with high performance upon demand, might look somewhat like an abstract dragonfly. Full article
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Technical Note
The Use of UAVs for the Characterization and Analysis of Rocky Coasts
Drones 2021, 5(1), 23; https://doi.org/10.3390/drones5010023 - 16 Mar 2021
Viewed by 1023
Abstract
Rocky coasts represent three quarters of all coastlines worldwide. These areas are part of ecosystems of great ecological value, but their steep configuration and their elevation make field surveys difficult. This fact, together with their lower variation rates, explains the lower numbers of [...] Read more.
Rocky coasts represent three quarters of all coastlines worldwide. These areas are part of ecosystems of great ecological value, but their steep configuration and their elevation make field surveys difficult. This fact, together with their lower variation rates, explains the lower numbers of publications about cliffs and rocky coasts in general compared with those about beach-dune systems. The introduction of UAVs in research, has enormously expanded the possibilities for the study of rocky coasts. Their relative low costs allow for the generation of information with a high level of detail. This information, combined with GIS tools, enables coastal analysis based on Digital Models and high spatial resolution images. This investigation summarizes the main results obtained with the help of UAVs between 2012 and the present day in rocky coastline sections in the northwest of the Iberian Peninsula. These investigations have particularly focused on monitoring the dynamics of boulder beaches, cliffs, and shore platforms, as well as the structure and function of ecosystems. This work demonstrates the importance of unmanned aerial vehicles (UAVs) for coastal studies and their usefulness for improving coastal management. The Galician case was used to explain their importance and the advances in the UAVs’ techniques. Full article
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Article
Modeling Streamflow and Sediment Loads with a Photogrammetrically Derived UAS Digital Terrain Model: Empirical Evaluation from a Fluvial Aggregate Excavation Operation
Drones 2021, 5(1), 20; https://doi.org/10.3390/drones5010020 - 12 Mar 2021
Viewed by 887
Abstract
Soil erosion monitoring is a pivotal exercise at macro through micro landscape levels, which directly informs environmental management at diverse spatial and temporal scales. The monitoring of soil erosion can be an arduous task when completed through ground-based surveys and there are uncertainties [...] Read more.
Soil erosion monitoring is a pivotal exercise at macro through micro landscape levels, which directly informs environmental management at diverse spatial and temporal scales. The monitoring of soil erosion can be an arduous task when completed through ground-based surveys and there are uncertainties associated with the use of large-scale medium resolution image-based digital elevation models for estimating erosion rates. LiDAR derived elevation models have proven effective in modeling erosion, but such data proves costly to obtain, process, and analyze. The proliferation of images and other geospatial datasets generated by unmanned aerial systems (UAS) is increasingly able to reveal additional nuances that traditional geospatial datasets were not able to obtain due to the former’s higher spatial resolution. This study evaluated the efficacy of a UAS derived digital terrain model (DTM) to estimate surface flow and sediment loading in a fluvial aggregate excavation operation in Waukesha County, Wisconsin. A nested scale distributed hydrologic flow and sediment loading model was constructed for the UAS point cloud derived DTM. To evaluate the effectiveness of flow and sediment loading generated by the UAS point cloud derived DTM, a LiDAR derived DTM was used for comparison in consonance with several statistical measures of model efficiency. Results demonstrate that the UAS derived DTM can be used in modeling flow and sediment erosion estimation across space in the absence of a LiDAR-based derived DTM. Full article
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Article
Safety Enhancement of UAVs from the Signal Processing’s Perspectives: A Bird’s Eye View
Drones 2021, 5(1), 16; https://doi.org/10.3390/drones5010016 - 26 Feb 2021
Viewed by 891
Abstract
Unmanned air vehicles (UAVs) or drones have gained popularity in recent years. However, the US Federal Aviation Administration (FAA) is still hesitant to open up the national air space (NAS) to UAVs due to safety concerns because UAVs have several orders of magnitude [...] Read more.
Unmanned air vehicles (UAVs) or drones have gained popularity in recent years. However, the US Federal Aviation Administration (FAA) is still hesitant to open up the national air space (NAS) to UAVs due to safety concerns because UAVs have several orders of magnitude of more accidents than manned aircraft. To limit the scope in this paper, we focus on large, heavy, and expensive UAVs that can be used for cargo transfer and search and rescue operations, not small radio-controlled toy drones. We first present a general architecture for enhancing the safety of UAVs. We then illustrate how signal processing technologies can help enhance the safety of UAVs. In particular, we provide a bird’s eye view of the application of signal processing algorithms on condition-based maintenance, structural health monitoring, fault diagnostics, and fault mitigation, which all play critical roles in UAV safety. Some practical applications are used to illustrate the importance of the various algorithms. Full article
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Article
Unmanned Aerial Vehicles for Wildland Fires: Sensing, Perception, Cooperation and Assistance
Drones 2021, 5(1), 15; https://doi.org/10.3390/drones5010015 - 22 Feb 2021
Cited by 2 | Viewed by 1447
Abstract
Wildfires represent a significant natural risk causing economic losses, human death and environmental damage. In recent years, the world has seen an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland fire assistance and [...] Read more.
Wildfires represent a significant natural risk causing economic losses, human death and environmental damage. In recent years, the world has seen an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland fire assistance and fighting. Systems were proposed for the remote detection and tracking of fires. These systems have shown improvements in the area of efficient data collection and fire characterization within small-scale environments. However, wildland fires cover large areas making some of the proposed ground-based systems unsuitable for optimal coverage. To tackle this limitation, unmanned aerial vehicles (UAV) and unmanned aerial systems (UAS) were proposed. UAVs have proven to be useful due to their maneuverability, allowing for the implementation of remote sensing, allocation strategies and task planning. They can provide a low-cost alternative for the prevention, detection and real-time support of firefighting. In this paper, previous works related to the use of UAV in wildland fires are reviewed. Onboard sensor instruments, fire perception algorithms and coordination strategies are considered. In addition, some of the recent frameworks proposing the use of both aerial vehicles and unmanned ground vehicles (UGV) for a more efficient wildland firefighting strategy at a larger scale are presented. Full article
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Article
StratoTrans: Unmanned Aerial System (UAS) 4G Communication Framework Applied on the Monitoring of Road Traffic and Linear Infrastructure
Drones 2021, 5(1), 10; https://doi.org/10.3390/drones5010010 - 28 Jan 2021
Viewed by 1419
Abstract
This study provides an operational solution to directly connect drones to internet by means of 4G telecommunications and exploit drone acquired data, including telemetry and imagery but focusing on video transmission. The novelty of this work is the application of 4G connection to [...] Read more.
This study provides an operational solution to directly connect drones to internet by means of 4G telecommunications and exploit drone acquired data, including telemetry and imagery but focusing on video transmission. The novelty of this work is the application of 4G connection to link the drone directly to a data server where video (in this case to monitor road traffic) and imagery (in the case of linear infrastructures) are processed. However, this framework is appliable to any other monitoring purpose where the goal is to send real-time video or imagery to the headquarters where the drone data is processed, analyzed, and exploited. We describe a general framework and analyze some key points, such as the hardware to use, the data stream, and the network coverage, but also the complete resulting implementation of the applied unmanned aerial system (UAS) communication system through a Virtual Private Network (VPN) featuring a long-range telemetry high-capacity video link (up to 15 Mbps, 720 p video at 30 fps with 250 ms of latency). The application results in the real-time exploitation of the video, obtaining key information for traffic managers such as vehicle tracking, vehicle classification, speed estimation, and roundabout in-out matrices. The imagery downloads and storage is also performed thorough internet, although the Structure from Motion postprocessing is not real-time due to photogrammetric workflows. In conclusion, we describe a real-case application of drone connection to internet thorough 4G network, but it can be adapted to other applications. Although 5G will -in time- surpass 4G capacities, the described framework can enhance drone performance and facilitate paths for upgrading the connection of on-board devices to the 5G network. Full article
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2020

Jump to: 2021

Article
Inter-UAV Routing Scheme Testbeds
Drones 2021, 5(1), 2; https://doi.org/10.3390/drones5010002 - 28 Dec 2020
Cited by 5 | Viewed by 1754
Abstract
With the development of more advanced and efficient control algorithms and communication architectures, UAVs and networks thereof (swarms) now find applications in nearly all possible environments and scenarios. There exist numerous schemes which accommodate routing for such networks, many of which are specifically [...] Read more.
With the development of more advanced and efficient control algorithms and communication architectures, UAVs and networks thereof (swarms) now find applications in nearly all possible environments and scenarios. There exist numerous schemes which accommodate routing for such networks, many of which are specifically designed for distinct use-cases. Validation and evaluation of routing schemes is implemented for the most part using simulation software. This approach is however incapable of considering real-life noise, radio propagation models, channel bit error rate and signal-to-noise ratio. Most importantly, existing frameworks or simulation software cannot sense physical-layer related information regarding power consumption which an increasing number of routing protocols utilize as a metric. The work presented in this paper contributes to the analysis of already existing routing scheme evaluation frameworks and testbeds and proposes an efficient, universal and standardized hardware testbed. Additionally, three interface modes aimed at evaluation under different scenarios are provided. Full article
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Article
Suitability of the Reforming-Controlled Compression Ignition Concept for UAV Applications
Drones 2020, 4(3), 60; https://doi.org/10.3390/drones4030060 - 22 Sep 2020
Viewed by 1419
Abstract
Reforming-controlled compression ignition (RefCCI) is a novel approach combining two methods to improve the internal combustion engine’s efficiency and mitigate emissions: low-temperature combustion (LTC) and thermochemical recuperation (TCR). Frequently, the combustion controllability challenge is resolved by simultaneous injection into the cylinder of two [...] Read more.
Reforming-controlled compression ignition (RefCCI) is a novel approach combining two methods to improve the internal combustion engine’s efficiency and mitigate emissions: low-temperature combustion (LTC) and thermochemical recuperation (TCR). Frequently, the combustion controllability challenge is resolved by simultaneous injection into the cylinder of two fuel types, each on the other edge of the reactivity scale. By changing the low-to-high-reactivity fuel ratio, ignition timing and combustion phasing control can be achieved. The RefCCI principles, benefits, and possible challenges are described in previous publications. However, the suitability of the RefCCI approach for aerial, mainly unmanned aerial vehicle (UAV) platforms has not been studied yet. The main goal of this paper is to examine whether the RefCCI approach can be beneficial for UAV, especially HALE (high-altitude long-endurance) applications. The thermodynamic first-law and the second-law analysis is numerically performed to investigate the RefCCI approach suitability for UAV applications and to assess possible efficiency gains. A comparison with the conventional diesel engine and the previously developed technology of spark ignition (SI) engine with high-pressure TCR is performed in view of UAV peculiarities. The results indicate that the RefCCI system can be beneficial for UAV applications. The RefCCI higher efficiency compared to existing commercial engines compensates the lower heating value of the primary fuel, so the fuel consumption remains almost the same. By optimizing the compression pressure ratio, the RefCCI system efficiency can be improved. Full article
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Article
Spray Deposition on Weeds (Palmer Amaranth and Morningglory) from a Remotely Piloted Aerial Application System and Backpack Sprayer
Drones 2020, 4(3), 59; https://doi.org/10.3390/drones4030059 - 19 Sep 2020
Viewed by 1551
Abstract
This study was designed to determine whether a remotely piloted aerial application system (RPAAS) could be used in lieu of a backpack sprayer for post-emergence herbicide application. Consequent to this objective, a spray mixture of tap water and fluorescent dye was applied on [...] Read more.
This study was designed to determine whether a remotely piloted aerial application system (RPAAS) could be used in lieu of a backpack sprayer for post-emergence herbicide application. Consequent to this objective, a spray mixture of tap water and fluorescent dye was applied on Palmer amaranth and ivyleaf morningglory using an RPAAS at 18.7 and 37.4 L·ha−1 and a CO2-pressurized backpack sprayer at a 140 L·ha−1 spray application rate. Spray efficiency (the proportion of applied spray collected on an artificial sampler) for the RPAAS treatments was comparable to that for the backpack sprayer. Fluorescent spray droplet density was significantly higher on the adaxial surface for the backpack sprayer treatment than that for the RPAAS platforms. The percent of spray droplets on the abaxial surface for the RPAAS aircraft at 37.4 L·ha−1 was 4-fold greater than that for the backpack sprayer at 140 L·ha−1. The increased spray deposition on the abaxial leaf surfaces was likely caused by rotor downwash and wind turbulence generated by the RPAAS which caused leaf fluttering. This improved spray deposition may help increase the efficacy of contact herbicides. Test results indicated that RPAASs may be used for herbicide application in lieu of conventional backpack sprayers. Full article
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Article
An Approach for Route Optimization in Applications of Precision Agriculture Using UAVs
Drones 2020, 4(3), 58; https://doi.org/10.3390/drones4030058 - 18 Sep 2020
Cited by 4 | Viewed by 2066
Abstract
This research paper focuses on providing an algorithm by which (Unmanned Aerial Vehicles) UAVs can be used to provide optimal routes for agricultural applications such as, fertilizers and pesticide spray, in crop fields. To utilize a minimum amount of inputs and complete the [...] Read more.
This research paper focuses on providing an algorithm by which (Unmanned Aerial Vehicles) UAVs can be used to provide optimal routes for agricultural applications such as, fertilizers and pesticide spray, in crop fields. To utilize a minimum amount of inputs and complete the task without a revisit, one needs to employ optimized routes and optimal points of delivering the inputs required in precision agriculture (PA). First, stressed regions are identified using VegNet (Vegetative Network) software. Then, methods are applied for obtaining optimal routes and points for the spraying of inputs with an autonomous UAV for PA. This paper reports a unique and innovative technique to calculate the optimum location of spray points required for a particular stressed region. In this technique, the stressed regions are divided into many circular divisions with its center being a spray point of the stressed region. These circular divisions would ensure a more effective dispersion of the spray. Then an optimal path is found out which connects all the stressed regions and their spray points. The paper also describes the use of methods and algorithms including travelling salesman problem (TSP)-based route planning and a Voronoi diagram which allows applying precision agriculture techniques. Full article
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Article
High Resolution Geospatial Evapotranspiration Mapping of Irrigated Field Crops Using Multispectral and Thermal Infrared Imagery with METRIC Energy Balance Model
Drones 2020, 4(3), 52; https://doi.org/10.3390/drones4030052 - 01 Sep 2020
Cited by 5 | Viewed by 1528
Abstract
Geospatial crop water use mapping is critical for field-scale site-specific irrigation management. Landsat 7/8 satellite imagery with a widely adopted METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) energy balance model (LM approach) estimates accurate evapotranspiration (ET) but limits field-scale spatiotemporal (30 [...] Read more.
Geospatial crop water use mapping is critical for field-scale site-specific irrigation management. Landsat 7/8 satellite imagery with a widely adopted METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) energy balance model (LM approach) estimates accurate evapotranspiration (ET) but limits field-scale spatiotemporal (30 m pixel−1, ~16 days) mapping. A study was therefore conducted to map actual ET of commercially grown irrigated-field crops (spearmint, potato, and alfalfa) at very high-resolution (7 cm pixel−1). Six small unmanned aerial system (UAS)-based multispectral and thermal infrared imagery campaigns were conducted (two for each crop) at the same time as the Landsat 7/8 overpass. Three variants of METRIC model were used to process the UAS imagery; UAS-METRIC-1, -2, and -3 (UASM-1, -2, and -3) and outputs were compared with the standard LM approach. ET root mean square differences (RMSD) between LM-UASM-1, LM-UASM-2, and LM-UASM-3 were in the ranges of 0.2–2.9, 0.5–0.9, and 0.5–2.7 mm day−1, respectively. Internal calibrations and sensible heat fluxes majorly resulted in such differences. UASM-2 had the highest similarity with the LM approach (RMSD: 0.5–0.9, ETdep,abs (daily ET departures): 2–14%, r (Pearson correlation coefficient) = 0.91). Strong ET correlations between UASM and LM approaches (0.7–0.8, 0.7–0.8, and 0.8–0.9 for spearmint, potato, and alfalfa crops) suggest equal suitability of UASM approaches as LM to map ET for a range of similar crops. UASM approaches (Coefficient of variation, CV: 6.7–24.3%) however outperformed the LM approach (CV: 2.1–11.2%) in mapping spatial ET variations due to large number of pixels. On-demand UAS imagery may thus help in deriving high resolution site-specific ET maps, for growers to aid in timely crop water management. Full article
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Article
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
Drones 2020, 4(3), 49; https://doi.org/10.3390/drones4030049 - 27 Aug 2020
Cited by 4 | Viewed by 1602
Abstract
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 [...] Read more.
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. Full article
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Article
Ice Detection on Aircraft Surface Using Machine Learning Approaches Based on Hyperspectral and Multispectral Images
Drones 2020, 4(3), 45; https://doi.org/10.3390/drones4030045 - 18 Aug 2020
Viewed by 1454
Abstract
Aircraft ground de-icing operations play a critical role in flight safety. However, to handle the aircraft de-icing, a considerable quantity of de-icing fluids is commonly employed. Moreover, some pre-flight inspections are carried out with engines running; thus, a large amount of fuel is [...] Read more.
Aircraft ground de-icing operations play a critical role in flight safety. However, to handle the aircraft de-icing, a considerable quantity of de-icing fluids is commonly employed. Moreover, some pre-flight inspections are carried out with engines running; thus, a large amount of fuel is wasted, and CO2 is emitted. This implies substantial economic and environmental impacts. In this context, the European project (reference call: MANUNET III 2018, project code: MNET18/ICT-3438) called SEI (Spectral Evidence of Ice) aims to provide innovative tools to identify the ice on aircraft and improve the efficiency of the de-icing process. The project includes the design of a low-cost UAV (uncrewed aerial vehicle) platform and the development of a quasi-real-time ice detection methodology to ensure a faster and semi-automatic activity with a reduction of applied operating time and de-icing fluids. The purpose of this work, developed within the activities of the project, is defining and testing the most suitable sensor using a radiometric approach and machine learning algorithms. The adopted methodology consists of classifying ice through spectral imagery collected by two different sensors: multispectral and hyperspectral camera. Since the UAV prototype is under construction, the experimental analysis was performed with a simulation dataset acquired on the ground. The comparison among the two approaches, and their related algorithms (random forest and support vector machine) for image processing, was presented: practical results show that it is possible to identify the ice in both cases. Nonetheless, the hyperspectral camera guarantees a more reliable solution reaching a higher level of accuracy of classified iced surfaces. Full article
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Article
Modeling and Investigations on Surface Colors of Wings on the Performance of Albatross-Inspired Mars Drones and Thermoelectric Generation Capabilities
Drones 2020, 4(3), 43; https://doi.org/10.3390/drones4030043 - 16 Aug 2020
Viewed by 1041
Abstract
Thermal effects of wing color for Albatross-inspired drones performing in the Martian atmosphere are investigated during the summer and winter seasons. This study focuses on two useful consequences of the thermal effects of wing color: the drag reduction and the thermoelectric generation of [...] Read more.
Thermal effects of wing color for Albatross-inspired drones performing in the Martian atmosphere are investigated during the summer and winter seasons. This study focuses on two useful consequences of the thermal effects of wing color: the drag reduction and the thermoelectric generation of power. According to its color, each wing side has a certain temperature affecting the drag. Investigations of various configurations have shown that the thermal effect on the wing boundary layer skin drag is insignificant because of the low atmospheric pressure. However, the total drag varies as much as 12.8% between the highest performing wing color configuration and the lowest performing configuration. Additionally, the large temperature differences between the top and the bottom wing surfaces show great potential for thermoelectric power generation. The maximum temperature differences between the top and bottom surfaces for the summer and winter seasons are, respectively, 65 K and 30 K. The drag reduction and the power generation via thermoelectric generators both contribute to enhancing the endurance of drones. Future drone designs will benefit from increased endurance through optimizing the wing color configuration. Full article
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Technical Note
Temperature Profiling of Waterbodies with a UAV-Integrated Sensor Subsystem
Drones 2020, 4(3), 35; https://doi.org/10.3390/drones4030035 - 21 Jul 2020
Cited by 1 | Viewed by 1126
Abstract
Evaluation of thermal stratification and systematic monitoring of water temperature are required for lake management. Water temperature profiling requires temperature measurements through a water column to assess the level of thermal stratification which impacts oxygen content, microbial growth, and distribution of fish. The [...] Read more.
Evaluation of thermal stratification and systematic monitoring of water temperature are required for lake management. Water temperature profiling requires temperature measurements through a water column to assess the level of thermal stratification which impacts oxygen content, microbial growth, and distribution of fish. The objective of this research was to develop and assess the functions of a water temperature profiling system mounted on a multirotor unmanned aerial vehicle (UAV). The buoyancy apparatus mounted on the UAV allowed vertical takeoff and landing on the water surface for in situ measurements. The sensor node that was integrated with the UAV consisted of a microcontroller unit, a temperature sensor, and a pressure sensor. The system measured water temperature and depth from seven pre-selected locations in a lake using autonomous navigation with autopilot control. Measurements at 100 ms intervals were made while the UAV was descending at 2 m/s until it landed on water surface. Water temperature maps of three consecutive depths at each location were created from the measurements. The average surface water temperature at 0.3 m was 22.5 °C, while the average water temperature at 4 m depth was 21.5 °C. The UAV-based profiling system developed successfully performed autonomous water temperature measurements within a lake. Full article
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Article
Vegetation Extraction Using Visible-Bands from Openly Licensed Unmanned Aerial Vehicle Imagery
Drones 2020, 4(2), 27; https://doi.org/10.3390/drones4020027 - 26 Jun 2020
Cited by 5 | Viewed by 2798
Abstract
Red–green–blue (RGB) cameras which are attached in commercial unmanned aerial vehicles (UAVs) can support remote-observation small-scale campaigns, by mapping, within a few centimeter’s accuracy, an area of interest. Vegetated areas need to be identified either for masking purposes (e.g., to exclude vegetated areas [...] Read more.
Red–green–blue (RGB) cameras which are attached in commercial unmanned aerial vehicles (UAVs) can support remote-observation small-scale campaigns, by mapping, within a few centimeter’s accuracy, an area of interest. Vegetated areas need to be identified either for masking purposes (e.g., to exclude vegetated areas for the production of a digital elevation model (DEM) or for monitoring vegetation anomalies, especially for precision agriculture applications. However, while detection of vegetated areas is of great importance for several UAV remote sensing applications, this type of processing can be quite challenging. Usually, healthy vegetation can be extracted at the near-infrared part of the spectrum (approximately between 760–900 nm), which is not captured by the visible (RGB) cameras. In this study, we explore several visible (RGB) vegetation indices in different environments using various UAV sensors and cameras to validate their performance. For this purposes, openly licensed unmanned aerial vehicle (UAV) imagery has been downloaded “as is” and analyzed. The overall results are presented in the study. As it was found, the green leaf index (GLI) was able to provide the optimum results for all case studies. Full article
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Article
Deep Learning Classification of 2D Orthomosaic Images and 3D Point Clouds for Post-Event Structural Damage Assessment
Drones 2020, 4(2), 24; https://doi.org/10.3390/drones4020024 - 22 Jun 2020
Cited by 5 | Viewed by 1632
Abstract
Efficient and rapid data collection techniques are necessary to obtain transitory information in the aftermath of natural hazards, which is not only useful for post-event management and planning, but also for post-event structural damage assessment. Aerial imaging from unpiloted (gender-neutral, but also known [...] Read more.
Efficient and rapid data collection techniques are necessary to obtain transitory information in the aftermath of natural hazards, which is not only useful for post-event management and planning, but also for post-event structural damage assessment. Aerial imaging from unpiloted (gender-neutral, but also known as unmanned) aerial systems (UASs) or drones permits highly detailed site characterization, in particular in the aftermath of extreme events with minimal ground support, to document current conditions of the region of interest. However, aerial imaging results in a massive amount of data in the form of two-dimensional (2D) orthomosaic images and three-dimensional (3D) point clouds. Both types of datasets require effective and efficient data processing workflows to identify various damage states of structures. This manuscript aims to introduce two deep learning models based on both 2D and 3D convolutional neural networks to process the orthomosaic images and point clouds, for post windstorm classification. In detail, 2D convolutional neural networks (2D CNN) are developed based on transfer learning from two well-known networks AlexNet and VGGNet. In contrast, a 3D fully convolutional network (3DFCN) with skip connections was developed and trained based on the available point cloud data. Within this study, the datasets were created based on data from the aftermath of Hurricanes Harvey (Texas) and Maria (Puerto Rico). The developed 2DCNN and 3DFCN models were compared quantitatively based on the performance measures, and it was observed that the 3DFCN was more robust in detecting the various classes. This demonstrates the value and importance of 3D datasets, particularly the depth information, to distinguish between instances that represent different damage states in structures. Full article
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