Authors:Marc-Antoine Leclerc, John Bass, Mathieu Labbé, David Dozois, Jonathan Delisle, David Rancourt, Alexis Lussier Desbiens Pages: 1 - 17 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-17, January 2023. Underground stope mapping is crucial to evaluate the quantity of blasted rock and the site integrity. In recent years, lidar-equipped drones have been used to map stopes with higher precision and without blind spots. However, they have limitations, such as large size, challenging lidar positioning on the drone, limited flight time for detailed visual inspections, and unreliable communication underground. This paper discusses the development of a compact tethered drone called the NetherDrone, specifically designed for stope inspections. The NetherDrone uses custom ducted propulsion to increase thrust efficiency by 50%. It reduces the propellers’ diameter and overall frame while maintaining an adequate lifting capability with low power consumption. The drone features an onboard 120 m tether spool for communication and power transmission, as well as a rotating arm to deploy the cable and reduce yaw moments from the tether tension. Flights in a real stope demonstrated that the drone could effectively move at least 50 m deep into a complex stope, complete a detailed lidar scan, visually scan one face of the stope in close proximity during 20 min, travel a total distance of 270 m, and maintain communications with an operator at all times through the tether. Citation: Drone Systems and Applications PubDate: 2023-09-01T07:00:00Z DOI: 10.1139/dsa-2023-0001 Issue No:Vol. 11 (2023)
Authors:Matthew Palmer, Jeremy Laliberte Pages: 1 - 11 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-11, January 2023. Propeller parameters and geometry can dramatically influence the performance of a drone and its ability to complete a mission. Though many off-the-shelf propeller choices exist, operators in the field may not be able to stock suitable options for any possible scenario and are often forced to fly with a suboptimal propeller. Modern desktop 3D printers are relatively portable, highly capable, and simple to operate, offering the chance to rapidly manufacture propellers tailored to specific missions. This research evaluates how two recent advances in fused filament fabrication 3D printing could affect the mechanical viability of printed propellers. Non-planar slicing is a model slicing technique that attempts to address roughness issues when printing the shallow three-dimensional curvature found on many propeller blades. For further improvement, polymer filaments with short-chopped carbon fibre additives were compared against their fibre-free counterparts. Test coupons were subjected to tests simulating the thrust and impact loads a propeller might experience during flight. Under thrust loading, the material with carbon fibre additives showed a significant performance advantage. During impact tests, both nonplanar slicing (65% average improvement) and carbon fibre material additives (20% average improvement) demonstrated performance gains over their more traditional counterparts. Citation: Drone Systems and Applications PubDate: 2023-08-08T07:00:00Z DOI: 10.1139/dsa-2023-0007 Issue No:Vol. 11 (2023)
Authors:Abhishek Phadke, Josh Boyd, F. Antonio Medrano, Michael Starek Pages: 1 - 4 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-4, January 2023. As technology and innovations in unmanned aerial vehicles progress, so does the need for regulations in place to create safe and controlled flying scenarios. The Federal Aviation Administration (FAA) is a governing body under the United States Department of Transportation that is responsible for a wide range of regulatory activities related to the United States airspace. In a recently published final rule, the FAA addresses several concerns such as the need for a system to identify all aircrafts flying in national airspace, as well as the implementation of a separate system from the prevalent Automatic Dependent Surveillance–Broadcast system to prevent interference with manned aircrafts. Their solution to these concerns is the deployment of remote identification (RID) on all unmanned aircraft systems (UAS) flying under its implied jurisdiction. While US governing agencies retain the use of the word UAS for now, the International Civil Aviation Organization terminology is remotely piloted aircraft systems. The FAA describes the RID implementation as a “Digital license plate” for all UAS flying in the United States airspace. They outline additional policies including several options for compliance, operating rules, and design and production guidelines for manufacturers. As the September 2023 deadline for compliance draws near, this article highlights possible deployment applications and challenges. Citation: Drone Systems and Applications PubDate: 2023-08-01T07:00:00Z DOI: 10.1139/dsa-2023-0029 Issue No:Vol. 11 (2023)
Authors:Majd Saied, Mohammad Kassem, Hussein Mazeh, Hassan Shraim, Clovis Francis Pages: 1 - 10 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-10, January 2023. Although important improvements in the area of robust control of nonlinear systems have been presented in the literature, most of the developed controllers suffer from complexity and large dependency on accurate mathematical formulation of the models. Recently, model-free robust control techniques were introduced and have shown good performance when applied to multi-input–multi-output systems. The model-free approach is characterized by the nonuse of any prior knowledge about the underlying structure and/or associated parameters of the dynamical system. Therefore, the major criteria for assessing the effectiveness of these controllers are related to their ability to handle unknown inputs and disturbances, as well as achieving the desired tracking performance in presence of faults and malfunctions. This work considers the development of robust fault-tolerant controllers based on the model-free approach and their application to multirotor unmanned aerial vehicles’ (UAVs) systems. The different controllers based on intelligent proportional-derivative (iPD), intelligent backstepping (iBackstepping), and adaptive control are compared in terms of performance, ease of implementation and parameters tuning. The simulated results, tested on Matlab/Simulink on a full nonlinear model of a hexarotor UAV, validate the theoretical advantages of the adaptive approach with respect to multiple criteria such as improved tracking performance in case of existence of actuators faults when compared to the iPD and iBackstepping control methods at the cost of increased complexity. Citation: Drone Systems and Applications PubDate: 2023-06-15T07:00:00Z DOI: 10.1139/dsa-2022-0048 Issue No:Vol. 11 (2023)
Authors:Iben Fasterholdt, Mette Præst Knudsen, Nicolai From, Marianne Harbo Frederiksen Pages: 1 - 8 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-8, January 2023. Drones are expected to become widespread in society, making public readiness an important prerequisite for successfully unleashing them. This article investigates Danish citizens’ opinions on drones across varying fields of application and, specifically, six potential cases of healthcare logistics. Survey data representative of age, gender, and geography were collected and included information about respondents’ background, knowledge level of drones, and opinions on different drone use cases. Data were analysed with frequency tables and bivariate cross-tabulation. A thousand and four Danish adults completed the survey. Although other fields of application received higher levels of support, a majority of the respondents were positive towards using drones for healthcare logistics. Transportation of medicine and blood samples between hospitals were the most accepted healthcare use cases. Support varies across age with the highest support found in the eldest age group. Also, the more citizens report to know about drones, the more they tend to support using them. The results suggest that policymakers and firms must be attentive towards the public opinion on drones and seek insights into what citizens regard as noble purposes of using drones. Moreover, citizens must become more acquainted with drones, as this will likely boost public support. Citation: Drone Systems and Applications PubDate: 2023-06-07T07:00:00Z DOI: 10.1139/dsa-2022-0050 Issue No:Vol. 11 (2023)
Authors:Chiaki Yamato, Tomoichiro Tanaka, Kotaro Ichikawa, Takuya Sato Pages: 1 - 10 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-10, January 2023. Monitoring the movement of small animals is a fundamental aspect of ecological studies as well as spatially explicit conservation and management. However, this remains a challenging task especially in mountainous terrains. Although drone-based radiotelemetry (DRT) is employed to localize animals, its application in mountainous terrains is limited by the collision risks associated with undulating terrains as well as the obstruction of signals by dense vegetation and steep slopes. We addressed these challenges by generating fine-scale three-dimensional maps and moving vertically mounted directional antennas in a double grid pattern, scanning both in longitudinal and latitudinal grids. This new DRT system was helpful in localizing four adult Japanese toads (Bufo japonicus) living in hiding places typical of mountainous terrains. All toads were located within 1–60 days of being released. Transmitter signals were detected within two consecutive flights (three flights in one case). Instances of transmitter detection were significantly biased when the drone was facing either direction of the double-grid path, indicating that the double-grid pattern had reduced detection failure. The absolute localization error (n = 48) of 22.4 ± 21.0 m (44.8 ± 42% of the transmitter-to-receiver distance) was lower than that reported in a previous study conducted in a similar mountainous terrain. Citation: Drone Systems and Applications PubDate: 2023-06-07T07:00:00Z DOI: 10.1139/dsa-2022-0060 Issue No:Vol. 11 (2023)
Authors:Glenn Slade, Dominic Fawcett, Andrew M. Cunliffe, Richard E. Brazier, Kamal Nyaupane, Marguerite Mauritz, Sergio Vargas, Karen Anderson Pages: 1 - 20 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-20, January 2023. Drone-based multispectral sensing is a valuable tool for dryland spatial ecology, yet there has been limited investigation of the reproducibility of measurements from drone-mounted multispectral camera array systems or the intercomparison between drone-derived measurements, field spectroscopy, and satellite data. Using radiometrically calibrated data from two multispectral drone sensors (MicaSense RedEdge (MRE) and Parrot Sequoia (PS)) co-located with a transect of hyperspectral measurements (tramway) in the Chihuahuan desert (New Mexico, USA), we found a high degree of correspondence within individual drone data sets, but that reflectance measurements and vegetation indices varied between field, drone, and satellite sensors. In comparison to field spectra, MRE had a negative bias, while PS had a positive bias. In comparison to Sentinel-2, PS showed the best agreement, while MRE had a negative bias for all bands. A variogram analysis of NDVI showed that ecological pattern information was lost at grains coarser than 1.8 m, indicating that drone-based multispectral sensors provide information at an appropriate spatial grain to capture the heterogeneity and spectral variability of this dryland ecosystem in a dry season state. Investigators using similar workflows should understand the need to account for biases between sensors. Modelling spatial and spectral upscaling between drone and satellite data remains an important research priority. Citation: Drone Systems and Applications PubDate: 2023-06-06T07:00:00Z DOI: 10.1139/dsa-2023-0003 Issue No:Vol. 11 (2023)
Authors:Tabitha W. Olsen, Trey Barron, Christopher J. Butler Pages: 1 - 9 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-9, January 2023. Rails are a highly secretive group of marshland obligate species that are difficult to consistently survey and detect. Current survey efforts utilize either call–playback or autonomous recording devices, but the low detection probabilities for rails create challenges for long-term systematic monitoring. Between 8 April and 16 May 2022, we flew a small aerial drone equipped with a thermal camera to survey for six species of rail (Black Rail (Laterallus jamaicensis), Yellow Rail (Coturnicops noveboracensis), Sora (Porzana carolina), Virginia Rail (Rallus limicola), Clapper Rail (Rallus crepitans), and King Rail (Rallus elegans)) along the Gulf Coast of Texas to assess the feasibility of long-term drone monitoring. We successfully conducted 33 flights at 15 m above ground level and detected rails on the first visit at 42% of known occupied points. We achieved 27 total rail detections, including 12 Black Rail/Yellow Rail detections. Of the birds detected, 81% exhibited no response to the drone’s first approach. We intend for this preliminary data to shape future survey protocol for secretive species occupying difficult to navigate terrain. Citation: Drone Systems and Applications PubDate: 2023-05-26T07:00:00Z DOI: 10.1139/dsa-2022-0046 Issue No:Vol. 11 (2023)
Authors:José P. Sibaja-Brenes, Akihiko Terada, Rosa Alfaro Solís, Mario Cambronero Luna, Danilo Umaña Castro, Daniel Porras Ramírez, Rolando Sánchez Gutiérrez, Mariela Martínez Arroyo, Ian Godfrey, María Martínez Cruz Pages: 1 - 14 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-14, January 2023. For the first time ever, samples were collected from volcanic lake waters in Costa Rica using an unmanned aerial vehicle (drone), which represents a major achievement in human–machine interaction and innovation in the technology sector. A Matrice 600 Pro drone was used for remote sampling in the hyperacid crater lake of the Poás volcano, the mildly acidic Lake Botos, and the nearly neutral Lake Hule. A bailer bottle of 250 mL and a HOBO temperature probe, mounted on the drone, were deployed using a specially designed delivery retrieval system. A comparison was carried out relating to the geochemistry of lake water collected by drone as opposed to the hand-collected samples. The SO4−2/Cl ratios of the two samples at Poás hyperacid crater lake were similar, (1.1 ± 0.2) on average, an indication of a lake with homogenous water composition. The Lake Hule showed a similar composition to that registered 20 years ago. The waters from Lake Botos showed some differences, which may be explained by the influence of springs at the bottom of the lake, but the Wilcoxon's signed-rank test showed a good exhibit of a satisfactory level of similarity. Autonomous navigation proves to be very useful for faster, more efficient, reliable, and less hazardous sampling of volcanic lakes. Citation: Drone Systems and Applications PubDate: 2023-05-17T07:00:00Z DOI: 10.1139/dsa-2022-0023 Issue No:Vol. 11 (2023)
Authors:Ryan Ward, Brett Readman, Brennan O’Yeung, W. Schuyler Hinman Pages: 1 - 16 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-16, January 2023. In this study, a methodology for the high-level conceptual design, optimization, and evaluation of amphibious remotely piloted and autonomous fixed-wing aircraft to support wildfire air attack strategies is presented. Of particular interest are questions of scale, water source utilization, and optimization of high-level aircraft parameters in a regional context. The Canadian province of British Columbia is used as a case study due to the relevance of wildfire control in that region. The present strategy incorporates a detailed analysis of available water bodies, tanker base locations, and their distance from historical wildfire locations and explores how these regionally specific details impact optimal aircraft design parameters. Results are obtained for optimal lake size as well as the primary design characteristics of the corresponding optimal aircraft. Two filling strategies are evaluated, namely, a “stop-and-go” strategy and a traditional skimming strategy. The results indicate the potential of fleets of optimized aircraft to supply high flow rates while capitalizing on the established benefits of using remotely piloted and autonomous systems. It is hoped this work will encourage future study into improved models and the further development of drone technology for this application, including necessary beyond visual line-of-sight technology and infrastructure. Citation: Drone Systems and Applications PubDate: 2023-05-16T07:00:00Z DOI: 10.1139/dsa-2022-0051 Issue No:Vol. 11 (2023)
Authors:Farrukh Javed, Humayun Zubair Khan, Raheel Anjum Pages: 1 - 12 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-12, January 2023. Employment of unmanned aerial vehicles (UAVs) or drones as swarms of coordinating nodes offers multiple advantages for commercial as well as military applications. However, the complex communication requirements of these swarms, coupled with high data rates of advanced UAV payloads, require innovative techniques for optimizing data throughput. Channel capacity being the key resource, optimum communication architecture and network topology is critical to ensure quality of service while remaining within transmission power constraints. This paper proposes a capacity maximization approach for swarm communication architectures using mixed-integer nonlinear programming (MINLP). These techniques are designed to tackle optimization applications involving both discrete variables and nonlinear system dynamics. Mathematical model formulated considering system constraints and desired objective function establishes applicability of MINLP. Since MINLP problems are NP-hard in general, computational overheads and search space exponentially grow with number of nodes in the swarm. Therefore, outer approximation algorithm has been applied that achieves near-optimal solutions with reduced convergence time and complexity compared with exhaustive search. Applicability of algorithm regardless of selected communication architecture has been established through realistic simulations. Citation: Drone Systems and Applications PubDate: 2023-05-05T07:00:00Z DOI: 10.1139/dsa-2023-0002 Issue No:Vol. 11 (2023)
Authors:Prashant Kumar, Bisheswar Choudhury, Amandeep Singh, Janakarajan Ramkumar, Deepu Philip, Ajoy Kanti Ghosh Pages: 1 - 16 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-16, January 2023. This study proposes a framework for developing a realistic model for throttle and servo control algorithms for a powered parafoil unmanned aerial vehicle (PPUAV) using artificial neural networks (ANNs). Two servo motors on an L-shaped platform, control and steer the PPUAV. Six degrees of freedom mathematical model of a dynamic parafoil system is built to test the technique's efficacy using a simulation in which disturbances mimic actual flights. A guiding law is then established, including the cross-track error and the line-of-sight approach. Furthermore, a path-following controller is constructed using the proportional-integral derivative, and a simulation platform was created to evaluate numerical data illustrating the route's validity following the technique. PPUAV was developed, built, and instrumented to collect real-time flight data to test the controller. These dynamic characteristics were sent into the ANN for training. A diverging-converging design was identified to obtain the best consistency between predicted and observed throttle and servo control values. For a comparable flight route, the control signal of the simulated model is compared with those of the actual and ANN-predicted models. The comparative findings show that the ANN-predicted and actual control inputs were almost identical, with an 80%–99% match. However, the simulated response showed deviation from the actual control input, with an accuracy of 50%–80%. Citation: Drone Systems and Applications PubDate: 2023-05-04T07:00:00Z DOI: 10.1139/dsa-2022-0040 Issue No:Vol. 11 (2023)
Authors:Karen Anderson, Brandi M. Shabaga, Serge Wich, Geoff Fink, Martin Barczyk, Jarrod Hodgson, Dominique Chabot Pages: 1 - 7 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-7, January 2023. Summary This journal (Drone Systems and Applications; DSA) conducted a targeted “horizon scan” during 2022 within our team of editors and associate editors. We asked—Which research areas currently under-represented in Drone Systems and Applications would you like to see more heavily represented in the future' The process highlighted five areas of interest and potential growth: Drones in the geosciences Aquatic drones Ground drones Drones within calibration/validation experiments Drones and computer vision Over the past two years (2020–22), the journal has published over 50 papers with a strong leaning towards aerial drones for ecology and also with an engineering focus. DSA is keen to receive new submissions addressing the five highlighted areas, which lie firmly within the aims and scope of the journal. Further to the horizon scan, we propose two special collections for the coming year—one addressing drone applications (drones in geoscience applications) and a second addressing drone systems (aquatic drone systems). We would like to hear from scientists and practitioners in these fields as both contributors and (or) collection editors. Citation: Drone Systems and Applications PubDate: 2023-04-26T07:00:00Z DOI: 10.1139/dsa-2023-0019 Issue No:Vol. 11 (2023)
Authors:Kusal B. Tennakoon, Oscar De Silva, Awantha Jayasiri, George K.I. Mann, Raymond G. Gosine Pages: 1 - 19 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-19, January 2023. This article proposes a mobile robot localization system developed using Google Indoor Street View (GISV) and Convolutional Neural Network (CNN)-based visual place recognition. The proposed localization system consists of two main modules. The first is a place recognition module based on GISV and a net Vector of Locally Aggregated Descriptors (VLAD)-based CNN. The second is a factor graph-based optimization module. In this work, we show that a CNN-based approach can be utilized to overcome the lack of visually distinct features in indoor environments and changes in images that can occur when using different cameras at different points in time for localization. The proposed CNN-based localization system is implemented using reference and query images obtained from two different sources (GISV and a camera attached to a mobile robot). It has been experimentally validated using a custom indoor dataset captured at the Memorial University of Newfoundland engineering building basement. The main results of this paper show that GISV-based place recognition reduces the percentage drift by 4% for the dataset and achieves a Root Mean Square Error (RMSE) of 2 m for position and 2.5° for orientation. Citation: Drone Systems and Applications PubDate: 2023-03-20T07:00:00Z DOI: 10.1139/dsa-2022-0045 Issue No:Vol. 11 (2023)
Authors:Leo Scicluna, Tonio Sant, Robert N. Farrugia Pages: 1 - 17 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-17, January 2023. The aim of this research was to establish the validity of wind measurements from on board a multirotor Remotely Piloted Aircraft System (RPAS) for the purposes of wind monitoring applications. A custom-built hexacopter RPAS recorded wind speed and direction by means of an onboard ultrasonic wind sensor, whilst operating in the inherently highly stochastic nature of open field atmospheric conditions. Experimental data were collected during open field hovering flights subject to different ambient conditions with free stream horizontal wind speeds reaching up to 12 m/s. Flights were conducted at different altitudes above ground level and in proximity to a Light Detection and Ranging (LiDAR) remote wind measurement unit that was used as a low-resolution reference meteorological station. Very good correlation was obtained between the RPAS and LiDAR unit for both wind speed and wind direction measurements across all hovering flight altitudes. The RPAS-based wind speed measurements were found to have a consistent 1 m/s positive offset, whilst the RPAS-based wind direction readings had a 6.16° negative offset. These were potentially caused by differences in the localized wind fields between the LiDAR and RPAS measuring positions, as well as by localized RPAS rotor-induced air flows for wind speed measurements and potential slight misalignments in the instruments’ reference datum for wind direction readings. Citation: Drone Systems and Applications PubDate: 2023-03-02T08:00:00Z DOI: 10.1139/dsa-2022-0034 Issue No:Vol. 11 (2023)
Authors:Hirad Goudarzi, Arthur Richards Pages: 1 - 13 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-13, January 2023. This paper describes the partial automation of drones (also referred to as uncrewed aerial vehicles, UAVs, or aerial robots) in populated areas within the visual line-of-sight of their pilot. Mission responsiveness is improved by reducing the number of human crew members and avoiding the need for area clearance, while carefully managing the workload of those remaining to ensure no compromise on safety. The work employs a system-centric approach with regard to integrating human and automation tasks based on their capabilities and use of standard procedures, whilst prioritizing the predictability and simplicity of the overall system. Safety claims about the proposed system are posed and rigorously analyzed through a structured safety case. The proposed system is applied to a bridge inspection case study with simulation results and scenario analysis. Citation: Drone Systems and Applications PubDate: 2023-02-10T08:00:00Z DOI: 10.1139/dsa-2022-0031 Issue No:Vol. 11 (2023)
Authors:Richard C. Millar, Leila Hashemi, Armin Mahmoodi, Robert Walter Meyer, Jeremy Laliberte Pages: 1 - 17 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-17, January 2023. This paper presents and assesses the feasibility and potential of a novel concept: the operation of multiple Unmanned Aerial Vehicles (UAVs) commanded and supported by a manned “Tender” air vehicle carrying a pilot and flight manager(s). The “Tender” is equipped to flexibly and economically monitor and manage multiple diverse UAVs over otherwise inaccessible terrain through wireless communication. The proposed architecture enables operations and analysis supported by the means to detect, assess, and accommodate change and hazards on the spot with effective human observation and coordination. Further, this paper seeks to find the optimal trajectories for UAVs to collect data from sensors in a predefined continuous space. We formulate the path-planning problem for a cooperative, and a diverse swarm of UAVs tasked with optimizing multiple objectives simultaneously with the goal of maximizing accumulated data within a given flight time within cloud data processing constraints as well as minimizing the probable imposed risk during UAVs mission. The risk assessment model determines risk indicators using an integrated Specific Operation Risk Assessment—Bayesian belief network approach, while its resultant analysis is weighted through the analytic hierarchy process ranking model. To this end, as the problem is formulated as a convex optimization model, and we propose a low complexity multi-objective reinforcement learning (MORL) algorithm with a provable performance guarantee to solve the problem efficiently. We show that the MORL architecture can be successfully trained and allows each UAV to map each observation of the network state to an action to make optimal movement decisions. This proposed network architecture enables the UAVs to balance multiple objectives. Estimated MSE measures show that the algorithm produced decreasing errors in the learning process with increasing epoch number. Citation: Drone Systems and Applications PubDate: 2023-01-25T08:00:00Z DOI: 10.1139/dsa-2022-0043 Issue No:Vol. 11 (2023)
Authors:Alexander L. Peace, Scott Jess Pages: 1 - 15 Abstract: Drone Systems and Applications, Volume 11, Issue , Page 1-15, January 2023. Drone use in geoscience research and teaching is becoming widespread, with diverse applications documented. Many studies favour consumer-level drones, however, recent developments in so-called “microdrones” (takeoff weight < 250 g) necessitate further investigation to determine possible benefits, limitations, and future developments. Microdrone deployment is often advantageous in numerous jurisdictions due to fewer regulations, lower cost, and simple transportation. In this study, we deployed a DJI Mini 2 microdrone to study the ca. 201 Ma North Mountain Basalt (NMB) exposed in coastal outcrops along the Bay of Fundy, Nova Scotia, Canada. We report benefits of the microdrone as a field aid with three related approaches: (1) general site location and characterisation, (2) drone-based photogrammetry using ArcGIS Drone2Map, and (3) quantitative fracture mapping using FracPaQ. Application of these methods showed that microdrone-acquired imagery from the NMB exposures provides a valuable resource for interpretation post-fieldwork. The microdrone-derived data show two near-perpendicular fracture sets in the NMB: ∼NNE–SSW and ∼ESE–WNW, with some variation along the coastline. Overall, we determined that microdrones offer field-based geoscientists a valuable tool due to quick deployment, a simple image capture process and relatively straightforward data processing, and thus predict that this approach to enhancing fieldwork will continue to advance. Citation: Drone Systems and Applications PubDate: 2022-12-07T08:00:00Z DOI: 10.1139/dsa-2022-0037 Issue No:Vol. 11 (2022)
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