Search Results (144)

The remain well clear (RWC) function of a detect-and-avoid (DAA) system provides guidance to a remote pilot (RP) of a remotely piloted aircraft to prevent a conflict from developing into a collision hazard. The ACAS Xu standard is a decision support system that uses RWC bands to advise a RP which headings to avoid. A recent A* DAA system is a resolution support system that advises a RP which route to take. The objective of this study is to achieve structured feedback by professional RPs on the horizontal RWC guidance of both systems. Nine RPs participated in on-line experiments, where they were shown videos of DAA displays of encounter scenarios between two aircraft. At various stages the RPs were asked for their opinion about transparency, pilot manoeuvring, situation awareness, display orientation, risk perception, competence, trust, and overall system preference. The results show that the scores for competence, trust and pilot manoeuvring were significantly higher, and the score for perceived risk was significant lower for the RWC route guidance. Overall, 89% of the RPs preferred the RWC route guidance, while one RP had no preference. An implication of the uncertainty in pilot behaviour is that ACAS Xu model-based optimisation may provide suboptimal RWC guidance strategies, while the A* DAA optimisation can be managed effectively. Full article

Maritime nations around the world proactively engage in preparedness, response, and recovery activities related to marine oil spills. In addition to an individual nation’s capabilities, there are a number of response organizations that are actively engaged in the surveillance, monitoring, and remote sensing of spilled oil. A global survey was conducted of these organizations to better understand surveillance/remote sensing capabilities operationally employed today from four aerial platforms: satellites, fixed-wing aircraft, helicopters, and remotely piloted aircraft systems (RPASs). Satellite remote sensing continues to be used for both routine surveillance of coastal environments and in support of response to oil spills. Additionally, there is a strong continued use of fixed-wing aircraft, and in some cases helicopters, particularly to support operational response to oil spills. Many of these fixed-wing aircraft are outfitted with sensor suites optimized for oil spill detection and documentation. Of particular interest is the recent introduction and widespread use of RPASs for the response of marine oil spills and oiled shorelines. Respondents identified operational gaps in remote sensing capabilities to support oil spill response, including the accurate measurement of oil spill thickness and volume, differentiation between petroleum oil and biogenic materials, and the detection of water-in-oil emulsions. Survey respondents also shared remote sensing capabilities used for oiled shorelines, as well as identifying research and operational gaps in the surveillance of oil spills. Full article

Research into Remotely Piloted Aircraft Systems (RPASs) has expanded rapidly, yet the competencies, knowledge, skills, and other attributes (KSaOs) required of RPAS pilots remain comparatively underexamined. This review consolidates existing studies addressing human performance, subject matter expertise, training practices, and accident causation to provide a comprehensive account of the KSaOs underpinning safe civilian and commercial drone operations. Prior research demonstrates that early work drew heavily on military contexts, which may not generalize to contemporary civilian operations characterized by smaller platforms, single-pilot tasks, and diverse industry applications. Studies employing subject matter experts highlight cognitive demands in areas such as situational awareness, workload management, planning, fatigue recognition, perceptual acuity, and decision-making. Accident analyses, predominantly using the human factors accident classification system and related taxonomies, show that skill errors and preconditions for unsafe acts are the most frequent contributors to RPAS occurrences, with limited evidence of higher-level latent organizational factors in civilian contexts. Emerging research emphasizes that RPAS pilots increasingly perform data-collection tasks integral to professional workflows, requiring competencies beyond aircraft handling alone. The review identifies significant gaps in training specificity, selection processes, and taxonomy suitability, indicating opportunities for future research to refine RPAS competency frameworks and support improved operational safety. Full article

Technological innovation in commercial Remotely Piloted Aircraft Systems (RPASs) is advancing rapidly. However, their operational efficiency remains limited by the need for on-site skilled human operators. Semi-autonomous drone-in-a-box (DIAB) systems are emerging as a practical solution, enabling automated, repeatable missions for applications such as construction site monitoring, security, and critical infrastructure inspection. Beyond industry, these systems hold significant promise for scientific research, particularly in long-term environmental monitoring where cost, accessibility, and safety are critical factors. In this technology demonstration, we detail the system implementation, discuss flight-planning challenges, and assess the overall feasibility of deploying a DJI Dock 2 DIAB system for remote monitoring of the Miles Ridge landslide in the Yukon Territory, Canada. The system was installed approximately 2.5 km from the landslide and operated remotely from across the country in Montreal, QC, about 4000 km away. A total of five datasets were acquired from July to September 2025, enabling three-dimensional reconstruction of the landslide surface from each acquisition. A comparison of extracted cross-sections demonstrated high reproducibility and accurate co-registration across acquisitions. This study highlights the potential of DIAB systems to support reliable, low-maintenance monitoring of remote landslides. Full article

The use of Remotely Piloted Aircraft (RPA) for spraying coffee crops has expanded due to their practicality and cost reduction. This study aimed to evaluate spray rate effects on coffee crops using two RPA (T10 and T20). The study was conducted on a commercial farm with 10-year-old Coffea arabica Catucaí Amarelo. Two aircraft were used, T1 (hydraulic) and T2 (rotary nozzles). The application rates were established at 25 and 50 L ha⁻¹. The application quality was obtained by attaching Water-Sensitive Papers (WSPs) to the upper, middle, and lower parts of coffee trees, inside and outside the plants, in addition to the inter-row areas. The statistical Nested Crossed Design was applied to analyze the dataset for the experimental field with three distinct factors (RPA, application rate, and WSP position) and four replications. WSP position was the most determinant factor across all design effects, followed by RPA. The external layers of leaves received more droplets than internal parts of coffee trees. The WSP position information indicated that no droplets reached the middle interior parts of the plants or underneath them. The inter-row positions (soil) received significantly more drops than the coffee plants, regardless of application rate or RPA. The potential for drift to the soil was high in both applications. The Potential Drift Risks were more significant for RPA T2. Future studies may deepen understanding of the relationship between coverage and specific application models for coffee farming, as traditional application methods require improvements. Full article

Today’s rapidly increasing number and performance of Remotely Piloted Aircraft Systems (RPASs) and sensors allows for an innovative approach in monitoring, mitigating, and responding to natural disasters and risks. At present, there are 100s of different RPAS platforms and smaller and more affordable payload sensors. As natural disasters pose ever increasing risks to society and the environment, it is imperative that these RPASs are utilized effectively. In order to exploit these advances, this study presents the development and validation of a Natural Disaster Information System (NDIS), a geospatial decision-support framework for RPAS-based natural hazard missions. The system integrates a global geohazard database with specifications of geophysical sensors and RPAS platforms to automate mission planning in a generalized form. NDIS v1.0 uses decision tree algorithms to select suitable sensors and platforms based on hazard type, distance to infrastructure, and survey feasibility. NDIS v2.0 introduces a Random Forest method and a Critical Path Method (CPM) to further optimize task sequencing and mission timing. The latest version, NDIS v3.8.3, implements a staggered decision workflow that sequentially maps hazard type and disaster stage to appropriate survey methods, sensor payloads, and compatible RPAS using rule-based and threshold-based filtering. RPAS selection considers payload capacity and range thresholds, adjusted dynamically by proximity, and ranks candidate platforms using hazard- and sensor-specific endurance criteria. The system is implemented using ArcGIS Pro 3.4.0, ArcGIS Experience Builder (2025 cloud release), and Azure Web App Services (Python 3.10 runtime). NDIS supports both batch processing and interactive real-time queries through a web-based user interface. Additional features include a statistical overview dashboard to help users interpret dataset distribution, and a crowdsourced input module that enables community-contributed hazard data via ArcGIS Survey123. NDIS is presented and validated in, for example, applications related to volcanic hazards in Indonesia. These capabilities make NDIS a scalable, adaptable, and operationally meaningful tool for multi-hazard monitoring and remote sensing mission planning. Full article

Post-fire soil and vegetation changes can intensify erosion and sediment yield by altering the factors controlling the runoff–infiltration balance. Erosion barriers (EBs) are widely used in hydrological and forest restoration to mitigate erosion, reduce sediment transport, and promote vegetation recovery. However, precise spatial assessments of their effectiveness remain scarce, requiring validation through operational methodologies. This study evaluates the impact of EB on post-fire vegetation recovery at two temporal and spatial scales: (1) Remotely Piloted Aircraft System (RPAS) imagery, acquired at high spatial resolution but limited to a single acquisition date coinciding with the field flight. These data were captured using a MicaSense RedEdge-MX multispectral camera and an RGB optical sensor (SODA), from which NDVI and vegetation height were derived through aerial photogrammetry and digital surface models (DSMs). (2) Sentinel-2 satellite imagery, offering coarser spatial resolution but enabling multi-temporal analysis, through NDVI time series spanning four consecutive years. The study was conducted in the area of the Luna Fire (northern Spain), which burned in July 2015. A paired sampling design compared upstream and downstream areas of burned wood stacks and control sites using NDVI values and vegetation height. Results showed slightly higher NDVI values (0.45) upstream of the EB (p < 0.05), while vegetation height was, on average, ~8 cm lower than in control sites (p > 0.05). Sentinel-2 analysis revealed significant differences in NDVI distributions between treatments (p < 0.05), although mean values were similar (~0.32), both showing positive trends over four years. This study offers indirect insight into the functioning and effectiveness of EB in post-fire recovery. The findings highlight the need for continued monitoring of treated areas to better understand environmental responses over time and to inform more effective land management strategies. Full article

The National Research Council Canada (NRC) is actively engaged in the development of an advanced autonomy system for the Bell 412 helicopter. This system’s capabilities extend to the execution of complex missions, such as arctic resupply missions. In an arctic resupply mission, the helicopter autonomously delivers supplies to a remote arctic base. During the mission it performs tasks such as takeoff, navigation, obstacle avoidance, and precise landing at its destination, all while minimizing the need for pilot intervention. The complexity of this autonomy system necessitates the inclusion of a high-level supervisory controller. This controller plays a critical role in monitoring mission progress, interacting with system components, and efficiently allocating resources. Conventionally, supervisory controllers are embedded within monolithic programs, lacking transparent state flows. This causes system modification and testing to be a significant challenge. In our research, we present an innovative approach and methodology to develop supervisory controllers for autonomous aircraft on the example of the NRC Bell 412. Using the Discrete Event System Specification (DEVS) formalism and the Cadmium simulation engine, we effectively address the challenges above. We discuss the entire development process for a state-based, event-driven supervisory controller for autonomous rotorcraft using the NRC’s Bell-412 autonomy system as a comprehensive case study. This process includes modeling, implementation, verification, validation, testing, and deployment. It incorporates a simulation phase, in which the supervisor integrates with components within a Digital Twin of the Bell 412, and a real-time operations phase, where the supervisor becomes an integral part of the actual Bell 412 helicopter. Our method outlines the smooth transition between these phases, ensuring a seamless and efficient process. Full article

Efficient irrigation management is crucial for optimizing crop development while minimizing resource use. This study aimed to assess the spatial variability of water distribution under conventional sprinkler irrigation, alongside soil moisture and infiltration dynamics, using multispectral sensors onboard Remotely Piloted Aircraft (RPAs). The experiment was conducted over a 466.2 m² area equipped with 65 georeferenced collectors spaced at 3 m intervals. Soil data were collected through volumetric rings (0–5 cm), auger sampling (30–40 cm), and 65 measurements of penetration resistance down to 60 cm. Four RPA flights were performed at 20 min intervals post-irrigation to generate NDVI and NDWI indices. NDWI values decreased from 0.03 to −0.02, indicating surface moisture reduction due to infiltration and evaporation, corroborated by gravimetric moisture decline from 0.194 g/g to 0.191 g/g. Penetration resistance exceeded 2400 kPa at 30 cm depth, while bulk density ranged from 1.30 to 1.50 g/cm³. Geostatistical methods, including Inverse Distance Weighting and Ordinary Kriging, revealed non-uniform water distribution and subsurface compaction zones. The integration of spectral indices within situ measurements proved effective in characterizing irrigation system performance, offering a robust approach for calibration and precision water management. Full article

Driving wheel slippage in agricultural tractors is influenced by soil moisture, density, and penetration resistance. These surface variations reflect post-tillage composition, enabling dynamic mapping via Remotely Piloted Aircraft (RPAs). This study evaluated ballast recommendations based on soil surface data and slippage percentages, correlating added wheel weights at different speeds for a tractor-reversible plow system. Six 94.5 m² quadrants were analyzed for slippage monitored by RPA (Mavic3M-RTK) pre- and post-agricultural operation overflights and soil sampling (moisture, density, penetration resistance). A 2 × 2 factorial scheme (F-test) assessed soil-surface attribute correlations and slippage under varying ballasts (52.5–57.5 kg/hp) and speeds. Results showed slippage ranged from 4.06% (52.5 kg/hp, fourth reduced gear) to 11.32% (57.5 kg/hp, same gear), with liquid ballast and gear selection significantly impacting performance in friable clayey soil. Digital Elevation Model (DEM) and spectral indices derived from RPA imagery, including Normalized Difference Red Edge (NDRE), Normalized Difference Water Index (NDWI), Bare Soil Index (BSI), Green–Red Vegetation Index (GRVI), Visible Atmospherically Resistant Index (VARI), and Slope, proved effective. The approach reduced tractor slippage from 11.32% (heavy ballast, 4th gear) to 4.06% (moderate ballast, 4th gear), showing clear improvement in traction performance. The integration of indices and slope metrics supported ballast adjustment strategies, particularly for secondary plowing operations, contributing to improved traction performance and overall operational efficiency. Full article

This paper proposes a solution for the design of high-performance propellers optimized for various flight conditions. Considering both propulsion and electric motor efficiencies, a new design optimization methodology is proposed. The optimization of the electric propulsive system is directly achieved by simultaneously analyzing the aerodynamic performance of the propeller and the motor. This study is focused on small, low-speed Remotely Piloted Aircraft Systems, addressing the design of fixed pitch propellers that operate efficiently over the entire speed range. The aerodynamic methodology uses combined blade element and momentum theory, which is adequate for a preliminary design phase with low computational time. For the aerodynamic coefficients of the airfoils used in these applications, at low Reynolds numbers, a new database was developed that incorporates airfoil experimental data and analytical methods to cover a wide range of angles of attack, beyond stall. For the modelling of the motor behavior, an idealization of the circuit was carried out, which considers its basic electric parameters. The results show significant improvements with respect to the information available for a current commercial propeller. Full article

This paper aims to analyze the performance of a tilt-rotor fixed-wing RPAS (Remotely Piloted Aircraft System) using a segmented approach, focusing on a nominal mission for SAR (Search and Rescue) applications. The study employs optimization techniques tailored to each segment to meet power consumption requirements, and the results highlight the accuracy of the physical characterization, which incorporates nonlinear propulsive and aerodynamic models derived from wind tunnel test campaigns. Critical segments for this nominal mission, such as the vertical take off or the transition from vertical to horizontal flight regimes, are addressed to fully understand the performance response of the aircraft. The proposed framework integrates experimental models into trajectory optimization procedures for each segment, enabling a realistic and modular analysis of energy use and aerodynamic performance. This approach provides valuable insights for both flight control design and future sizing iterations of convertible UAVs (Uncrewed Aerial Vehicles). Full article

In both scientific and industrial fields, there has been a notable increase in attention toward High-Altitude Pseudo-Satellites (HAPSs) in recent years. This surge is driven by their distinct advantages over traditional satellites and Remotely Piloted Aircraft Systems (RPASs). These benefits are particularly evident in critical areas such as intelligent transportation systems, surveillance, remote sensing, traffic and environmental monitoring, emergency communications, disaster relief efforts, and the facilitation of large-scale temporary events. This review provides an overview of key aspects related to the propellers and propulsion systems of HAPSs. To date, propellers remain the most efficient means of propulsion for high-altitude applications. However, due to the unique operational conditions at stratospheric altitudes, propeller design necessitates specific approaches that differ from those applied in conventional applications. After a brief overview of the propulsion systems proposed in the literature or employed by HAPSs, focusing on both the technical challenges and advancements in this emerging field, this review integrates theoretical foundations, historical design approaches, and the latest multi-fidelity optimization techniques to provide a comprehensive comparison of propeller design methods for HAPSs. It identifies key trends, including the growing use of CFD-based simulations methodologies, which contribute to notable performance improvements. Additionally, the review includes a critical assessment of experimental methods for performance evaluation. These developments have enabled the design of propellers with efficiencies exceeding 85%, offering valuable insights for the next generation of high-endurance, high-altitude platforms. Full article

This study presents a digital twin–based framework for assessing rockfall hazards at the immediate vicinity of the Rumkale Archaeological Site, a geologically sensitive and culturally significant location in southeastern Türkiye. Historically associated with early Christianity and strategically located along the Euphrates, Rumkale is a protected heritage site that attracts increasing numbers of visitors. Here, high-resolution photogrammetric models were generated using imagery acquired from a remotely piloted aircraft system and post-processed with ground control points to produce a spatially accurate 3D digital twin. Field-based geomechanical measurements including discontinuity orientations, joint classifications, and strength parameters were integrated with digital analyses to identify and evaluate hazardous rock blocks. Kinematic assessments conducted in the study revealed susceptibility to planar, wedge, and toppling failures. The results showed the role of lithological structure, active tectonics, and environmental factors in driving slope instability. The proposed methodology demonstrates effective use of digital twin technologies in conjunction with traditional geotechnical techniques, offering a replicable and non-invasive approach for site-scale hazard evaluation and conservation planning in heritage contexts. This work contributes to the advancement of interdisciplinary methods for geohazard-informed management of cultural landscapes. Full article

Monitoring forest structure, diversity, and biomass in restoration areas is both expensive and time-consuming. Metrics derived from digital aerial photogrammetry (DAP) may offer a cost-effective and efficient alternative for monitoring forest restoration. The main objective of this study was to use metrics derived from digital aerial photogrammetry (DAP) point clouds obtained by remotely piloted aircraft (RPA) to estimate aboveground biomass (AGB), species diversity, and structural variables for monitoring restored secondary tropical forest areas. The study was conducted in three active and one passive forest restoration systems located in a secondary forest in Sergipe state, Brazil. A total of 2507 tree individuals from 36 plots (0.0625 ha each) were identified, and their total height (ht) and diameter at breast height (dbh) were measured in the field. Concomitantly with the field inventory, the plots were mapped using an RPA, and traditional height-based point cloud metrics and Fourier transform-derived metrics were extracted for each plot. Regression models were developed to calculate AGB, Shannon diversity index (H′), ht, dbh, and basal area (ba). Furthermore, multivariate statistical analyses were used to characterize AGB and H′ in the different restoration systems. All fitted models selected Fourier transform-based metrics. The AGB estimates showed satisfactory accuracy (R² = 0.88; RMSE = 31.2%). The models for H′ and ba also performed well, with R² values of 0.90 and 0.67 and RMSEs of 24.8% and 20.1%, respectively. Estimates of structural variables (dbh and ht) showed high accuracy, with RMSE values close to 10%. Metrics derived from the Fourier transform were essential for estimating AGB, species diversity, and forest structure. The DAP-RPA-derived metrics used in this study demonstrate potential for monitoring and characterizing AGB and species richness in restored tropical forest systems. Full article