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Traditional field vegetation plot surveys are critical for monitoring ecosystem restoration performance and include visual observations to quantitatively measure plants (e.g., species composition and abundance). However, surveys can be costly, time-consuming, and only provide data at discrete locations, leaving potential data gaps across a site. Uncrewed aircraft system (UAS) technology can help fill data gaps between high-to-moderate spatial resolution (e.g., 1–30 m) satellite imagery, manned airborne data, and traditional field surveys, yet it has not been thoroughly evaluated in a virtual capacity as an alternative to traditional field vegetation plot surveys. This study assessed the utility of UAS red-green-blue (RGB) and low-altitude imagery for virtually surveying vegetation plots in a web application and compared to traditional field surveys at two coastal marsh restoration sites in southeast Louisiana, USA. Separate expert botanists independently observed vegetation plots in the field vs. using UAS imagery in a web application to identify growth form, species, and coverages. Taxa richness and assemblages were compared between field and virtual vegetation plot survey results using taxa resolution (growth-form and species-level) and data collection type (RGB imagery, Anafi [low-altitude] imagery, or field data) to assess accuracy. Virtual survey results obtained using Anafi low-altitude imagery compared better to field data than those from RGB imagery, but they were dependent on growth-form or species-level resolution. There were no significant differences in taxa richness between all survey types for a growth-form level analysis. However, there were significant differences between each survey type for species-level identification. The number of species identified increased by approximately two-fold going from RGB to Anafi low-altitude imagery and another two-fold from Anafi low-altitude imagery to field data. Vegetation community assemblages were distinct between the two marsh sites, and similarity percentages were higher between Anafi low-altitude imagery and field data compared to RGB imagery. Graminoid identification mismatches explained a high amount of variance between virtual and field similarity percentages due to the challenge of discriminating between them in a virtual setting. The higher level of detail in Anafi low-altitude imagery proved advantageous for properly identifying lower abundance species. These identifications included important taxa, such as invasive species, that were overlooked when using RGB imagery. This study demonstrates the potential utility of high-resolution UAS imagery for increasing marsh vegetation monitoring efficiencies to improve ecosystem management actions and outcomes. Restoration practitioners can use these results to better understand the level of accuracy for identifying vegetation growth form, species, and coverages from UAS imagery compared to field data to effectively monitor restored marsh ecosystems. [ABSTRACT FROM AUTHOR]

Last-mile delivery systems are one of the numerous industrial applications of uncrewed aircraft systems (UAS). This study analyzes UAS-based package delivery systems in the context of the integrated operations of crewed and uncrewed aircraft. It introduces a multi-trip, time-dependent vehicle routing problem aimed at optimizing UAS delivery routes within integrated operations. By conducting numerical simulations of helicopters (crewed aircraft) and UAS missions sharing the same airspace, the optimal UAS routes for resolving potential conflicts in the shared airspace can be effectively determined without any adverse impact on helicopter operations. Knowing the helicopter mission times in advance enables the efficient planning of UAS missions. The results of this study provide valuable insights regarding the implementation of integrated crewed and uncrewed aircraft operations. [ABSTRACT FROM AUTHOR]

Context: Understanding the movement of bioaerosols, such as spores and pollen, through the atmosphere is important for a broad spectrum of landscape research, including agricultural fungal outbreaks and pollen threats to public health. As spores and pollen can be transported in the air over large distances, the use of aircraft has historically played a role in detecting and mapping their presence in the lower atmosphere. Objectives: We present a simple alternative to costly and specialized aircraft and associated equipment that are typically used in the study of spores and pollen in the atmosphere. Methods: We use 3D printable components and common lab supplies mounted on an uncrewed aircraft (UA). Conveniently, this setup does not require additional electronic components to control collection during flight, using the UA landing gear mechanism instead. Results: We demonstrate that this apparatus can collect fungal spores in the atmosphere and describe potential impacts by the environment and experimental protocol on collection efficiency. These include the effects of: (1) competing airflows from UA rotors, flight trajectories, and wind, (2) flight altitude, and (3) particle size and Petri dish collection medium. Conclusions: Complex biological mechanisms and atmospheric dynamics dictate the release, transport, and deposition of bioaerosols. Economical methods to sample bioaerosols in the lower atmosphere can increase the amount and type of data collected and unlock new understanding. The methodology presented here provides an economical method to sample bioaerosols that can help improve landscape-level understanding of the dispersal of bioaerosols. [ABSTRACT FROM AUTHOR]

The present study introduces "WindAware", a wind and turbulence prediction system that provides nowcasts of wind and turbulence parameters every 5 min up to 6 h over a predetermined airway over Chicago, Illinois, USA, based on 100 m high-resolution simulations (HRSs). This system is a long short-term memory-based recurrent neural network (LSTM-RNN) that uses existing ground-based wind data to provide nowcasts (forecasts up to 6 h every 5 min) of wind speed, wind direction, wind gust, and eddy dissipation rate to support the Uncrewed Aircraft Systems (UASs) safe integration into the National Airspace System (NAS). These HRSs are validated using both ground-based measurements over airports and upper-air radiosonde observations and their skill is illustrated during lake-breeze events. A reasonable agreement is found between measured and simulated winds especially when the boundary layer is convective, but the timing and inland penetration of lake-breeze events are overall slightly misrepresented. The WindAware model is compared with the classic multilayer perceptron (MLP) and the eXtreme Gradient Boosting (XGBoost) models. It is demonstrated by comparison to high-resolution simulations that WindAware provides more accurate predictions than the MLP over the 6 h lead times and has almost similar performance as the XGBoost model although the XGBoost's training is the fastest using its parallelized implementation. WindAware also has higher prediction errors when validated against lake-breeze events data due to their under-representation in the training dataset. [ABSTRACT FROM AUTHOR]

With the advancing development of Advanced Air Mobility (AAM), there is a collaborative effort to increase safety in the airspace. AAM is an advancing field of aviation that aims to contribute to the safe transportation of goods and people using aerial vehicles. When aerial vehicles are operating in high-density locations such as urban areas, it can become crucial to incorporate collision avoidance systems. Currently, there are available pilot advisory systems such as Traffic Collision and Avoidance Systems (TCAS) providing assistance to manned aircraft, although there are currently no collision avoidance systems for autonomous flights. Standards Organizations such as the Institute of Electrical and Electronics Engineers (IEEE), Radio Technical Commission for Aeronautics (RTCA), and General Aviation Manufacturers Association (GAMA) are working to develop cooperative autonomous flights using UAS-to-UAS Communication in structured and unstructured airspaces. This paper presents a new approach for collision avoidance strategies within structured airspace known as “digital traffic lights”. The digital traffic lights are deployed over an area of land, controlling all UAVs that enter a potential collision zone and providing specific directions to mitigate a collision in the airspace. This strategy is proven through the results demonstrated through simulation in a Cesium Environment. With the deployment of the system, collision avoidance can be achieved for autonomous flights in all airspaces.

Importance: Out-of-hospital cardiac arrest (OHCA) is a leading cause of morbidity and mortality in the US and Europe (∼600,000 incident events annually) and around the world (∼3.8 million). With every minute that passes without cardiopulmonary resuscitation or defibrillation, the probability of survival decreases by 10%. Preliminary studies suggest that uncrewed aircraft systems, also known as drones, can deliver automated external defibrillators (AEDs) to OHCA victims faster than ground transport and potentially save lives. Objective: To date, the United States (US), Sweden, and Canada have made significant contributions to the knowledge base regarding AED-equipped drones. The purpose of this Special Communication is to explore the challenges and facilitators impacting the progress of AED-equipped drone integration into emergency medicine research and applications in the US, Sweden, and Canada. We also explore opportunities to propel this innovative and important research forward. Evidence review: In this narrative review, we summarize the AED-drone research to date from the US, Sweden, and Canada, including the first drone-assisted delivery of an AED to an OHCA. Further, we compare the research environment, emergency medical systems, and aviation regulatory environment in each country as they apply to OHCA, AEDs, and drones. Finally, we provide recommendations for advancing research and implementation of AED-drone technology into emergency care. Findings: The rates that drone technologies have been integrated into both research and real-life emergency care in each country varies considerably. Based on current research, there is significant potential in incorporating AED-equipped drones into the chain of survival for OHCA emergency response. Comparing the different environments and systems in each country revealed ways that each can serve as a facilitator or barrier to future AED-drone research. Conclusions and relevance: The US, Sweden, and Canada each offers different challenges and opportunities in this field of research. Together, the international community can learn from one another to optimize integration of AED-equipped drones into emergency systems of care.

Polar boundary layers are difficult to model due to the existence of intermittent turbulence within stable layers. Here we present a case study evaluation of coherent structures in a stable boundary layer observed during a series of flights with an uncrewed aircraft system (DataHawk2) on 19 October 2016 at Oliktok Point, Alaska as part of the ERASMUS (Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems) field campaign. During a sequence of five flights over a nine-hour period, 57 profiles of atmospheric properties (0–400 m a.g.l) were collected. Turbulence was identified using derived Richardson Number, temperature structure function parameter, and turbulence kinetic energy dissipation. Throughout all flights on this strongly stable day, intermittent turbulence was observed. These turbulent layers showed well-mixed potential temperature profiles embedded within otherwise stable potential temperature profiles; often resulting in a characteristic staircase pattern. Turbulent layers ranged from 1 to 30 m deep, with most individual layers being 1–2 m deep. Vertical propagation velocities of layers in the lower atmosphere were on the order of a few cm s−1, typical of non-convective environments. In different regions of the profile, turbulence was driven by a different balance of buoyancy and shear forces, with turbulence in the near surface environment driven by strong shear forces overcoming strong resistance to buoyancy, while turbulence in elevated layers characterized by weaker shear forces overcoming weaker resistance to buoyancy. We discuss the potential of such datasets for improving subgrid parameterizations of small-scale turbulence embedded within stable boundary layers. [ABSTRACT FROM AUTHOR]

Autonomous uncrewed aircraft will require collision avoidance systems (CASs) designed with autonomy in mind as they integrate into the increasingly crowded national airspace system. Current uncrewed aircraft CASs typically require a remote pilot to execute avoidance or to provide poorly defined guidance that does not benefit autonomous systems. The Path Recovery Automated Collision Avoidance System (PRACAS) re-plans flight paths to autonomously adjust for collisions using path planners and keep-out zones (KOZs), but it does not currently detect or mitigate overtaking collisions. This work investigates the effect of geometric KOZs on overtaking scenarios for autonomous uncrewed aircraft. KOZ shapes were developed by relating relative velocities and turn rates of aircraft in overtaking scenarios and were tested using PRACAS. The operational ranges for approach heading, relative velocity, and look-ahead time were then determined. The set of KOZs that were developed prevented intruder aircraft from entering the minimum separation distance of one wingspan from the mission aircraft in overtaking scenarios with look-ahead times between 5 and 12 s, relative velocities of 2–20, and approach angles between 110° and −110° measured from the heading of the main UAS. Minimum separation was maintained for low-speed encounters with relative velocities between 1.1 and 2.0 for look-ahead times between 2 and 8 s for all approach angles. With look-ahead times ranging from 5 to 8 s, overtaking collisions of all tested approach angles and relative speeds are handled with more than twice the separation required for success, showing that the KOZs developed are feasible in possible autonomous CASs.

In the very near future, Advanced Air Mobility (AAM) services including air taxis and air ambulances are moving closer to reality. The low-altitude airspace, especially in urban areas, is expected to be filled with thousands of uncrewed aircraft systems (UASs). Such an increase in volume of UASs in the national airspace is going to create a huge challenge for air traffic management. This article outlines how the stakeholder communities - academics, federal aviation administration, aviation industry, and regional communities - are preparing for this exciting development. The central theme presented here is an integrated air space management, or a digital twin model for the airspace management. The digital twin system is presented as a combination of subsystems that include integrated airspace management, autonomous air space operations, digital flight rules, urban air corridors, and UAS to UAS communications. The subsystems discussed in this article along with the digital infrastructure form the foundation for enhanced autonomy and safety of AAM.

This study applies uncrewed aircraft systems towards the investigation of surface-layer structure during the morning transition. Three uncrewed aircraft systems simultaneously measuring horizontal transects were partnered with a fourth measuring vertical profiles during two consecutive mornings as part of the 2017 Collaboration Leading Operational Unmanned Aerial System Development for Meteorology and Atmospheric Physics (CLOUDMAP) measurement campaign near Stillwater, Oklahoma, USA. Data were analyzed to extract time-dependent single-point statistics of kinematic and thermodynamic variables from the uncrewed aircraft systems. In addition, an approach is presented by which multi-point spatial statistics in the form of auto- and cross-correlations could be calculated from the measurements. The results reflect differences in the evolution of spatial statistics with altitude for each of the two days at scales smaller than 500 m, despite very similar synoptic conditions. Conditional averaging was also applied to identify the structure of sweep and ejection motions and results revealed similarities to observations from canonical wall-bounded flow. [ABSTRACT FROM AUTHOR]