Recent research has highlighted the potential for high-resolution, high-density, 3D and 4D ground-penetrating radar (GPR) acquisitions on alpine glaciers. When carried out on foot, such surveys are laborious and time consuming, which limits their application to small domains of limited glaciological interest. Further, crevasses and other hazards make the data acquisition risky. To address these issues, we have developed a drone-based GPR system. The system has a payload weight of 2.2 kg and a data output rate of 14 traces per second. An 80-MHz antenna and a recording time of 2800 ns mean that depths of over 100 m can be reached in temperate ice. Differential GPS positioning assures accurate flight paths. At a speed of 4 m s−1 and height of 5 m above the glacier surface, our system can acquire over 4 line-km of GPR data in 20 min on a single set of drone batteries. After presenting the technical specifications of the system and tests required to optimize its performance, we showcase a recently acquired 3D dataset from the Otemma glacier in Switzerland, where 462 parallel GPR profiles were surveyed at a 1-m line spacing, totaling over 112 line-km of data, in only 4 days.

Gibbons are often difficult to observe in dense forest habitats using traditional ground-based methods. This makes it challenging to estimate group sizes and, in turn, population sizes. This has proven to be a key constraint on accurate monitoring of the last remaining population of the Critically Endangered cao vit gibbon Nomascus nasutus. However, new technologies are beginning to circumvent the problems associated with traditional methods. We hypothesized that, by using an unoccupied aerial vehicle (UAV) equipped with thermal and standard (RGB) cameras, we could obtain more accurate group size counts than by using ground-based observations, as fewer gibbons would be missed. We tested this during a population survey of the cao vit gibbon, finding that the thermal video footage revealed additional individuals that were not counted by ground-based surveyors. Statistically, there was strong evidence (93% probability) that UAV-derived counts were higher (by 41%) than concurrent ground-based counts. We recorded six primate groups of three species (cao vit gibbon, rhesus macaque Macaca mulatta and Assamese macaque Macaca assamensis), including 24 gibbons across four groups (c. 20% of the global population). The RGB video footage also revealed seven female gibbons, two of which were carrying infants, providing vital group composition data. These data have contributed directly to a more accurate population survey of the species than would have been possible using direct observation only. We anticipate more widespread use of UAVs in the study of gibbons and other threatened species, leading to a more robust evidence base for their conservation.

Unoccupied aerial application systems (UAAS) are gaining popularity for weed management to increase applicator safety and to deliver herbicide treatments where treatment sites limit ground-based spray equipment. Several studies have documented UAAS application strategies and procedures for weed control in terrestrial settings, yet literature describing remote spray technology for use in aquatics remains limited. Currently, applicators seek guidance for UAAS deployment for aquatic weed management to overcome site access restrictions, deal with environmental limitations, and improve ground-based applicator safety in hazardous treatment scenarios. In the present case studies, we evaluate a consumer-available UAAS to deliver the herbicide, florpyrauxifen-benzyl, as both foliar and directed in-water spray applications. The first case study showed that the invasive floating-leaved plant, yellow floating heart, was controlled 80% to 99% by 6 wk after treatment (WAT) following UAAS foliar herbicide treatments. The second case study demonstrated that UAAS directed in-water herbicide application reduced variable-leaf watermilfoil visible plant material by 94% at 5 WAT. Likewise, directed in-water applications from UAAS eliminated the need to deploy watercraft, which improved overall operational efficiency. Data from both case studies indicate that UAAS can provide an effective and efficient treatment strategy for floating-leaved and submersed plant control among common herbicide treatment scenarios. Future integration of UAAS in aquatic weed control programs is encouraged, especially among smaller treatment sites (≤4 ha) or where access limits traditional spray operations.

Expanding the current aquatic herbicide portfolio, reducing total spray volumes, or remotely delivering herbicide using novel spray technologies could improve management opportunities targeting invasive aquatic plants, where options are more limited. However, research on giant salvinia (Salvinia molesta Mitchell) response to foliar herbicide applications at carrier volumes ≤140 L ha−1 is incomplete. Likewise, no data exist documenting S. molesta control with unoccupied aerial application systems (UAAS). Following the recent >100-ha incursion of S. molesta in Gapway Swamp, NC, a case study was developed to provide guidance for ongoing management efforts. In total, three field trials evaluated registered aquatic and experimental herbicides using a 140 L ha−1 carrier volume. Select foliar applications from UAAS were also evaluated. Results at 8 wk after treatment (WAT) indicated the experimental protoporphyrinogen oxidase inhibitor, PPO-699-01 (424 g ai ha−1), in combination with endothall dipotassium salt (2,370 g ae ha−1) provided 78% visual control, whereas control when PPO-699-01 (212 g ai ha−1) was applied alone was lower at 35%. Evaluations also showed diquat (3,136 g ai ha−1) alone, glyphosate (4,539 g ae ha−1) alone, and metsulfuron-methyl (42 g ai ha−1) alone achieved 86% to 94% visual plant control at 8 WAT. Sequential foliar applications of diquat, flumioxazin (210 g ai ha−1), and carfentrazone (67 g ai ha−1) at 6 wk following exposure to in-water fluridone treatments were no longer efficacious by 6 WAT due to plant regrowth. Carfentrazone applications made from a backpack sprayer displayed greater control than applications made with UAAS deploying identical carrier volumes at 2 WAT; however, neither application method provided effective control at 8 WAT. Additional field validation is needed to further guide management direction of S. molesta control using low carrier volume foliar applications.

The Vulnerable marsh deer Blastocerus dichotomus, the largest native cervid in South America, is declining throughout its range as a result of the conversion of wetlands and overhunting. Estimated densities in open wetlands of several types are 0.1–6.8 individuals per km2. We undertook the first unmanned aerial vehicle (UAV) survey of the marsh deer to estimate the density of this species in a 113.6 km2 area under forestry management in the lower delta of the Paraná River, Argentina. During 6–8 August 2019, at a time of year when canopy cover is minimal, we surveyed marsh deer using Phantom 4 Pro UAVs along 94 transects totalling 127.8 km and 8.6 km2 (8.1% of the study area). The 5,506 photographs obtained were manually checked by us and by a group of 39 trained volunteers, following a standardized protocol. We detected a total of 58 marsh deer, giving an estimated density of 6.90 individuals per km2 (95% CI 5.26–8.54), which extrapolates to 559–908 individuals in our 113.6 km2 study area. As it has generally been assumed that marsh deer prefer open habitats, this relatively high estimate of density within a forestry plantation matrix is unexpected. We discuss the advantages of using UAVs to survey marsh deer and other related ungulates.

While the opioid epidemic engulfing the United States and the globe is well-documented, the potential use of powerful fentanyl derivatives as a weapon of terror is increasingly a concern. Carfentanyl, a powerful and deadly fentanyl derivative, is seeing a surge in popularity as an illegal street drug, and there is increasing congressional interest surrounding the classification of opioid derivatives under the Chemical Weapons Convention (CWC) given their potential to cause harm. The combination of the potency of opioid derivatives along with the ease of accessibility poses a potential risk of the use of these deadly agents as chemical weapons, particularly by terrorist organizations. Disaster Medicine specialists in recent years have established a sub-specialty in Counter-Terrorism Medicine (CTM) to address and research the unique terrorism-related issues relating to mitigation, preparedness, and response measures to asymmetric, multi-modality terrorist attacks.

The mass proliferation and increasing affordability of unmanned aerial vehicles (UAVs) in recent years has given rise to weaponized UAV use by terrorists, leading to mounting and credible concerns this attack methodology will be the next terrorism modus operandi. Counter-Terrorism Medicine (CTM) specialists need to consider how UAVs alter or create new mass-casualty scenarios that can further exploit existing medical preparedness vulnerabilities. With an opportunity to be proactive in disaster prevention, mitigation, and preparedness, it is imperative this gathering storm be acknowledged and stakeholders explore how best to prepare for, respond to, and mitigate the consequences of UAV incidents.

Data extraction from unmanned aerial vehicle (UAV) imagery has proved effective in animal surveys and monitoring, but to date has scarcely been used for detailed population analysis and individual animal feature extraction. We assessed the zoometric and feature extraction of the Arabian oryx (Oryx leucoryx) using data acquired from a captive population for comparison with reintroduced populations monitored by UAVs. Highly accurate scaled and geo-rectified imagery derived from UAV surveys allowed precise morphometric measurements of the oryx. The scaled top-view imagery combined with baseline data from known sex, age, weight and pregnancy status of captive individuals were used to develop predictive models. A bracketed index developed from the predictive models showed high accuracy for classifying the age group ≤16 months, animals with a weight >80 kg and pregnancy. The pregnancy classification decision tree model performed with 91.7% accuracy. The polynomial weight predictive model performed well with relatively high accuracy when using the total top-view surface measurement. Photogrammetrically processed UAV-acquired imagery can yield valuable zoometric data, feature extraction and modelling; it is a tool with a practical application for field biologists that can assist in the decision-making process for species conservation management.

Fossil fuel sources are well suited to fulfill the energy needs of human beings. Unfortunately, there are some limitations and disadvantages pertaining to fossil fuels, some of which are drastic. The main issues are: firstly, there is a finite supply of these fuels, eventually this supply will be exhausted; secondly, burning fossil fuels contributes to global warming, leading to disastrous consequences for the environment and the health of humans. Switching to renewable energy sources is the viable solution to the aforementioned issues. Robots bring numerous benefits in a wide variety of applications. Introducing robots to production environments and other applications results in a remarkable improvement in terms of productivity and efficiency. In this paper, the integration between robots and renewable energy sources is discussed. In other words, two main points are investigated: (1) how can renewable energy be a viable source of energy for robots and (2) how can the renewable energy industry benefit from utilizing robots in the execution of renewable energy-related tasks. Some of the recent developments concerning the integration between robots and renewable energy are reviewed. In addition, more opportunities and expected advancements are also discussed.

Quantifying the abundance of species is essential for their management and conservation. Much effort has been invested in surveys of freshwater dolphins in the Amazon basin but river dimensions and complex logistics limit replication of such studies across the region. We evaluated the effectiveness of using unmanned aerial vehicles (UAVs) for surveying two Amazon dolphin species, the tucuxi Sotalia fluviatilis and pink river dolphin Inia geoffrensis, in tropical rivers. In 2016 we conducted drone and visual surveys over 80 km of the Juruá River in Brazil. The aerial surveys provided higher accuracy than human observers in counting individuals detected in groups. Compared to estimates derived from visual surveys, the use of UAVs could provide a more feasible, economical and accurate estimate of Amazon river dolphin populations. The method could potentially be replicated in other important areas for the conservation of these species, to generate an improved index of river dolphin populations in the Amazon.

Although drones are becoming very common in the skies, most concerns about their use are not focused on their possible impact on wildlife. We used the information available from the scientific literature on the effects of drones on wildlife and complement it with Internet (YouTube) information to evaluate whether recreational activities using drones produce behavioural responses from wildlife. Scientific papers specifically evaluating the effects of drones on wildlife are scarce but increasing. Nonetheless, we found abundant videos in which many species from different taxonomic groups and multiple countries presented behavioural responses to drone overflights. Furthermore, 26% of the species that were disturbed are included in one of the International Union for Conservation of Nature categories of threat. We found that wildlife that use aerial and terrestrial habitats are more likely to show a behavioural response than those occupying aquatic habitats. The Internet is becoming a source of evidence of disturbances to wildlife that should be considered, particularly for recreational activities. We advocate for the use of technology, but argue that funding and effort should be devoted to evaluating drone impacts on wildlife. We call for educational programmes for laypeople who use drones for recreation and for more research and regulations on their use in sensitive wildlife areas.

This paper reports a visible and thermal drone monitoring system that integrates deep-learning-based detection and tracking modules. The biggest challenge in adopting deep learning methods for drone detection is the paucity of training drone images especially thermal drone images. To address this issue, we develop two data augmentation techniques. One is a model-based drone augmentation technique that automatically generates visible drone images with a bounding box label on the drone's location. The other is exploiting an adversarial data augmentation methodology to create thermal drone images. To track a small flying drone, we utilize the residual information between consecutive image frames. Finally, we present an integrated detection and tracking system that outperforms the performance of each individual module containing detection or tracking only. The experiments show that, even being trained on synthetic data, the proposed system performs well on real-world drone images with complex background. The USC drone detection and tracking dataset with user labeled bounding boxes is available to the public.

Data on the distribution and population size of the Near Threatened Tibetan antelope Pantholops hodgsonii are necessary to protect this species. Ground-based count surveys are usually carried out from a long distance to avoid disturbing the sensitive animals, and on calving grounds or along migration routes where they are seasonally concentrated. This can result in underestimation of population sizes if terrain features obstruct the view and high concentrations of animals make estimating numbers difficult. Here we test the efficacy of unmanned aerial vehicles (UAVs) for gathering population data for the Tibetan antelope. We conducted the study south of a known calving ground, at the foot of Sewu Snow Mountain, in the Chang Tang National Nature Reserve, China. The UAV did not appear to disturb the animals and resulted in more accurate counts than ground-based observations. A total of 23,063 Tibetan antelopes were identified in twelve orthoimages derived from c. 4,000 aerial photographs. In the first flight area 7,671 females and 4,353 calves were identified (proportion of calves: 36.2%). In the second flight area 7,989 females and 3,050 calves were identified (proportion of calves: 27.6%). Two flights over the same area revealed the direction and speed of moving Tibetan antelope groups. Image resolution, which can be controlled with flight planning, was an important factor in determining the animals’ visibility in the photos. We found that UAV-based surveys outperformed ground-based surveys, and that larger UAVs are preferable for this application.

The Great War ushered in a new era of long-distance combat. For the first time, weapons with a very long range were massively deployed, in previously unheard-of places: under the sea and in the air. Stealth fighting also included espionage and propaganda, now orchestrated on a global scale. In reaction to the carnage in the trenches, a degree of moral rehabilitation came to be conferred on the weapons initially associated with a “cowards’ war”. This in turn encouraged experimentation with the new, unmanned technology that would lead to the first prototypes of guided munitions and drones.

Armed drones pose a major threat to the general prohibition on the inter-state use of force and to respect for human rights. On the battlefield, in a situation of armed conflict, the use of armed drones may be able to satisfy the fundamental international humanitarian law rules of distinction and proportionality (although attributing international criminal responsibility for their unlawful use may prove a significant challenge). Away from the battlefield, the use of drone strikes will often amount to a violation of fundamental human rights. Greater clarity on the applicable legal regime along with restraints to prevent the further proliferation of drone technology are urgently needed.