To what extent can drones be the primary determinants of victory in warfare? This question is at the heart of the drone revolution debate in security studies. Proponents of a drone revolution argue that drones provide ‘game-changing characteristics’, act as ‘magic bullets’ against adversaries, and even provide the key defence to decide the ‘fate of nations’. Sceptics disagree, arguing that no matter the nuances or contexts of war, drones can never be considered the primary determinant of victory. In this article, we argue that the two sides of the debate rest upon a false dichotomy – that technologies must either be revolutionary or evolutionary. We reappraise country-specific case studies used by both sides of the debate: the Ethiopia–Tigray War, the Houthi–Saudi War, and the Russia–Ukraine War. Our analysis reveals a welcome synthesis; the impact of drone employment depends on the types of war waged, the drone capabilities deployed, and the political objectives sought in each conflict. In this sense, drones can have an impact on war that is sometimes ordinary and sometimes revolutionary. It is only by clarifying the analytical scope of the debate that the impact of drones on the practice of war can be fully understood.

Drone technology and digital image analysis have enabled significant advances in precision agriculture, especially in site-specific treatment of weed escapes in crop fields. This study evaluated a pipeline for weed detection in multispectral drone imagery, along with site-specific herbicide application, using a remotely piloted aerial application system (RPAAS) targeting late-season weed escapes in rice with a selective postemergence rice herbicide, florpyrauxifen-benzyl. The efficacy of the RPAAS-based herbicide application with geocoordinates of weed escapes obtained manually or based on image analysis was compared with conventional backpack broadcast spray. The weed species targeted were barnyardgrass, Amazon sprangletop, yellow nutsedge, and hemp sesbania. A Python-based rice–weed detection model was developed using the canopy height model and spectral reflectance of weeds and rice plants. Results indicate that the accuracy of image-based detection for late-season weed escapes in rice was highest for hemp sesbania (95%), followed by Amazon sprangletop (87%) and yellow nutsedge (74%), with barnyardgrass showing the lowest accuracy at 62%. The study found that the backpack broadcast method had the highest efficacy in weed control, followed by the RPAAS method using manually obtained geocoordinates and those based on image analysis. Site-specific herbicide application using RPAAS resulted in a 45% reduction in herbicide compared to the broadcast backpack application. Moreover, the RPAAS site-specific application method for late-season treatment minimized the field area affected by herbicide injury and protected rice grain yields compared to the broadcast method. Overall, the utility of unmanned aerial sprayer–based detection and site-specific treatment of late-season weed escapes in rice has been demonstrated in this research, but further improvements in weed detection efficacy and the accuracy of targeting plants with RPAAS are necessary.

How do military chaplains perceive the legitimacy of US drone strikes? Though chaplains are entrusted to shape the moral use of force, scholars have not studied what accounts for their perceptions of legitimate drone warfare, and whether these relate to legal-rational or moral considerations. To understand these dynamics, we field a survey experiment among a rare sample of US Army chaplains. We find that while chaplains’ perceptions of legally and morally legitimate strikes largely covary, they can also deviate. Chaplains discount the legality of strikes in undeclared theaters of operations, even when they are tightly constrained to minimize civilian casualties. Though chaplains may perceive strikes as legitimate, they can also support them less. Finally, other factors shape chaplains’ perceptions, with combat experiences exercising the greatest effect on perceptions of legal versus moral legitimacy. This first evidence for chaplains’ attitudes toward drone warfare has implications for policy, research, and military readiness.

In recent years, the rapid convergence of artificial intelligence (AI) and low-altitude flight technology has driven significant transformations across various industries. These advancements have showcased immense potential in areas such as logistics distribution, urban air mobility (UAM) and national defense. By adopting the AI technology, low-altitude flight technology can achieve high levels of automation and operate in coordinated swarms, thereby enhancing efficiency and precision. However, as these technologies become more pervasive, they also raise pressing ethical or moral concerns, particularly regarding privacy, public safety, as well as the risks of militarisation and weaponisation. These issues have sparked extensive debates. In summary, while the integration of AI and low-altitude flight presents revolutionary opportunities, it also introduces complex ethical challenges. This article will explore these opportunities and challenges in depth, focusing on areas such as privacy protection, public safety, military applications and legal regulation, and will propose strategies to ensure that technological advancements remain aligned with ethical or moral principles.

Birds are often used as ecological indicators because they are widely distributed across diverse habitats and display distinct behavioural responses to environmental changes. The Endangered Grey Crowned Crane Balearica regulorum is regarded as a flagship species of Africa’s wetland and grassland habitats, both of which are undergoing substantial transformation to alternative land uses. The delayed reproductive strategies and habitat specialisation of this crane species makes them more vulnerable to extinction, but this risk is further compounded by data paucity. We employed traditional and contemporary survey methods to collect breeding metrics to calculate stage transition probabilities (i.e. egg–hatchling, hatchling–juvenile) and to identify possible macro-environmental factors that either promote or hinder their reproductive output in a key agricultural area in KwaZulu-Natal, South Africa. We found that Grey Crowned Cranes have a low hatching rate of 38.4% (95% confidence interval 29.3–48.4%) and show that this low hatching rate is exacerbated under high rainfall intensity. Multivariate analyses and multi-model inference revealed that successful nest-sites were generally associated with larger open water-bodies, greater distances from shore, and increased proximity to secondary roads, buildings, and natural grasslands. Although increased agricultural activities might promote greater foraging opportunities, the overall breeding outcomes of this species were poor in this key agricultural region. Our findings stress the urgent need for further fine-scale data collection and monitoring activities to better inform conservation strategies for this species. We also encourage future studies to focus on aspects affecting Grey Crowned Crane breeding in regions where proximity to human activities is inevitable.

This essay assesses the morality of Ukraine's use of drones to attack targets inside Russia. Following its invasion by Russian forces, Ukraine has had a just cause to wage a war of self-defense. However, its efforts to achieve that cause remain subject to moral limits. Even a state that has been unjustly attacked may not, for example, respond by deliberately targeting the attacking state's civilian population. To do so would violate the jus in bello principle of discrimination. The essay first describes how drone technology has frequently enabled long-range strikes against Russian military assets as well as other targets inside cities. It then explains why it would be morally wrong for Ukraine to attack its enemy's population centers. First, Russian civilians are not liable to attack, and this nonliability is undiminished by the injustice of Russia's invasion or by any in bello wrongs committed by the Russian military. Second, attacking Russian cities with drones would arguably achieve little or no self-defensive benefit for Ukraine, and it could even be counterproductive.

The global increase in observed forest dieback, characterized by the death of tree foliage, heralds widespread decline in forest ecosystems. This degradation causes significant changes to ecosystem services and functions, including habitat provision and carbon sequestration, which can be difficult to detect using traditional monitoring techniques, highlighting the need for large-scale and high-frequency monitoring. Contemporary developments in the instruments and methods to gather and process data at large scales mean this monitoring is now possible. In particular, the advancement of low-cost drone technology and deep learning on consumer-level hardware provide new opportunities. Here, we use an approach based on deep learning and vegetation indices to assess crown dieback from RGB aerial data without the need for expensive instrumentation such as LiDAR. We use an iterative approach to match crown footprints predicted by deep learning with field-based inventory data from a Mediterranean ecosystem exhibiting drought-induced dieback, and compare expert field-based crown dieback estimation with vegetation index-based estimates. We obtain high overall segmentation accuracy (mAP: 0.519) without the need for additional technical development of the underlying Mask R-CNN model, underscoring the potential of these approaches for non-expert use and proving their applicability to real-world conservation. We also find that color-coordinate based estimates of dieback correlate well with expert field-based estimation. Substituting ground truth for Mask R-CNN model predictions showed negligible impact on dieback estimates, indicating robustness. Our findings demonstrate the potential of automated data collection and processing, including the application of deep learning, to improve the coverage, speed, and cost of forest dieback monitoring.

Aerial visuals play a central – and increasing – role in military operations, informing military decision-makers in real time. While adding relevant and time-sensitive information, these visuals construct an imperfect representation of people and spaces, placing additional burdens on decision-makers and creating a persuasive – yet misleading – virtual representation of the actual conditions on the ground. Based on interdisciplinary analysis of critical security studies, behavioural economics and international law literature, as well as rich data from US and Israeli military investigations into four military operations spanning from 2009 to 2021, this article identifies three types of challenges stemming from the mounting reliance on aerial visuals to inform military operations: technical challenges, relating to the technical capabilities and features of aerial vision technologies; cognitive challenges, relating to decision-making biases affecting human decision-makers; and human-technological challenges, relating to the human–machine interaction itself. The article suggests ways to mitigate these challenges, improve the application of the law of armed conflict, and protect people, animals and the environment during armed conflicts.

Vultures are among the most threatened bird guilds on the planet and have a unique functional role within ecosystems. They are therefore subject to increasing research interest, calling for standardised study approaches and monitoring methods. The use of Unmanned Aircraft Systems (UASs) is rapidly gaining popularity in ecological research due to technological advances, affordability, and accessibility. This study reviews the existing peer-reviewed publications and grey literature on the responses of European vultures and other comparable species to UASs, and summarises the types of UAS use, their potential disturbance effects on vultures, and the resulting inter- and intra-specific interactions. Our goal was to assess the potential effects of UASs and to provide practical recommendations to optimise their safe use in vulture conservation and research. We acknowledge the potential of UASs to increase research efficiency and reduce research effort, time, and financial cost. Owing to the absence of sufficient data on long-term disturbance effects, we advocate the precautionary principle and offer a set of species-tailored practical recommendations to limit the potential negative effects of UASs and maximise their value in conservation management. We urge that the physiological and long-term impacts on vulture reproduction are considered and call for standardised monitoring protocols and controls on UAS use. Our conclusions and recommendations are particularly aimed at researchers working on vulture conservation and restoration projects worldwide.

Coasts are undeniably regions of critical importance for a range of environmental, sociocultural, and economic reasons. Yet they are also areas of intense anthropogenic impact and are particularly susceptible to climate change-related concerns. As such, it is imperative that we have the means to monitor and manage them in a sustainable manner. Drone technology has emerged as providing a unique value proposition in coastal environments to support data-driven monitoring and management decisions. With their highly detailed data capture capability, drones are particularly well suited to map the spatial heterogeneity, structural complexity, and temporally dynamic nature of coasts. Further, they are readily accessible to coastal populations and can promote grassroots action by the very people whose lives and livelihoods the coasts support. Herein, we cover several of the leading innovations in using aerial drones to map coastal ecosystems. We then consider how general trends and technology projections including artificial intelligence, as well as cloud and edge computing offer opportunities for the future of drone mapping and monitoring in a coastal context. While the challenge of change is inevitable, embracing the opportunities it provides will allow us to better understand and live sustainably with and within our coastal ecosystems.