Abstract. Melting of the Greenland Ice Sheet (GrIS) is the largest single contributor to eustatic sea level and is amplified by the growth of pigmented algae on the ice surface, which increases solar radiation absorption. This biological albedo-reducing effect and its impact upon sea level rise has not previously been quantified. Here, we combine field spectroscopy with a radiative-transfer model, supervised classification of unmanned aerial vehicle (UAV) and satellite remote-sensing data, and runoff modelling to calculate biologically driven ice surface ablation. We demonstrate that algal growth led to an additional 4.4–6.0 Gt of runoff from bare ice in the south-western sector of the GrIS in summer 2017, representing 10 %–13 % of the total. In localized patches with high biomass accumulation, algae accelerated melting by up to 26.15±3.77 % (standard error, SE). The year 2017 was a high-albedo year, so we also extended our analysis to the particularly low-albedo 2016 melt season. The runoff from the south-western bare-ice zone attributed to algae was much higher in 2016 at 8.8–12.2 Gt, although the proportion of the total runoff contributed by algae was similar at 9 %–13 %. Across a 10 000 km2 area around our field site, algae covered similar proportions of the exposed bare ice zone in both years (57.99 % in 2016 and 58.89 % in 2017), but more of the algal ice was classed as “high biomass” in 2016 (8.35 %) than 2017 (2.54 %). This interannual comparison demonstrates a positive feedback where more widespread, higher-biomass algal blooms are expected to form in high-melt years where the winter snowpack retreats further and earlier, providing a larger area for bloom development and also enhancing the provision of nutrients and liquid water liberated from melting ice. Our analysis confirms the importance of this biological albedo feedback and that its omission from predictive models leads to the systematic underestimation of Greenland's future sea level contribution, especially because both the bare-ice zones available for algal colonization and the length of the biological growth season are set to expand in the future.

The coordination of multiple autonomous vehicles into convoys or platoons is expected on our highways in the near future. However, before such platoons can be deployed, the new autonomous behaviours of the vehicles in these platoons must be certified. An appropriate representation for vehicle platooning is as a multiagent system in which each agent captures the "autonomous decisions" carried out by each vehicle. In order to ensure that these autonomous decision-making agents in vehicle platoons never violate safety requirements, we use formal verification. However, as the formal verification technique used to verify the agent code does not scale to the full system and as the global verification technique does not capture the essential verification of autonomous behaviour, we use a combination of the two approaches. This mixed strategy allows us to verify safety requirements not only of a model of the system, but of the actual agent code used to program the autonomous vehicles.(V2V) communication is used at a lower (continuous control system) level to adjust each vehicle's position in the lanes and the spacing between the vehicles. V2V is also used at higher levels, for example to communicate joining requests, leaving requests, or commands dissolving the platoon. So a traditional approach is to implement the software for each vehicle in terms of hybrid (and hierarchical) control systems and to analyse this using hybrid systems techniques.However, as the behaviours and requirements of these automotive platoons become more complex there is a move towards much greater autonomy within each vehicle. Although the human in the vehicle is still responsible, the autonomous control deals with much of the complex negotiation to allow other vehicles to leave and join, etc. Traditional approaches involve hybrid automata [12] in which the continuous aspects are encapsulated within discrete states, while discrete behaviours are expressed as transitions between these states. A drawback of combining discrete decision-making and continuous control within a hybrid automaton is that it is difficult to separate the two (high-level decision-making and continuous control) concerns. In addition, the representation of the high-level decision-making can become unnecessarily complex.As is increasingly common within autonomous systems, we use a hybrid autonomous systems architecture where not only is the discrete decision-making component separated from the continuous control system, but the behaviour of the discrete part is described in much more detail. In particular, the agent paradigm is used [26]. This style of architecture, using the agent paradigm, not only improves the system design from an engineering perspective but also facilitates the system analysis and verification. Indeed, we use this architecture for actually implementing automotive platoons, and we here aim to analyse the system by verification.Safety certification is an inevitable concern in the development of more autonomous road vehicles, and verifying the safety and reli...

This paper presents an alternative method of designing a guidance controller for a small unmanned aerial vehicle (UAV) so as to perform path following under wind disturbances. The wind effects acting on UAVs need to be taken into account and eventually eliminated. To solve this problem, we adopted a disturbance observer-based control approach. The wind information is first estimated by a nonlinear disturbance observer, then it is incorporated into the nominal path following controller to formulate a composite controller that is able to compensate wind influences. The globally asymptotic stability of the composite controller is illustrated through theoretical analysis, whereas its performance is evaluated by various simulations including the one with software-in-the-loop. Initial flight tests using a small fixed-wing UAV are carried out to demonstrate its actual performance.

Accurate and precise population estimates form the basis of conservation action but are lacking for many arboreal species due to the high costs and difficulty in surveying these species. Recently, researchers have started to use drones to obtain data on animal distribution and density. In this study, we compared ground and drone counts for spider monkeys (Ateles geoffroyi) at their sleeping sites using a custom-built drone fitted with a thermal infrared (TIR) camera. We demonstrated that a drone with a TIR camera can be successfully employed to determine the presence and count the number of spider monkeys in a forested area. Using a concordance analysis, we found high agreement between ground and drone counts for small monkey subgroups (<10 individuals), indicating that the methods do not differ when surveying small subgroups. However, we found low agreement between methods for larger subgroups (>10 individuals), with drone counts being higher than the corresponding ground counts in 83% of surveys. We could identify additional individuals from TIR drone footage due to a greater area covered compared to ground surveys. We recommend using TIR drones for surveys of spider monkey sleeping sites and discuss current challenges to implementation.

Search and rescue (SAR) is a vital line of defense against unnecessary loss of life. However,in a potentially hazardous environment, it is important to balance the risks associated with SARaction. Drones have the potential to help with the efficiency, success rate and safety of SAR operationsas they can cover large or hard to access areas quickly. The addition of thermal cameras to the dronesprovides the potential for automated and reliable detection of people in need of rescue. We performeda pilot study with a thermal-equipped drone for SAR applications in Morecambe Bay. In a varietyof realistic SAR scenarios, we found that we could detect humans who would be in need of rescue,both by the naked eye and by a simple automated method. We explore the current advantages andlimitations of thermal drone systems, and outline the future path to a useful system for deploymentin real-life SAR.