Established in 2013, The OpenSky Network, a crowdsourced network of ADS-B receivers, has consistently collected surveillance data from equipped aircraft and made it available for science. Coverage has steadily improved, boasting more than 6000 registered sensors worldwide today. This platform has aided numerous researchers in publishing studies across fields such as air traffic management, security, environment, and radio frequency interference. Following the 2020 mandate, most aircraft flying at high altitudes in Europe or Northern America are within range of one of the network’s ADS-B receivers. To complement existing research using OpenSky data, this paper focuses on lower altitude coverage, including light aircraft, general aviation, gliders, and ultralights, which are not required to carry ADS-B transponders. Instead, these often use, esp. in Europe, another traffic awareness and collision avoidance technology known as FLARM. The OpenSky Network has been gathering FLARM messages since 2018, and now enough data is available for a detailed analysis. The aim of this report is to present OpenSky’s FLARM data, explain the workings of the technology, and highlight potential uses of this data for future research.@en

In this paper, we analyze two months of trajectory data for aircraft landing in five major European airports. Based on open ADS-B data from the OpenSky Network and open performance models, we enrich all trajectories with automatically detected procedure information, fuel consumption, and emissions for supported aircraft types. To assess the inefficiencies associated with holding patterns, point merges, and continuous descent operations across different airports, we propose methodologies to quantify and compare these environmental inefficiencies. Holding patterns are found to have a higher negative impact on the environment than point merge and continuous descent operations. Furthermore, the paper provides recommendations for procedure evaluations of future airports, which could help policymakers and relevant stakeholders to evaluate the environmental performances of arrival procedures based on open data and open models@en

Efforts to minimise the environmental impact of aviation can be implemented at several levels including electric green taxiing systems, novel propulsion systems, jet fuels, improvements in aircraft efficiency and optimisation of climb profiles. In this paper, we address the optimisation of flight plans in a route network considering operational parameters and weather forecast. We implement an A* based approach to explore all possible sequences of nodes, altitudes with given wind, temperature and pressure forecasts in order to minimise total flown distance, total burnt fuel, CO2 and non-CO2 emissions, the latter being responsible for two-thirds of aviation radiative forcing. We evaluated our approach on both a network of standard routes and through free route areas, and observed that our optimised flight plans are consistent with those that have actually been filed to be flown in similar weather conditions during December 2021. @en

Civil aviation contributes to rising global greenhouse gas emissions. Flights carried out by private and business jets are only a very small fraction of commercial passenger flights. However, these private flights are extremely environmentally inefficient and account for the most emissions per passenger in the aviation sector. While the commercial aviation sector has been under increased scrutiny by environmentalists for years, the footprint of private and business jets has entered the public eye only very recently. Social media provides new ways for sharing individual private flights, but the large-scale analysis of private jet flights and their emissions has been lacking until now. To better inform this discussion, we use open and large-scale flight data collected by the OpenSky Network over fours years and apply the OpenAP model in order to estimate the emissions of around 250 private jets. The total carbon emissions is found to be between 0.45 and 0.5 megatonnes. The yearly emissions from these selected jets is equivalent to 40,000 global inhabitant emissions. In our analysis, we provide further insight into private jet emissions and raise awareness about the emission inequalities in the current aviation system.

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The usage of large private and business jets, from those owned by Elon Musk to Kylie Jenner and Bernard Arnault, has recently attracted considerable attention in many countries. Enabled by open and crowdsourced aircraft tracking systems based on the automatic dependent surveillance–broadcast protocol, the aircraft and their owners have been scrutinized. While the underlying technology is not novel and its privacy issues have been discussed for years, the increased attention has led to the backlash against open tracking data and, consequently, a scramble to find possible solutions to hide private jets from the public eye. In this paper, we analyze two such methods, which have not yet been discussed previously in the literature: blocking requests to web tracking platforms and malicious editing of crowdsourced databases. We draw on data from the OpenSky Network and illustrate the futility of such approaches. Finally, we outline the type of stakeholders and aircraft deploying such methods, as well as demonstrate the level of environmental impact that might have otherwise been missed by the public.

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Inefficiencies in flight operations, like deviations and non-optimal flight speed or altitude, are directly linked to flight emission inefficiencies. Quantifying these emission inefficiencies and studying potential mitigation strategies is certainly beneficial for the sustainability of the aviation industry. In this paper, we analyze emission inefficiencies in Dutch and French airspaces using flight data from 2019. The emission inefficiency analysis quantifies the excess carbon emissions for each flight by comparing its emissions with a set of optimal alternative trajectories. We find that around 19% of excess emissions existed in 2019 within the airspace of interest. We also study the potential reduction of emissions by replacing short-range flights with electric aircraft. We propose a simple electric aircraft energy model and relate that to emissions in electric generations in different countries. We find that besides the significant increase in air traffic demand caused by the limited capacities of electric flights, the emissions caused by electricity generation cannot be neglected. Significant reductions can only be achieved when emissions caused by electricity generation are low, as is the case currently in France. However, more emissions can be indirectly generated if the electricity used to power the future electric aircraft is itself produced from high emission sources, as is the case currently in the Netherlands. The paper also provides further insights and recommendations on the data sources, research approach, and future research for aviation sustainability. @en

The environmental impact of aviation has become the focus of increased concerns for policymakers around the world. The recent pandemic provided many interesting case studies on the impact of aviation on the environment. Following the initial COVID-19 containment measures and hard lockdowns, the sharp decrease in aircraft movements caused a measurably improved air quality worthy of further study.The OpenSky Network has acted as an important open data source for aviation research since 2013. In this paper, we analyze one year of fine-grained pre-COVID air traffic trajectories (comprising the entire year 2018) to estimate fuel consumption and pollutant emissions in the aviation industry. We compare this large-scale big data processing approach to a reduced model approach based solely on global commercial aircraft movement schedules collected from airlines and airports, aggregated by a commercial provider.Our study quantifies the impact of commercial aviation on global emissions. The numbers reveal that aviation's CO₂ emissions contribute to 2% of global emissions and that commercial aviation contribution remains a proxy for countries' wealth.

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The year 2020 had been selected by EU and US regulators as the deadline for ADS-B compliant Mode S transponders, following various iterations of ADS-B and Mode S services. It will also be remembered as marking a profound change in civil aviation, when the global virus outbreak triggered an unprecedented slowdown in traffic and brought immense impact on the world economy. Fleets have been grounded and a great number of airplanes went into long-term storage due to travel restrictions. The OpenSky Network has been collecting valuable information regarding ADS-B compliance since 2017. It also acted as an important open data source for studying the aviation industry during these crisis times. In this paper, we analyze years of data collected by the OpenSky Network to provide an overview of the past and current situations in global air traffic with equipage updates, ADS-B implementation, Mode S interrogation practices, and fleet management by airlines.@en

Aircraft trajectory generation is a widely addressed problem with applications including emergency trajectory generation, collision risk models, air traffic flow and capacity management or airspace design. State of the art methods to generate individual trajectories and optimise some performance or emergency criterion may lack of realism with respect to common situations implemented by air traffic controllers. On the other hand, statistical data-driven methods to generate aircraft trajectories excel at imitating operational practice but may be difficult to implement even in simulations due to aircraft performance limitations. This contribution proposes a common baseline to compare literature and bleeding-edge methods to generate air traffic trajectories. Keeping in mind that the most appropriate criterion should always depend on the targeted application, we present here an extensive set of metrics to evaluate the quality of generated trajectories, before assessing two generation methods in light of these indicators. @en

Mode S surveillance allows air traffic controllers to interrogate certain information from aircraft, such as airspeeds, turn parameters, target altitudes, and meteorological conditions. However, not all aircraft have enabled the same capabilities. Before performing any specific interrogation, the surveillance radar must acquire the transponder capabilities of an aircraft. This is obtained via the common usage Ground-initiated Comm-B (GICB) capabilities report (BDS 1,7). With this report, third-party researchers can further improve the identification accuracy of different Mode S Comm-B message types, as well as study the compliance of surveillance standards. Thanks to the OpenSky network’s large-scale global coverage, a full picture of current Mode S capabilities over the world can be constructed. In this paper, using the OpenSky Impala data interface, we first sample over one month of raw BDS 1,7 messages from around the world. Around 40 million messages are obtained. We then decode and analyze the GICB capability messages. The resulting data contain Comm-B capabilities for all aircraft available to OpenSky during this month. The analyses in this paper focus on exploring statistics of GICB capabilities among all aircraft and within each aircraft type. The resulting GICB capability database is shared as an open dataset. @en

The large amount of aircraft trajectory data publicly available through open data sources like the OpenSky Network presents a wide range of possibilities for monitoring and post-operational analysis of air traffic performance. This contribution addresses the automatic identification of operational events associated with trajectories. This is a challenging task that can be tackled with both empirical, rule-based methods and statistical, data-driven approaches. In this paper, we first propose a taxonomy of significant events, including usual operations such as take-off, Instrument Landing System (ILS) landing and holding, as well as less usual operations like firefighting, in-flight refuelling and navigational calibration. Then, we introduce different rule-based and statistical methods for detecting a selection of these events. The goal is to compare candidate methods and to determine which of the approaches performs better in each situation. @en

Instability in the movement of air masses in the atmosphere can result in turbulence. Most often, turbulence causes discomfort to passengers but it can occasionally affect their safety as well. Turbulence experienced by aircraft can be difficult to predict, especially for clear air turbulence (CAT) which occurs in the absence of any visual clues. Pilots may report turbulence when they fly through turbulent areas; their input contributes to the issuance of weather advisories (SIGMETs) that contain meteorological information concerning the safety of all aircraft. This paper presents a novel method to detect turbulence experienced by aircraft based on Mode S data, emitted by transponders in reply to BDS 6,0 requests (heading and speed reports) sent by Secondary Surveillance Radars. The method is first validated on a few flights labelled manually by the authors flying around Europe. Then, a large-scale reconstitution of turbulent areas over Europe on ten days across different seasons in 2018 is compared with SIGMETs emitted during the same time interval. This method may be an encouraging entry point for Air Navigation Service Providers so as to gain a better awareness of the turbulence situation, by simply requesting this type of information from aircraft flying in their airspace. @en