Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources

Li, Max Z.; Ryerson, Megan S.

doi:10.1016/j.jairtraman.2018.12.004

Cited by 21 publications

(11 citation statements)

References 200 publications

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“…This paper is in line with authors (including Ren and Li, 2018;Burmester et al, 2018;and Li and Ryerson, 2019) who have highlighted the potential of new big data sources for aviation research in general, but de facto also includes air transport geography. Today, and once ADS-B technology has been fully implemented in aircraft, several new directions for research could be considered (provided ground-level spatial coverage is increased).…”

Section: Resultssupporting

confidence: 84%

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The magnitude of detours faced by commercial flights: A global assessment

Dobruszkes

Peeters

2019

Journal of Transport Geography

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Scholars and experts in transportation, economics, geography and environmental studies have largely assumed the distance flown by commercial planes represents the shortest route (also known as the great-circle or orthodromic route). However, in the real world, planes follow longer itineraries for various reasons. The magnitude of these detours is assessed through a large, one-week sample of actual flight traces obtained from Flightradar, which we compare with great-circle distances (n=393,360). The results suggest that the average lengthening is 7.6 %, although under conservative hypotheses and with high standard deviation. The shortest flights are proportionally more affected. They also contribute more to the global amount of extra kilometres. The geography of detours by departure airport is the consequence of a wide range of factors. As a result, considering the use of great-circle distances to feed spatial interaction models, emission (or fuel burnt) assessments or airline rankings can lead to significantly skewed outcomes. In addition, detours imposed on certain airlines for geopolitical reasons increase costs, emissions and time aboard, and could be anticompetitive.

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Section: Resultssupporting

confidence: 84%

“…However, as with most sources of big data, quantity does not mean exhaustive coverage, since not all aircraft types or all areas and airports are evenly covered. What is more, most aviation-related new big data sources are proprietary sources (Li and Ryerson, 2019). This usually involves high purchase prices, and thus inequality among scholars.…”

Section: Resultsmentioning

confidence: 99%

The magnitude of detours faced by commercial flights: A global assessment

Dobruszkes

Peeters

2019

Journal of Transport Geography

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“…Two reviews, one presented by Findlater and Bogoch (2018) illustrating how rapid movement around the globe facilitate epidemics in different viruses (e.g., Zika, SARS, Dengue) and the other by Desai et al (2019) evidencing the role of forecasting methodologies and the importance of data in outbreak events. Unfortunately, most of the aviation data is not public, having implications in reproducibility and extension of the use of these models in global disasters faced today (Li and Ryerson 2019;Meslé et al 2019).…”

Section: Airports and Air Travel In Pandemic Managementmentioning

confidence: 99%

Tracking the Wings of Covid-19 by Modeling Adaptability with Open Mobility Data

Sousa

Barata

2020

Applied Artificial Intelligence

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The lifecycle of COVID-19 pandemic curves requires timely decisions to protect public health while minimizing the impact to global economy. New models are necessary to predict the effect of mobility suppression/reactivation decisions at a global scale. This research presents an approach to understand such tensions by modeling air travel restrictions during the new coronavirus outbreak. The paper begins with an updated review on the impact of air mobility in infectious disease progression, followed by the adoption of complex networks based on semi-supervised statistical learning. The model can be used to (1) determine the early identification of infectious disease spread via air travel and (2) align the need to keep the economy working with open connections and the different dynamic of national pandemic curves. The approach takes advantage of open data and machine self-supervised statistical learning to develop knowledge networks visualization. Test cases using Hong Kong and Wuhan aerial mobility are discussed in the decisions to (1) restrict and (2) increase mobility. The approach may also be of governments use in their international cooperation policy and commercial companies that need to choose how to prioritize the reopening of international trade routes.

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“…via recurrent neural networks 9 . One problem of any data-driven approach is that many articles on aviation research solely rely on proprietary data: In a recent review investigating 200 research articles, were based on proprietary data 10 . Hence, to enable the broader applicability of machine learning applications, more publicly available data are still required.…”

Section: Introductionmentioning

confidence: 99%

Statistical characterization of airplane delays

Mitsokapas

Schäfer

Harris

et al. 2021

Sci Rep

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The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airline? Here, we present a statistical analysis of arrival delays at several UK airports between 2018 and 2020. We establish a procedure to compare both mean delay and extreme events among airlines and airports, identifying a power-law decay of large delays. Furthermore, we note drastic changes in plane delay statistics during the COVID-19 pandemic. Finally, we find that delays are described by a superposition of simple distributions, leading to a superstatistics.

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Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources

Cited by 21 publications

References 200 publications

The magnitude of detours faced by commercial flights: A global assessment

The magnitude of detours faced by commercial flights: A global assessment

Tracking the Wings of Covid-19 by Modeling Adaptability with Open Mobility Data

Statistical characterization of airplane delays

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