opensky_flights_full — OpenSky airport networks, non-commercial release (2019-2022)

Description

Monthly networks of flights between airports worldwide, from January 2019 to December 2022, derived from the crowdsourced air traffic data of the OpenSky Network, a network of more than 2500 receivers of the ADS-B and Mode S messages broadcast by aircraft. The data were compiled by Strohmeier, Olive, Lübbe, Schäfer and Lenders to illustrate the development of air traffic during the COVID-19 pandemic. This is the last release (v23.00, of May 2023) of the version of the data set with non-anonymized aircraft information, which extends to December 2022, and whose files of earlier months were corrected ("fixed after a thorough sanity check") with respect to the previous releases; the version with anonymized aircraft information and a CC BY license, which ends in December 2021, is in the entry opensky_flights. The data lists every flight seen by the network, with its origin and destination airports, which were inferred from the trajectory of the aircraft on takeoff and approach, without cross-checking with other sources.

This entry is restricted because the license of this release of the data (the OpenSky Network's General Terms of Use & Data License Agreement) does not allow distributing the data to other persons, and limits its use to non-profit research and education, commercial internal testing and evaluation, and government purposes.

Each network covers one month, and is named by it (e.g. 2022-04); the month of a flight is the (UTC) day of the last message received from it. Nodes are airports, identified by their four-letter (ICAO) codes, and a directed edge from one airport to another is weighted by the number of flights from the first to the second in that month. The individual flights are aggregated into these weighted edges (about 72 million flights over the four years, of those whose origin and destination are known). The networks of 2019 to 2021 differ from those of opensky_flights in some months (e.g. September 2019, December 2019 and September 2021), because of the corrections. Flights whose origin or destination airport could not be determined (which are many, e.g. flights that left the coverage of the network) are left out. Flights that took off and landed at the same airport (e.g. training or test flights) are kept as self-loops. Only airports with at least one flight in the month are included.

The names, positions and types of the airports come from the OurAirports database (public domain; a snapshot of January 2022), matched by their ICAO code or, failing that, by their GPS code; for airport codes that are not found there, these properties are empty (NaN for the coordinates).

The networks have the following properties:

Nodes: code, the four-letter code of the airport (as given by OpenSky); name, the name of the airport; lat and lon, its latitude and longitude; type, the type of airport in OurAirports (e.g. large_airport, small_airport, heliport); country, the ISO 3166-1 code of its country.
Edges: weight, the number of flights from the origin to the destination airport in the month.

Tags

Transportation Airport Weighted Temporal Metadata

Citation

M. Strohmeier, X. Olive, J. Lübbe, M. Schäfer, V. Lenders, "Crowdsourced air traffic data from the OpenSky Network 2019–2020." Earth System Science Data 13(2), 357-366 (2021) 10.5194/essd-13-357-2021 Sci-Hub

Upstream URL OK

https://doi.org/10.5281/zenodo.7923702
https://github.com/davidmegginson/ourairports-data

Upstream license

Restricted access. Upstream does not permit data redistribution, hence the network files cannot be downloaded without authorization. See here how to gain access.

Networks

Tip: click on a column header to sort the list, or hover over it for a description.

Column legend

$\left<k\right>$: Mean degree
$\sigma_k$: Standard deviation of the degrees
$\lambda_h$: Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$: Random walk mixing time
$r$: Degree assortativity
$c$: Global clustering coefficient
$\oslash$: (Pseudo-) diameter
$S$: Relative size of the largest component
NPs: Node properties
EPs: Edge properties

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
2019-01	10,464	136,897	13.08	69.45	149.31	67.99	0.00	0.22	12	0.99	Directed	Unipartite	code name lat lon type country	weight	640 KiB	1.1 MiB	1.0 MiB	927 KiB
2019-02	10,670	134,126	12.57	67.48	146.09	64.16	0.01	0.22	12	0.99	Directed	Unipartite	code name lat lon type country	weight	645 KiB	1.1 MiB	1.0 MiB	927 KiB
2019-03	10,752	143,400	13.34	68.64	146.16	115.48	0.02	0.22	11	0.99	Directed	Unipartite	code name lat lon type country	weight	666 KiB	1.1 MiB	1.1 MiB	961 KiB
2019-04	10,211	146,457	14.34	71.73	151.30	24.76	0.03	0.23	9	0.99	Directed	Unipartite	code name lat lon type country	weight	641 KiB	1.1 MiB	1.1 MiB	945 KiB
2019-05	9,960	158,822	15.95	77.23	157.36	25.56	0.02	0.23	9	1.00	Directed	Unipartite	code name lat lon type country	weight	655 KiB	1.1 MiB	1.1 MiB	972 KiB
2019-06	10,337	171,890	16.63	77.86	155.47	22.87	0.03	0.23	9	1.00	Directed	Unipartite	code name lat lon type country	weight	688 KiB	1.2 MiB	1.2 MiB	1.0 MiB
2019-07	10,847	185,815	17.13	80.80	156.45	24.11	-0.01	0.21	10	1.00	Directed	Unipartite	code name lat lon type country	weight	732 KiB	1.3 MiB	1.3 MiB	1.1 MiB
2019-08	11,289	199,758	17.69	82.93	165.84	26.04	0.03	0.22	9	1.00	Directed	Unipartite	code name lat lon type country	weight	775 KiB	1.4 MiB	1.4 MiB	1.1 MiB
2019-09	11,434	197,520	17.27	83.98	169.45	24.65	0.02	0.22	9	1.00	Directed	Unipartite	code name lat lon type country	weight	768 KiB	1.4 MiB	1.3 MiB	1.1 MiB
2019-10	11,109	191,455	17.23	84.48	167.31	25.80	0.01	0.22	8	1.00	Directed	Unipartite	code name lat lon type country	weight	747 KiB	1.3 MiB	1.3 MiB	1.1 MiB
2019-11	10,803	174,024	16.11	79.45	159.66	27.02	0.01	0.22	10	0.99	Directed	Unipartite	code name lat lon type country	weight	712 KiB	1.2 MiB	1.2 MiB	1.0 MiB
2019-12	11,167	173,454	15.53	78.56	160.08	29.80	0.00	0.21	11	0.99	Directed	Unipartite	code name lat lon type country	weight	719 KiB	1.3 MiB	1.2 MiB	1.1 MiB
2020-01	11,067	166,466	15.04	76.75	157.13	29.42	0.00	0.22	10	0.99	Directed	Unipartite	code name lat lon type country	weight	708 KiB	1.2 MiB	1.2 MiB	1.0 MiB
2020-02	11,277	181,146	16.06	79.02	160.99	31.38	0.03	0.22	12	1.00	Directed	Unipartite	code name lat lon type country	weight	742 KiB	1.3 MiB	1.3 MiB	1.1 MiB
2020-03	11,214	165,727	14.78	73.21	153.83	29.49	0.03	0.21	10	0.99	Directed	Unipartite	code name lat lon type country	weight	711 KiB	1.2 MiB	1.2 MiB	1.0 MiB
2020-04	10,661	114,568	10.75	48.77	108.69	42.02	0.08	0.20	12	0.99	Directed	Unipartite	code name lat lon type country	weight	606 KiB	1010 KiB	970 KiB	860 KiB
2020-05	11,235	159,596	14.21	62.09	130.94	51.38	0.08	0.20	12	1.00	Directed	Unipartite	code name lat lon type country	weight	707 KiB	1.2 MiB	1.2 MiB	1.0 MiB
2020-06	11,777	192,064	16.31	71.85	149.36	54.65	0.06	0.20	10	1.00	Directed	Unipartite	code name lat lon type country	weight	775 KiB	1.3 MiB	1.3 MiB	1.1 MiB
2020-07	12,182	218,656	17.95	77.84	157.14	57.62	0.04	0.20	10	0.99	Directed	Unipartite	code name lat lon type country	weight	839 KiB	1.5 MiB	1.5 MiB	1.2 MiB
2020-08	12,179	225,397	18.51	80.46	162.76	56.14	0.05	0.21	10	1.00	Directed	Unipartite	code name lat lon type country	weight	845 KiB	1.5 MiB	1.5 MiB	1.3 MiB
2020-09	12,264	219,896	17.93	79.38	160.79	57.01	0.05	0.21	11	1.00	Directed	Unipartite	code name lat lon type country	weight	840 KiB	1.5 MiB	1.5 MiB	1.2 MiB
2020-10	12,182	219,848	18.05	82.86	170.36	51.17	0.04	0.21	8	1.00	Directed	Unipartite	code name lat lon type country	weight	830 KiB	1.5 MiB	1.5 MiB	1.2 MiB
2020-11	11,735	196,014	16.70	77.05	161.08	49.23	0.05	0.20	9	1.00	Directed	Unipartite	code name lat lon type country	weight	786 KiB	1.4 MiB	1.4 MiB	1.1 MiB
2020-12	11,444	179,659	15.70	76.19	162.50	49.45	0.05	0.21	11	0.99	Directed	Unipartite	code name lat lon type country	weight	745 KiB	1.3 MiB	1.3 MiB	1.1 MiB
2021-01	11,549	172,328	14.92	73.76	160.44	66.68	0.05	0.21	13	0.99	Directed	Unipartite	code name lat lon type country	weight	733 KiB	1.3 MiB	1.2 MiB	1.1 MiB
2021-02	11,685	165,364	14.15	70.55	158.82	106.44	0.07	0.22	10	0.99	Directed	Unipartite	code name lat lon type country	weight	730 KiB	1.2 MiB	1.2 MiB	1.0 MiB
2021-03	12,231	214,865	17.57	82.73	177.25	67.46	0.07	0.22	10	1.00	Directed	Unipartite	code name lat lon type country	weight	828 KiB	1.5 MiB	1.5 MiB	1.2 MiB
2021-04	12,559	230,449	18.35	85.54	181.80	57.21	0.07	0.22	11	0.99	Directed	Unipartite	code name lat lon type country	weight	863 KiB	1.5 MiB	1.5 MiB	1.3 MiB
2021-05	12,762	245,360	19.23	88.98	187.41	55.86	0.07	0.22	10	0.99	Directed	Unipartite	code name lat lon type country	weight	897 KiB	1.6 MiB	1.6 MiB	1.3 MiB
2021-06	13,054	265,158	20.31	93.67	193.11	49.81	0.05	0.22	11	0.99	Directed	Unipartite	code name lat lon type country	weight	935 KiB	1.7 MiB	1.7 MiB	1.4 MiB
2021-07	13,269	284,004	21.40	98.61	200.21	64.62	0.03	0.22	11	0.99	Directed	Unipartite	code name lat lon type country	weight	980 KiB	1.8 MiB	1.8 MiB	1.5 MiB
2021-08	13,132	270,915	20.63	95.81	194.74	66.51	0.04	0.22	10	0.99	Directed	Unipartite	code name lat lon type country	weight	957 KiB	1.7 MiB	1.7 MiB	1.4 MiB
2021-09	12,766	277,446	21.73	98.15	192.78	45.02	0.03	0.21	10	1.00	Directed	Unipartite	code name lat lon type country	weight	949 KiB	1.8 MiB	1.7 MiB	1.5 MiB
2021-10	12,827	272,166	21.22	102.06	202.60	54.19	0.00	0.21	10	1.00	Directed	Unipartite	code name lat lon type country	weight	935 KiB	1.7 MiB	1.7 MiB	1.4 MiB
2021-11	12,463	233,667	18.75	91.70	186.24	48.28	0.02	0.21	10	0.99	Directed	Unipartite	code name lat lon type country	weight	867 KiB	1.6 MiB	1.5 MiB	1.3 MiB
2021-12	12,417	211,759	17.05	87.73	183.71	51.84	0.01	0.21	12	0.99	Directed	Unipartite	code name lat lon type country	weight	839 KiB	1.5 MiB	1.5 MiB	1.2 MiB
2022-01	12,361	211,154	17.08	85.29	180.78	48.17	0.03	0.22	9	1.00	Directed	Unipartite	code name lat lon type country	weight	831 KiB	1.5 MiB	1.5 MiB	1.2 MiB
2022-02	12,320	215,948	17.53	86.16	183.66	43.27	0.04	0.22	10	1.00	Directed	Unipartite	code name lat lon type country	weight	829 KiB	1.5 MiB	1.5 MiB	1.2 MiB
2022-03	12,853	252,623	19.65	94.64	197.42	40.05	0.04	0.22	10	1.00	Directed	Unipartite	code name lat lon type country	weight	911 KiB	1.7 MiB	1.6 MiB	1.4 MiB
2022-04	13,047	261,235	20.02	95.89	199.38	40.53	0.03	0.22	11	1.00	Directed	Unipartite	code name lat lon type country	weight	935 KiB	1.7 MiB	1.7 MiB	1.4 MiB
2022-05	13,382	279,656	20.90	99.04	201.69	40.01	0.03	0.22	10	1.00	Directed	Unipartite	code name lat lon type country	weight	981 KiB	1.8 MiB	1.8 MiB	1.5 MiB
2022-06	13,580	292,316	21.53	99.63	201.39	40.51	0.04	0.22	11	1.00	Directed	Unipartite	code name lat lon type country	weight	1004 KiB	1.9 MiB	1.9 MiB	1.5 MiB
2022-07	13,651	302,246	22.14	100.32	198.41	37.46	0.02	0.21	11	1.00	Directed	Unipartite	code name lat lon type country	weight	1.0 MiB	1.9 MiB	1.9 MiB	1.6 MiB
2022-08	13,511	290,345	21.49	98.52	198.54	38.70	0.04	0.22	10	0.99	Directed	Unipartite	code name lat lon type country	weight	997 KiB	1.8 MiB	1.8 MiB	1.5 MiB
2022-09	13,509	286,661	21.22	98.72	197.17	52.54	0.03	0.21	11	1.00	Directed	Unipartite	code name lat lon type country	weight	992 KiB	1.8 MiB	1.8 MiB	1.5 MiB
2022-10	13,475	290,783	21.58	100.74	203.80	36.37	0.04	0.22	11	1.00	Directed	Unipartite	code name lat lon type country	weight	998 KiB	1.8 MiB	1.8 MiB	1.5 MiB
2022-11	12,851	242,838	18.90	93.07	194.95	36.88	0.03	0.22	11	1.00	Directed	Unipartite	code name lat lon type country	weight	898 KiB	1.6 MiB	1.6 MiB	1.3 MiB
2022-12	12,502	213,485	17.08	87.68	186.37	37.32	0.03	0.22	11	1.00	Directed	Unipartite	code name lat lon type country	weight	839 KiB	1.5 MiB	1.5 MiB	1.2 MiB

Ridiculograms^*

^* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.