Abstract
Much research has been published about trajectory management on the ground or at the sea, but compression or indexing of flight trajectories have usually been less explored. However, air traffic management is a challenge because airspace is becoming more and more congested, and large flight data collections must be preserved and exploited for varied purposes. This paper proposes 3DGraCT, a new method for representing these flight trajectories. It extends the GraCT compact data structure to cope with a third dimension (altitude), while retaining its space/time complexities. 3DGraCT improves space requirements of traditional spatio-temporal data structures by two orders of magnitude, being competitive for the considered types of queries, even leading the comparison for a particular one.
This work was funded in part by EU H2020 MSCA RISE BIRDS: 690941; MINECO-AEI/FEDER-UE: TIN2016-78011-C4-1-R; MINECO-CDTI/FEDER-UE CIEN IDI-20141259; MINECO-CDTI/FEDER-UE CIEN IDI-20150616; MINECO-CDTI/FEDER-UE INNTERCONECTA ITC-20161074; Xunta de Galicia/FEDER-UE ED431C 2017/58 and ED431G/01.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
From now on, we will refer to them simply as objects or moving objects.
- 2.
Note that only shaded structures are used to encode the snapshot, the other ones are used for illustration purposes.
- 3.
\(\langle z,x,y \rangle \) notation indicated that these three values are packed in a 32-bit integer.
- 4.
References
de Bernardo, G., Álvarez-García, S., Brisaboa, N.R., Navarro, G., Pedreira, O.: Compact querieable representations of raster data. In: Kurland, O., Lewenstein, M., Porat, E. (eds.) SPIRE 2013. LNCS, vol. 8214, pp. 96–108. Springer, Cham (2013). https://doi.org/10.1007/978-3-319-02432-5_14
Botea, V., Mallett, D., Nascimento, M.A., Sander, J.: PIST: an efficient and practical indexing technique for historical spatio-temporal point data. GeoInformatica 12(2), 143–168 (2008)
Brisaboa, N., Ladra, S., Navarro, G.: DACs: bringing direct access to variable-length codes. Inf. Process. Manag. 49(1), 392–404 (2013)
Brisaboa, N.R., Gómez-Brandón, A., Navarro, G., Paramá, J.R.: GraCT: a grammar based compressed representation of trajectories. In: Inenaga, S., Sadakane, K., Sakai, T. (eds.) SPIRE 2016. LNCS, vol. 9954, pp. 218–230. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46049-9_21
Brisaboa, N.R., Ladra, S., Navarro, G.: Compact representation of web graphs with extended functionality. Inf. Syst. 39(1), 152–174 (2014)
Cudre-Mauroux, P., Wu, E., Madden, S.: Trajstore: an adaptive storage system for very large trajectory data sets. In: Proceedings of the IEEE 26th International Conference on Data Engineering (ICDE 2010), pp. 109–120 (2010)
Deng, K., Xie, K., Zheng, K., Zhou, X.: Trajectory indexing and retrieval. In: Zheng, Y., Zhou, X. (eds.) Computing with Spatial Trajectories, pp. 35–60. Springer, New York (2011). https://doi.org/10.1007/978-1-4614-1629-6_2
Douglas, D.H., Peuker, T.K.: Algorithms for the reduction of the number of points required to represent a line or its caricature. Can. Cartogr. 10(2), 112–122 (1973)
Gog, S., Beller, T., Moffat, A., Petri, M.: From theory to practice: plug and play with succinct data structures. In: Gudmundsson, J., Katajainen, J. (eds.) SEA 2014. LNCS, vol. 8504, pp. 326–337. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07959-2_28
Jacobson, G.: Space-efficient static trees and graphs. In: IEEE Symposium on Foundations of Computer Science (FOCS), pp. 549–554 (1989)
Knuth, D.E.: Efficient representation of perm groups. Combinatorica 11, 33–43 (1991)
Larsson, N.J., Moffat, A.: Off-line dictionary-based compression. Proc. IEEE 88(11), 1722–1732 (2000)
Nascimento, M.A., Silva, J.R.O.: Towards historical R-trees. In: Proceedings of the 1998 ACM Symposium on Applied Computing. SAC 1998, pp. 235–240. ACM (1998)
Navarro, G.: Compact Data Structures - A Practical Approach. Cambridge University Press, Cambridge (2016)
Nibali, A., He, Z.: Trajic: an effective compression system for trajectory data. IEEE Trans. Knowl. Data Eng. 27(11), 3138–3151 (2015)
Schäfer, M., Strohmeier, M., Lenders, V., Martinovic, I., Wilhelm, M.: Bringing up OpenSky: a large-scale ADS-B sensor network for research. In: Proceedings of the 13th International Symposium on Information Processing in Sensor Networks. IPSN 2014, pp. 83–94. IEEE Press, Piscataway (2014). http://dl.acm.org/citation.cfm?id=2602339.2602350
Tao, Y., Papadias, D.: MV3R-tree: a spatio-temporal access method for timestamp and interval queries. In: 2001 Proceedings of the 27th International Conference on Very Large Data Bases, VLDB, pp. 431–440 (2001)
Trajcevski, G., Cao, H., Scheuermann, P., Wolfson, O., Vaccaro, D.: On-line data reduction and the quality of history in moving objects databases. In: Proceedings of the Fifth ACM International Workshop on Data Engineering for Wireless and Mobile Access, pp. 19–26 (2006)
Vazirgiannis, M., Theodoridis, Y., Sellis, T.K.: Spatio-temporal composition and indexing for large multimedia applications. ACM Multimed. Syst. J. 6(4), 284–298 (1998)
Wandelt, S., Sun, X.: Efficient compression of 4D-trajectory data in air traffic management. IEEE Trans. Intell. Transp. Syst. 16(2), 844–853 (2015)
Wandelt, S., Sun, X., Fricke, H.: ADS-BI: compressed indexing of ADS-B data. IEEE Trans. Intell. Transp. Syst. 99, 1–12 (2018)
Wandelt, S., Sun, X., Gollnick, V.: SO6C: compressed trajectories in air traffic management. Air Traffic Control Q. 22(2), 157–178 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix
Appendix
The datasets used in our experimentaion have been obtained from the OpenSky NetworkFootnote 4. We have chosen ADS-B messages broadcasted by aircrafts of 30 different airlines and describe flights between 30 European airports:
-
Airlines (ICAO code): AEA, AEE, AFR, AUA, AZA, BAW, BEE, BEL, BER, DLH, EIN, EWG, EZS, EZY, FDX, FIN, GWI, IBE, IBK, IBS, KLM, LOT, NAX, NLY, RYR, SAS, SHT, SWR, TAP, and VLG.
-
Airports (ICAO code): EBBR, EDDF, EDDK, EDDL, EDDM, EDDT, EFHK, EGCC, EGKK, EGLL, EGPH, EGSS, EHAM, EIDW, EKCH, ENGM, EPWA, ESSA, LEBL, LEMD, LEPA, LFPG, LFPO, LGAV, LIMC, LIRF, LOWW, LPPT, LSGG, and LSZH.
ADS-B messages were captured from 2017-01-02 to 2017-01-31, and sampled as follows:
-
1day : 2017-01-02.
-
1week: 2017-01-02 – 2017-01-08.
-
2weeks: 2017-01-02 – 2017-01-15.
-
1month: 2017-01-02 – 2017-01-31.
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Brisaboa, N.R., Gómez-Brandón, A., Martínez-Prieto, M.A., Paramá, J.R. (2018). 3DGraCT: A Grammar-Based Compressed Representation of 3D Trajectories. In: Gagie, T., Moffat, A., Navarro, G., Cuadros-Vargas, E. (eds) String Processing and Information Retrieval. SPIRE 2018. Lecture Notes in Computer Science(), vol 11147. Springer, Cham. https://doi.org/10.1007/978-3-030-00479-8_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-00479-8_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00478-1
Online ISBN: 978-3-030-00479-8
eBook Packages: Computer ScienceComputer Science (R0)