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12 - Air Traffic Analysis
- from PART III - MOBILITY APPLICATIONS
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- By C. Hurter, France, G. Andrienko, Germany, N. Andrienko, Germany, R.H. Güting, FernUniversität in Hagen, M. Sakr, FernUniversität in Hagen
- Edited by Chiara Renso, Stefano Spaccapietra, École Polytechnique Fédérale de Lausanne, Esteban Zimányi, Université Libre de Bruxelles
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- Book:
- Mobility Data
- Published online:
- 05 October 2013
- Print publication:
- 14 October 2013, pp 240-258
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- Chapter
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Summary
Introduction
The goal of air traffic control (ATC) is to maximize both safety and capacity, so as to accept all flights without compromising the life of the passengers or creating delays. Because air traffic is expected to double by 2030, new visualizations and analysis tools have to be developed to maintain and further improve the safety level. To do so, air traffic practitioners analyze data from the ATC activity. These multidimensional data include aircraft trajectories (3D location plus time), flight routes (ordered sequences of spatio-temporal points that represent planned routes), and meteorological data. In this chapter, we detail the relevant tasks of ATC practitioners and demonstrate recent visualization and query methods to fulfill them.
The special properties of ATC data propose new challenges and, at the same time, new opportunities of data analysis. The semantics of the data are rich because they includes the third dimension (altitude), which can be used to discover salient events such as takeoffs and landings. More semantics can be added by augmenting background data such as the traffic network and the meteorological data. ATC data sets are characterized by their large sizes, adding more challenges to the analysis. Trajectory analysis is difficult due to the data set size and to the fact that it contains many errors and uncertainties. One day's traffic over France contains about 20,000 trajectories (> 1 million records). Recording is done in a periodic manner (in our database: a radar plot, per aircraft, every 4 minutes), but a plot can be missed, or have erroneous data because of physical problems that occur at the time of recording.
3 - Trajectory Databases
- from PART I - MOBILITY DATA MODELING AND REPRESENTATION
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- By R.H. Güting, Fern Universität in Hagen, T. Behr, Fern Universität in Hagen, C. Düntgen, Fern Universität in Hagen
- Edited by Chiara Renso, Stefano Spaccapietra, École Polytechnique Fédérale de Lausanne, Esteban Zimányi, Université Libre de Bruxelles
-
- Book:
- Mobility Data
- Published online:
- 05 October 2013
- Print publication:
- 14 October 2013, pp 42-61
-
- Chapter
- Export citation
-
Summary
Introduction
In this chapter, we consider the problem of modeling and representing trajectories in the context of database systems. Since about 1995 there has been research on moving objects databases (MODs), also termed spatio-temporal databases. The general goal has been to allow one to represent moving entities in databases and to enable a user to ask all kinds of questions about such movements. This requires extensions of the DBMS data model and query language. Further, DBMS implementation needs to be extended at all levels, for example, by providing data structures for representation of moving objects, efficient algorithms for query operations, indexing and join techniques, extensions of the query optimizer, and extensions of the user interface to visualize and animate moving objects.
Moving objects databases come in two types. The first represents a set of currently moving objects. One is interested in maintaining the current locations and asking queries about current and expected near future locations. The second type maintains complete histories of movement. These are sometimes called trajectory databases and are the topic of this chapter.
Whereas spatio-temporal databases had been around for a much longer time, they supported only discrete changes of geometries over time. The emphasis in the new field of moving objects databases is to consider continuously changing geometries. Neither the position of a car on a road nor the shape and location of a hurricane changes in discrete steps; these are clearly continuous phenomena.