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Figure 12.1 Factors of choosing among the methods of trajectory analysis.
subsets using convenient views and simple mouse interaction. Visual analytics
provide a rich tool box of data transformations and visualizations that help a
human analyst exploring complex movement events in the data. Moving object
database (MOD) defines query operators accessible to the user through textual
query languages. They are able to perform complex computations over large
data sets efficiently. According to the analysis task, the experience of the human
doing the analysis, and the data set size, any of these three analysis methods (or
a combination of them) can be chosen. This is illustrated in Figure 12.1 .
Direct manipulation is good for having a first look at the data. It is intuitive to
use. Visual analytics provides more sophisticated transformations and aggrega-
tions, and thus it is able to process larger data sets, and to performdeeper analysis.
Human expertise is, however, a deciding factor for good analysis results. MOD
queries are mandatory for complex computations such as pattern matching. The
user must however know exactly what he or she is looking for, and how to
precisely describe it in terms of the MOD query language.
Throughout this chapter we will demonstrate each of these analysis methods,
in the context of real tasks and using a real data set. The motivation for the
analysis and the description of the data set are presented in Sections 12.2 and 12.3
respectively. Direct manipulation is demonstrated in Section 12.4 . Section 12.5
demonstrates the use of visual analytics to explore movement events, such as
landings and takeoffs, and to derive useful statistics from them. Finally Section
12.6 explains a MOD query operator that is able to match complex patterns in
ATC data, such as missed approaches and stepwise descents.
12.2 Motivation
Aircraft trajectories are monitored and recorded by ground radar. They are
displayed in real time on radar screens. This data is essential for air traffic
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