Space-Time Analytics of Tracks for the Understanding of Patterns of Life - Space-Time Integration in Geography and GIScience - page 368

Fig. 20.2 Path and trajectories: Trajectories are defined through the semantic segmentation of a
path. Some parts of the path are irrelevant to the application of interest and do not belong to any
trajectory (Adapted from Spaccapietra et al. 2008 )

Fig. 20.3 Trajectories and sub-trajectories (Adapted from Lee et al. 2007 )

result from multiple activities (e.g. driving, working, shopping), and therefore, may
consist of multiple trajectories (Fig. 20.2 ). Trajectory analysis on both data sources
has been built upon descriptive and predictive analyses of trajectory descriptors,
similarity indices, clustering patterns, and individual-group dynamics (Long and
Nelson 2012 ). A suite of parameters and derivatives is being built to characterize
primitive and compound movement patterns (Dodge et al. 2008 ), which can serve
the basis for a systematic development of quantitative methods for trajectory
analysis.
Units of trajectory analysis usually are trajectories, trajectory segments (a.k.a.
sub-trajectories, Fig. 20.3 ), and stops. Measures of trajectory geometry or density
are common identifiers for clusters or outliers. Gaffney and Smyth ( 1999 ) proposed
a model-based clustering algorithm with a probabilistic mixture regression model
and the Expectation-Maximization algorithm to analyze hand movement. A similar
approach is used to analyze tracks of extratropical cyclones (Gaffney et al. 2007 ).