Geography Reference
In-Depth Information
Chapter 20
Space-Time Analytics of Tracks
for the Understanding of Patterns of Life
May Yuan and Atsushi Nara
Location-aware devices have enabled the recording of personal whereabouts at fine
spatial and temporal resolutions. These temporal sequences of personal locations
provide unprecedented opportunities to explore patterns of life through space-time
analytics of movement and stops of individuals. At a disaggregated level, patterns
of life reveal the activities and places as well as the development of routines for
individuals. At an aggregate level, patterns of life suggest potential social networks
and social hot spots for interactions. Moreover, the concept of “neighborhood” can
become personalized and dynamic with space-time analytics to identify the spatial
extent to which an individual operates and how the extent varies with temporal
granularity. This chapter starts with an overview of space-time track analysis. While
time geography has proven useful for analysis of space-time paths and space-time
constraints on human activities, its scalability to large data sets is questionable. This
chapter provides a conceptual framework and methodology for conducting space-
time analysis with a massive number of space-time tracks including over a million
points of moves and stops over the course of a year. The examples demonstrate
the usefulness of the proposed conceptual framework and methodology to distill
complex patterns of life at both disaggregate and aggregate levels that can lead
to research opportunities for space-time integration in GIScience for an improved
understanding of geography.
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