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functions can be applied such as Sum-of-Pairs Distance (Li and Goodchild
2012
),
Dynamic Time Warping (Li et al.
2011
), and Longest Common Subsequence (Böhm
et al.
2011
).
In our case study, we have employed a simple similarity measure, Sum-of-
Closest-Pairs Distance (SCPD). In this measurement, we find the closest pair of
points from two stop point datasets and calculate the sum of the distance between
them. Given two sets of stop points A and B, SCPD is calculated as follows:
X
n
d
a
i
;b
j
SCPD
.A; B/
D
min
a
i
2
A;b
j
2
B
i
D
1
Figure
20.8
shows similarity distance comparisons for one day of stops to the
previous day over a 6-month period (5/1/2009-10/31/2009). In this analysis, we use
a duration threshold of 5 min in order to ignore very short stop events such as stops
at traffic lights. The unit of similarity cost is measured in kilometer and a lower
distance value denotes similar stop-events between 2 days. The color of data points
represents a day of week, and it reveals weekly pattern of extracted stop-events. For
example, Saturday's stop events are quite different from Friday's throughout the
time period. In addition, Thursday's are also different from Wednesday. Moreover,
stops between Saturday and Wednesday are relatively similar (low distance in the
box
a
in Fig.
20.8
). This regularity corresponds to the 5-day and 2-day weekly
pattern suggesting that the individual may have a regular weekly work pattern. In
fact, stop points for those 5 days (Saturday to Wednesday) are found in the area A
in Fig.
20.7
and not the other 2 days (Thursday and Friday), which implies that the
location could be his/her work place.
Alternatively, space can serve as the first order structure for analysis of patterns
of life, investigating location-focused frequency and duration of stops distribution
over time is a useful exploratory analysis. The bar chart in Fig.
20.9
visualizes
stop-events frequency and duration distribution for two locations (A, B) in Fig.
20.7
.
Fig. 20.8
Individual stop similarity over a 6-month period
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