Geography Reference
In-Depth Information
In transportation research, walking behavior is usually recorded by travel diary.
Travel diaries ask respondents to keep a log of all trips made during a particular time
period, usually 1 or 2 days. A detailed travel diary includes origins and destinations,
modes of travel, durations of trips and primary activities at trip destinations.
However, walking data in the diaries are usually incomplete (Handy et al.
2002
)
and less valid (Lee and Moudon
2004
). Travel diaries typically focus on driving and
public transit rather than walking, which could inevitably lead to a lack of walking
data. In addition, the separation of walking for leisure from walking for transport is
not necessarily straightforward (Handy
2005
). Duncan and his colleagues suggests
that a global positioning system (GPS), especially when used in combination with
GIS, offers great promise in objectively measuring individual behavior in terms of
physical and transport-related activity (Duncan et al.
2009
).
In physical activity studies, self-report measures play a central role in measuring
physical activity in general and walking in particular (Johnson-Kozlow and Matt
2004
; Pereira et al.
1997
). They are economical and allow large populations to be
assessed quickly and easily (Tudor-Locke et al.
2004
). Assessments are variously
quantified as sessions and duration per week, number of miles per week, number
of blocks walked and as walking more or less with reference to others of the
same age. Many studies investigate biases and response errors in self-reported data
on physical activity (Sallis and Saelens
2000
). A growing number of studies are
utilizing objective measures of walking behavior in conjunction with self-reporting.
A common method is to utilize a device such as a pedometer or accelerometer, which
detect steps and distances travelled throughout the day (Tudor-Locke et al.
2004
).
However, the high cost of the devices limits their usage in studies with large sample
sizes. In addition, the devices alone cannot identify different built environments.
5.2.3
Specificity and Matching
Barriers are formed by spatially matching sufficiently detailed data between the
built environment and walking behavior (Cervero and Kockelman
1997
). Survey
data are usually collected at the census collector district level (Duncan et al.
2010
),
leading inevitably to a lack of built environment attributes related to walking. Taking
pedestrian networks as examples, street networks are too coarse to trace the paths
chosen by pedestrians. A true pedestrian network should incorporate formal and
informal paths, including sidewalks, laneways, pedestrian bridges and park paths
that are informal but used frequently for transit. The missing pedestrian paths in the
street network database are likely those that can greatly increase the connectivity
of separate locations in the real world. Most accessibility studies use only street
networks in their analyses, which may result in inadequacies in the description
and prediction of walking travel and induce arguments about the reliability of the
analysis result (Chin et al.
2008
).
Introducing greater specificity to models that seek to explain the impact of the
environment on behavior would greatly improve the predictability of the developed
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