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and 10am) are more spatially dispersed. Later on in the morning and early
afternoon (from between 10am and 2pm), trips tend to be more concentrated
and spatially focussed around the CBD and the immediate surrounding
suburbs. This spatial flow pattern continues until around 5pm where after
(from 5pm to 10pm) trips begin to spread further into the suburbs but appear
less dispersed than during the morning peak hours. There is also evidence that
there are a relatively high proportion of self-contained trips that remain
relatively constant across the 24-hour period at some suburbs.
The effects of specific calendar events (i.e. weekdays, weekends, public
and school holidays) and hour on trip patterns simultaneously using an array of
flow maps. A number of specific observations can be made. First, CBD-based
trips taking place during weekends, especially between the hours of 9am to
5pm are shown to be markedly less concentrated that those occurring during
workdays. Trips taking place during the evening (i.e. after 5pm) show a
significant reduction in weekdays that is not as marked during weekends. The
effect of public holidays on the spatio-temporal patterns is very similar to
weekend patterns. Trips occurring during school holidays differ very little
from regular weekdays apart from a small reduction in the number of trips
taking place between the suburbs and the CBD during peak hours.
4. D ISCUSSIONS
Understanding the spatial patterns of transport activities have always gain
increase in importance. As GIS techniques become more established in this
area, they will enhance the analysis of transport data that seek to derive deeper
understanding of the transport pattern and underlying spatial structure and
dynamics. The development and application GIS-based techniques will
supplement the planners' toolbox. When the techniques presented in this paper
are well developed into deployable solutions their added value to the urban
and transport analysis can be fully evaluated. At this point, it would then be
possible to better respond to the transport questions to inform the future
development timely and geo-targeted policy; that could potentially enhance
planning efficiency.
The first part of this chapter has investigated the JTW dynamics in a large
region based on spatial analysis of JTW data with a focus on geographic
patterns of travel distance and travel flows. The use of JTW datasets is far
from straightforward because of complexity of the data and changes in
geography of traffic zones over time. Therefore, we utilised advanced GIS
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