chapter one – introduction · 2013-04-11 · chapter one – introduction . 1.1 summary of the...
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Chapter One – Introduction
1.1 Summary of the topic
Increasingly, the topic of health has become more and more eminent in our
society and daily lives. Today, jargons include healthy beings, balanced life,
good diet and healthy city are frequently used everywhere. This phenomenon is
a shift from the legacy of consumerism and materialism, where the focus, more
or less, is about consuming and consuming more. As such, we mould our
physical environment accordingly, consuming more resources and land of the
earth. Hence, we build and erase paying little attention to the externalities that
may be affected. As time passes, evidences have shown such behaviour will
eventually affects us and the longevity of our survival. This is when we begin a
new chapter of legacy – healthy city.
Walking is a hot topic in the agenda of healthy city as it by itself is a transport
mode, and virtually cost nothing. Arguably, walking can yield benefits
environmentally, economically and socially. This thesis is not advocating people
to destroy their cars once and for all and revive walking as the mean to get to
places, like in the medieval time. Such would cost too much time and cost
considered the size and layout of our modern city today. As such, in today’s
world, it is considered that walking is only viable if it is combined with a fast
transport mode, which should also be environmental-friendly. An example of this
is walking and getting on commuter railway, which is very fast compared with a
number of public transports available in New South Wales. In actual fact,
walking as an inter-mode to a public transport station constitute the largest
proportion of walking trips t in Sydney in the year 1991 and 2001, according to a
joint study by Transport Population Data Centre, NSW Department of
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Infrastructure Planning and Natural Resources and NSW Centre for Physical
Activity and Health (2005).
Walk trips by purpose on an average weekday (Corpuz, Hay & Merom 2005)
This thesis envisages gaining insights on walking as an intermodal transport. In
the realm of town planning, understanding the influence of the built and natural
environment has on people making their choice to walk to a public transport
station is crucial in the process of city making. Railway stations are examined in
this instance. Investigation will be carried out to find out the optimum walking
distance to a train station and the strength of the relationship between the
physical environments and walking distance. The results will be a hope for
creating a better city for tomorrow - one that invites walking and the use of
public transport, thus helping people to become more active.
1.2 Importance of topic
Hardly anybody dwell into the nexus of walking and public transport, yet walking
and public transport have frequently been interlinked in health and planning
literatures without more sophisticated analysis. Evidence of such negligence can
be seen from a statement which was found in the design guideline published by
the Heart Foundation of Australia (2004):
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“Planners play an essential role in planning, designing and regulating the
environments in which we live. Well planned neighbourhoods can increase the
number of people who walk to…facilities and public transport.”
However, how it can be achieved exactly has not really been uncovered. To
make such to become a reality require understanding and recognising walking
as a mode before any designing to take place. Understanding the matter helps
planners make cities and towns that are encouraging to walk, especially to train
stations. It is important to increase that understanding in the any context. The
matter is urgent at present as the majority of the population are still choosing to
travel on their automobiles for their normal daily trips, causing damages to the
already deteriorating environment.
Proportion of trips by purpose and mode on an average weekday, 1999 and 2006
(Transport Data Centre 2008)
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Proportion of trips by mode and age group on an average weekday 1999 and 2006
(Transport Data Centre 2008)
The findings from the 2006 household travel survey, recorded by the Transport
Data Centre (2008), show that automobile still dominates all category of travel
by a majority in the year 1999 and 2006. This is in spite of age differences. Private
vehicle travel accounted for over 50% of total travel in both 1999 and 2006 and
across all age groups. Our reliance on private vehicular transport has been
increasing rather than decreasing during this six year period from 1999 to 2006.
During the same period, public transport usage had decreased slightly across all
age groups except in the age group of 21-30.
We cannot afford a further drop in public transport patronage and further
increase of automobile usage as the statistics have shown no sign of reversing
travel pattern. Planning our cities and towns that are transit oriented is believed
to have significant impact on the propensity to walk and how far they walk.
Such strategy is very important to be examined as numerous studies have shown
people living far from a public transport stop are highly likely to travel with their
automobile instead of choosing to walk to get to the public transport stop. This is
illustrated in the next diagram.
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(Belden Russonello & Stewart Research and Communication 2004)
According to Belden Russonello & Stewart 2004, the general American
communities are concerned about the walking distance to public transport
station. It is ranked just after the issues of housing for low incomes. This study
further hints the need for better understanding of what really is the optimum
walking distance that people will walk to get to the transport stop. This thesis
addresses this very issue by examining the theoretic walking distance suggested
by scholars and the walking distance that people will more likely to walk in a
quantitative research conducted. The results will be important for transport and
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urban planning. It is envisaged that the results will help planners and politicians
to make decisions that will ultimately reduce the necessity of private vehicular
travel in cities.
1.3 Specific of topic
The term ‘ped-shed’ refers to the walkable catchment within an actual area to
which people are very likely to walk to get to a centre. Studies have found that
the acceptable ped-shed for any centre to be 5 min walking distance and 10
min for major transport stop such as railway station. This is the generally
accepted figure adopted both in Australia and the United States. This finding is
important as it has implications on transport and land use planning. However,
there are other researches which suggested other figures.
According to a U.S. Smart Growth Agency (2008), it was reported that, in
general circumstances, most Americans are willing to walk up to about 150
metres, 40% would walk 300 metres and only a dreadful 10% would walk a
distance of 800 metres.
For intermodal walking, the 1996 National Personal Transportation Study (Smart
Growth 2008) showed that only around 10% of residents living within 400 metres
of a public transport stop used it to get to work and the figure drops to 3.8% for
those living between 400 to 2000 metres, indicating probably less than 3.8% used
the public transport in the distances between 400 and 800 metres from the
transport stop. This is opposed to Pushkarev and Zupan’s remark (1980) of
walking distance of 800 metres as the rail catchment.
Different researchers from different places would have different view on the
actual figures. For example, Goodman and Tolley (in Tolley 2003) have shown
that acceptable walking distance of up to 1.6 km and in some circumstances
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up to 2 km. This extended walking distance figure has been proven true in some
European cities.
While different researches have different figures, the New South Wales
Government has more or less adopted figures similar to the researches from the
America. This could be due to similarity of our urban landscape setting – one
that is vast and extremely auto-oriented. Figures can be seen from the planning
guideline published by the Department of Planning (2004), where we see the
NSW government adopting a circle of radius 400 metres or 5 minute walk
around a centre and 800 metres or 10 minute walk around a public transport
stop to be walkable.
Besides having a walkable figure, our Government also advocates good
environment will induce more walk trips. The NSW Premier’s Council for Active
Living (2008) believed that “design considerations have the potential to
positively impact individual and community health and wellbeing”. Design
considerations include mixed use, higher densities, walking routes and attractive
environment. This is also emphasized by Health Foundation of Australia, in a
design guideline which they received an award for in 2004. However, again,
both have been advocating design as a factor but not giving insights as to how
potent and effective good environment could influence people choosing to
walk.
Despite statistically differences on an optimum walking distance, some
researches concluded with remarks that the physical characteristics of the
environment would have significant impact on walking behaviour. Those
characteristics can fall into density, diversity and design categorically. Careful
considerations of these components will make up an environment that most
people will walk and for a longer distance.
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If the environment is to be proven significant in whether people choose to walk,
then planners have the responsibility to shape the towns and cities in such
fashion that will encourage us all to walk. This will be explored in more detailed
in Chapter 2.
1.4 Hypotheses
There will be three main categorical hypotheses in this thesis, namely density,
diversity and design.
Density hypothesis - The higher the residential density, the more likely a
person will walk for longer distance
The higher the residential density means that more people will be on the street,
making the streetscape more celebrated and vibrant. More people on the
street allow the streetscape to be less homogeneity and feel safer. The
relationship is exploded in Chapter 2.
Diversity hypothesis - The more satisfactory the level of mixed use, he/she will
walk for longer distance
Mix use refers to the diversity of function a place can serve. Commonly refers to
the mixing of retail/commercial/services with or in proximity to residential
development. This will be discussed further in Chapter 2.
Design - The better the aesthetic of the place and street connectivity, the
longer a person will walk
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Most of us would want to travel as directly as possible and seeing things that are
aesthetically pleasing. The different aspects of design will be explained in
detailed in Chapter 2.
The results will show how significance these environmental variables are to how
far they walk and provide a comparison to the figures disclose from different
literatures and government agencies. Some socioeconomic details will also be
gathered for analysis, however, these variables will not be analysed to the
extent of the environmental variables.
1.5 Layout of thesis
The chapters that follow are the results of the much research and analysis
carried out to determine if the hypotheses are correct. Chapter 2 is the
examination of past literature. Chapter 3 looks at the methods that were
considered and used for this research. Chapter 4 outlines the results found from
the primary data that was collected. Chapter 5 discusses the results. Chapter 6
seeks to promote another form of urban landscape by providing examples.
Chapter 7 concludes this thesis with a reflection on the topic.
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Chapter Two – Literature Review
2.1 The Rise and Dawn of Automobile
Since automobile was invented in the 1880’s, it has become increasingly
popular for over a century. The automobile outlasted the Great Depression in
the 1930’s and two World Wars. However, not only the automobile did not fade
away, it became even more appealing and effective to use as the cost of
owning one dropped. Eventually, it became a product some people see as a
necessity rather than luxury. Specialization of towns and suburbs in our cities only
made automobile more appealing.
After a century, people are starting to realise the adversaries that the
automobile is causing us. The realisation was mainly induced by the vast number
of literatures opposing its further use. Some called for significant cut for its use,
while some suggested an end to it to cease the great damage it is causing the
environment. This chapter will provide some background knowledge to the
impact automobile had caused in different aspects and the reasons to find
alternative mode of travel in modern cities. This knowledge will help us to
understand the rationale to revive walking as some means of transport
Europe, a continent about the same size of Australia, is the origin where most of
the early settlers of Australia came from. Australia and Europe shared a lot of
commonalities in the past and present, yet in terms of transport planning,
Europeans leap a big gap ahead of Australia. This is evident when comparing
transport statistics from Australian cities with European cities. According to
Newman (1992), Australians consumed gasoline three times more, use less
transport, four times less walking and cycling, over 50% more parking our city
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cores and four times less dense urban form than the European cities. These
results provided crucial indication about how Australian cities performed in
targeting automobile use. The differences show that although our cities are
considered as developed cities, we definitely are not one in terms of
transportation.
Proportion of trips by mode on average weekday (Transport Data Centre 2008)
In the graph above, we see evidence of automobile being the most dominating
transport mode (‘Total Vehicle’) from 1991 to 2006 in Sydney. A percentage of
70.1 was recorded in the year 2001, an increase of 3.2% from 1991 and then
dropped slightly to 69.5% in the year 2006, an increase of 2.6% from 1991. This
increase occurred in spite of rising concerns of automobile from around the
world.
Australian cities will soon have to bear the costs for the increased automobile
usage. There have been studies on the economic, environmental and social
costs that automobile brought to us. These costs are translated in the following
table.
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Congestion is a waste of time and space, which costs.
Provision for additional infrastructures for urban sprawl suburbs
Price of an automobile can bar some from accessing economic and social benefits which require private transportation
Economical Costs
Automobiles cause public transport to run with unsustainable funds and they may eventually fade out
Pollutions include air, greenhouse gas and noise pollution
Resources required by automobile like petrol and gas will soon be depleted
Millions of unwanted automobile materials require disposal solution
Chunks are lands are loss for building roads and auto oriented suburban
Environmental Costs
Automobile excludes the poorer and disabled population
Automobile foster social separation and isolation
Social Costs
Synthesis from Grava (2003) and Newman (1992)
Automobile causes loss of public spaces and social interaction
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Many, including planners, still do not understand the full extent of the
implications of automobile use. The economic, environmental and social
impacts that automobile causes, as indicated, are enormous. Like early in the
twentieth century, interconnection was made between public health and urban
planning as heavy industries affect public health, we urgently need today to
draw the same connection only that this time it is the automobile. This
connection was translated to the healthy city initiatives in which part of it fosters
walkable neighbourhood and public transport. Walking has been mentioned in
the initiatives as a mean to reduce automobile uses. In the next chapter, we
look into the fundamentals of walk as a transport mode.
2.2 Walking – popular and unpopular
“Walking is the most natural form of physical activity and our most basic mode
of transport. A comprehensive review of the subject by the originator of the
exercise/health relationship concluded that ‘walking is the nearest activity to
perfect exercise’”. (Cavill in Tolley 2003)
Walking is healthy and we all walk. Any trip by any means includes at least a
small distance covered on foot at the beginning and end of each journey.
Walking is the most basic urban transport mode that has allowed cities to
operate. However, its role has been eroded with the introduction of mechanical
means of transportation, especially in the Australian and American communities.
Evidence of this can be found in the negative trend in the percentage of
people who walk to their destinations in Sydney presented below:
Year Growth 2004 – 05 - 0.9% 2005 – 06 - 1.7%
Transport Data Centre (2008)
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We look in turn some of the possible limits of walking that may have led to the
negative trend. A benefits and limits table is listed below:
Benefits and Limits of Walking
Benefits Limits
The walking mode involves very little
expense, either public or private.
Human does become tired, rather
quickly. Studies shows acceptable
access distance to a transit station on
foot is 400m.
Health benefits; yet walking is the most
basic form of exercise
Speed: For short distances, the slow
pedestrian speed does not matter, but
it becomes a factor with longer trips.
Availability: The mode is always present
and ready for use (within reason).
Adverse weather will reduce
considerably any propensity for
walking.
Certainty: A pedestrian is in direct
contact with the surrounding
environment so are others nearby.
Pedestrians have limitations including
how much weight they are able or
willing to carry with them.
Environmental Friendly Safety may be a concern for
vulnerable
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2.3 Density – Diversity – Design (3Ds)
We now look into the core of the subject. Density, diversity and design were said
to influence people choosing to walk. A broader study of walking and the
environment was examined. The connection between the physical environment
and walking was found to be widely accepted from scholars and government
agencies which will be examined later in the text. Many of the studies
concluded that the physical environment had significant influence on people
who chose to walk.
An environment that encourages walking have characteristics including higher
residential density, mixture of land uses and connected streets (Brownson et al.
2003). Such concept coincides with other studies like Saelens’s (2003), who
suggested similar elements in his study but added short block lengths was also
important for people when deciding to walk especially for those walking for
transportation. He also suggested that low walkability can be defined by low
residential density, lack of mixed land uses and poor street connectivity. The
definition certainly gave heavy weighting to urban planning in the arena of
walking.
The phenomena later went further with Lee and Vernex (2006) remarks. They
stated in their study that “architectural visual quality showed significant bivariate
association with walking.” Other than visual quality, they also were in support of
the elements mentioned were significant for people who chose to walk in their
study.
Another advocate of the concept was Giles-Corti, a professor from Western
Australia. In a quote in the following, it is evident that he made the presumptions
that such concept was right.
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“There is strong evidence that the built environment affects the transport mode
choices of both adults and children. A growing body of evidence confirms that
neighbourhoods characterised by low density, poorly connected street
networks, and poor access to shops and services, are associated with low levels
of walking. Moreover, urban sprawl and low walkability appeas to be
associated with obesity. This may be due to long commuter trips to reach
suburbs located on the urban fringe.” (Giles-Corti 2006)
In her studies, she concluded that “cross sectional studies repeatedly show that
residents in more walkable neighbourhoods do more transportation related
physical activity including walking.” (Giles Corti et al. 2007)
Engagement of the topic went on further to organisations and even
government agencies. The concept became a belief for the Heart Foundation
of Australia. The Foundation published a guideline in 2004 called ‘Healthy by
design: A planners’ guide to environments for active living’. This is an initiative by
the Foundation to promote design principles that coincide with the belief
mentioned and it sees those principles as solutions to many issues including
walking to public transport. This is evident in a quote which says “Planners play
an essential role in planning, designing and regulating the environments in
which we live. Well-planned neighbourhood can increase the number of
people walk walk or cycle to shops, parks, services, facilities and public transport.
This supports healthier lifestyles for local residents, a more socially vibrant local
neighbourhood and brings with it associated economic and environmental
benefits.” (Heart Foundation 2004)
2.3.1 Density
Essentially, this is about raising residential densities in a neighbourhood. Ewing
(1996) explained, the higher the density, especially around a transit stop or
station, the more residents will be within proximity of the transit stop or station,
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which will then improve people walk and riding public transport. The side
impacts, he added, is a more vibrant and secured street life, which will bring
more people to walk.
(Denver Regional Council of Gov. 1993 in Ewing 1996)
The above graph shows the analogy that more people, employees in this case,
meant more walk and ride trips. He claimed that low density would not have
been practical without automobile to cover great distance for daily activities.
Hence, the wisdom of higher densities is that it would compress activities into a
small area which allow people to walk, instead of driving, to almost everything
within reasonable distance. The connection between high residential densities
and lower automobile use is endorsed very much in Sydney. This is evident in the
table below adopted from the RTA.
Development Type Weekday peak hour trips Daily vehicle trips Residential type
Dwelling houses 0.6 to 0.85 per dwelling 6 to 9 per dwelling
Medium density units 0.4 0.5 per dwelling 4 to 5 per dwelling
High density units
- Near CBD, busy locations
- Less built up areas
0.24 per dwelling
0.29 per dwelling
2.5 per dwelling
3 per dwelling
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(RTA in South Sydney City Council 1996)
In the table, it is apparent that lower densities housing produces fewer weekday
peak hour trips and daily vehicle trips. The difference of automobile use
between dwelling houses and high density units was almost tripled.
This connection was also carried internationally by people like, Hass Klau, from
Environmental and Transport Planning in the U.K., who gave examples in the
Amsterdam that more people walked in the densely populated parts than those
lived in less dense housing or modern housing estates, which are auto oriented.
She suggested that there is a relationship between population density and
walking. Her conclusion (Hass Klau in Tolley 2003) was “people living in densely
populated areas are much more reliant on walking than households residing in
the suburban or rural regions.”
2.3.2 Diversity
The presence of retail uses can yield almost as many transportation benefits as
higher densities in residential neighbourhoods (Bernick & Cevero 1997). As Ewing
(1996) justified, with the rise of the automobile, almost all of our daily essentials
have become compartmentalized and at various places. Where we live, work
and play are remote form one another, and beyond walking distance of a
suburban home. Mix use, therefore, is considered to be a necessary
precondition for pedestrian street activity of a place as, simply, there are places
to go within reasonable walking distance. Ewing (1996) made remarks that
“transit ridership should grow as land uses become more varied and
integrated.”
In New South Wales, the Department of Planning (then DIPNR in 2004), was also
a fan of such connection. In a planning guideline published in 2004, it states,
“Mixing land uses in and around accessible centres creates opportunities for
people to live near shops, public transport and other services, making them
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more accessible by walking rather than by car… This can be enhanced by
ensuring all compatible neighbourhood activities are co-located within or near
the neighbourhood centre.” (DIPNR 2004)
Cluster of uses reduces walking distance (DIPNR 2004)
With that analogy in mind, the more mix use the greater possibility of people
walking in a neighbourhood as there are more places to go and drop-by at
midst of a trip. It is fair to conclude, accordingly, that more mix uses in a
neighbourhood and around a transit station would encourage people to walk
to destinations including the transit station.
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2.3.3 Design
Traditional city layout with inter connected street network is an important factor
in influencing people to walk. Traditional cities featured by nodes of
development on streets that connects to other places of interest in the area, a
cluster of mix uses and activities that are often in the form of medium to high
density (Jones in Tolley 2003). The city is focused on the pedestrian and the
convenience of pedestrian movement. A typical European city, like the centre
of Copenhagen is an example of that.
Jones (in Tolley 2003) also pointed out that there is another form of urban design
which we have adopted now in western societies, known as suburban
development. Suburban development is largely different from the city layout of
a traditional city. Roads are curvilinear with cul-de-sacs. It promotes hierarchy
based road system and specialisation of land uses in different districts. Suburban
urban layout encourages automobile movement and centred on provision of
car parking rather than accommodation of pedestrian.
Typical suburban development layout
(Jones in Tolley 2003)
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A more traditional neighbourhood layout
(Jones in Tolley 2003)
Studies have shown many advantages with the traditional neighbourhood
layout including more direct routes, alternatives to high volume routes and sense
of orientation as vision is clear in a grid layout. Ewing (1996) also stated that the
traditional grid layout has already been actively promoted in many transit
oriented development to capture more people walking and public transport
ridership as a grid layout provides direct access to a transit stop or station.
In a guideline published by the Department of Planning (then DIPNR) in 2004, the
department also agreed that “street pattern is an important determinant of
walkability”. The guideline then moves on to promote that “local streets should
be highly interconnected...[as it makes] walking trips short and direct...sightlines
are extended and several route options are available for any one trip.”Streets
are encouraged to orient to transit stop. Cul-de-sacs and other features of a
suburban development are not supported in the guidelines. It is clear that the
Department was in support of transit oriented development layout with street
connectivity similar to the traditional ones.
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Walkable neighbourhood is fostered by connectivity
(DIPNR 2004)
Good street layout design is best to combined with some weather protection.
Canopies, awnings, and arcades are common urban design features. Ewing
(1996) suggested that such features would protect pedestrians as well as transit
walkers. Trees planted between the street and sidewalks provide a physical and
psychological barrier between large mass vehicles and small mass pedestrians
for visual relieve. Trees visually limit street space in architectural terms, at the
same time, decorate a street or act as a sceen on an unpleasant view. Streets
with either natural or built features to protect pedestrians from weather form
good design elements that promotes walking and for farther. An example of
such is the European city of Copenhagen.
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The city of Copenhagen made its commitment to transit oriented development
in the 1960s. Part of the commitment involved in bringing walking and cycling
not only as travel alternatives but also as viable means of accessing train
stations. According to the initiative, involving improving pedestrian facilities and
turning roads into walking paths, urban designers in Copenhagen found that the
average number of people sitting and staying around public spaces and streets
rose from 1,750 in 1968 to 5,900 in 1995. A 1994 survey of access trips to 15
suburban stations in Copenhagen found that walking dominated for distances
up to 1 km from stations, capturing 38 to 100% of access trips (Bernick & Cevero
1997). According to the success in Copenhagen, it is expected that exclusive
walking paths, good pedestrian facilities and environment would induce more
people walking and for farther.
2.3.4 Safety
Safety is essential to all when deciding to choose walking or alternative transport.
Safe, nonthreatening environments need to be created so that people will be
willing to forego their motor vehicles in favour of alternative modes of travel.
Pedestrian pockets offer advantages over conventional suburban designs in
providing safer and more enjoyable non-automobile travel. The dangers of
motor vehicle travel are seldom considered when people elect to travel. The
feeling of safety that comes from being inside a vehicle is still reassuring to most
people. However, people can be reassured by proper space design, proper
lighting and closeness to others.
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2.4 Transit Oriented Development
“A Transit oriented development is a mixed use community within an average
[400 metres] walking distance of a transit stop and core commercial area. The
design, configuration, and mix of uses emphasises a pedestrian oriented
environment and reinforce the use of public transportation. TODs mix residential,
retail, office, open space, and public uses within comfortable walking distance,
making it convenient for residents and employees to travel by transit and
walking.” (Calthorpe1990)
The terminologies used in transit oriented development, as defined by Calthorpe
(1990), shared many commonalities with what an ideal town looks like that
compatible with the 3Ds analogy. Calthorpe’s definition of the TOD is similar to
that of Greenwald (2003), Giles-Corti (2007) and Bernick & Cevero (1997), who
all put many emphasises on higher densities, more mixed uses and pedestrian
oriented design elements such as inter connected street form. As such, TODs are
the best examples in testing the 3Ds mentioned and their relevance to walking
to public transport. The selection will be further explained in Chapter 3.
Bernick and Cevero (1997), especially, concentrated his studies on people’s
willingness to walk in relation to a TOD environment. Through his studies, he
found that most Americans are willing to walk 150 metres, however, only 20% will
walk if the distance increased to 300 metres. The figure dropped to 10% for
distance of 800 metres. Despite the less than appealing results, he drew the
conclusion that “walking distances [can be stretched] through good quality
planning that lends legitimacy to transit village planning.”
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(Belden Russonello & Stewart Research and Communication 2002)
As shown in the graph above, it is indicated that “things are too far and it is not
convenient to walk” made up the largest portion of those who were surveyed
with the question of the reasons for not walking more. As such, the notion of
what is the acceptable walking distance is important when people making the
decision to walk and is imperative for town planning such as planning for the
environment around a transit station. It is that notion together with the 3Ds that
will be tested.
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Chapter Three - Methodology
As has been shown in Chapter One the aim of this research was to analyse
walking as intermodal to train stations. The focus of the investigation was to
investigate how long people walked to the selected train stations and whether
the physical environment influenced them to walk that distance at all. The
investigation was carried out with variables that are compatible to the 3Ds
concept.
Surveys were found in this research to be an appropriate tool as they allow for
primary data to be collected from train travellers in Sydney. Questions were
asked directly of those that used the train. These questions were aimed at
answering the hypotheses as set out precisely in Chapter One.
Information was collected from people by means of asking questions while they
are waiting at the train station for trains. The survey was kept as short and simple
as possible, to decrease the time that it takes for the survey to be filled out and
to make it easier for the commuters to follow. The aim was to make the survey
short enough so that there would be enough time for it to be filled in before
people having to board the train. It was estimated that each survey would take
about 5 minutes of the commuter’s time. However, there is concern that with
high frequency train services in the morning, it could be very hard for commuters
to complete the survey before the train arrives. In that respect, the survey will
mainly be taken during non-peak hours between 10a.m. and 4p.m, even
though some trial will be carried out during peak hours. It is expected that the
participants would be those who travel during non-peak hours and not travellers
in general.
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The sampling method that were used were non-random and a simple-random
sample. The non-random sampling method was use when choosing the train
stations. The train stations that were chosen are listed below. The simple method
was used whereby every commuter at the train station had the same chance of
being chosen.
The survey was of quantitative type, where possible, the questions were pre-
coded. The aim of pre-coding was to avoid having to categorise the data after
the surveys had been collected, especially for the walkability index. Open
ended questions were asked in the end of the survey to allow for participants to
express other perspectives if necessary.
The train stations which were going to be surveyed have to be situated in a
suburb that meets the definition of TOD as closely as possible. Parramatta was
identified as a TOD in the western part of Sydney, Burwood in the inner west and
Bondi Junction in the eastern part of Sydney City. These places conform to the
characteristics of a TOD including:
• Higher density around the transport node
• Mixed use intended for diversity; and
• Good pedestrian connectivity.
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Burwood Station and surroundings
Bondi Junction surroundings
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Parramatta Station and surroundings
The sample size collected was 30 per station with a total of 90 responses. It was
decided that a face-to-face interview type survey would be the best. This
interview was conducted by going to train stations and asking commuters
questions whilst they stood at the platform of the train station. It was felt that by
having the researchers ask the questions the questions could be further
explained if the respondent did not understand or gave an inappropriate
answer. It was important to understand the journey to the train station, what
they think about the physical environment to the train stations.
Putting aside personal details, the survey consisted of 22 questions. These
questions all relate to the hypotheses. The first set of questions asked was about
the density of the journey to get to the train station. The second set seeks
understanding of the land use pattern of his/her journey and whether he/she
uses it at all. Design characteristics were asked in the final part of the survey to
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gain insights on how important design was of which he/she experienced and
perceived on the journey. The respondent was allowed to answer freely why
they had chosen to walk to the train station. The data from the survey was
entered into a statistical program called SPSS. The data was then analysed.
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Chapter Four - Results
A total of 90 people were surveyed, with 35 walked less than or equal to 5
minutes, 24 walked 6 to 10 minutes, 20 walked 11 to 15 minutes and 11 walked
16 to 30 minutes. There is a gradual decrease of the number of people walking
as the time to cover a distance increases. The average walking time is recorded
in the table below. Average walking time ranges from 6.4 to 11.6 minutes.
Lowest range (min.) Count Highest range (min.) Count
1 35 5 35
6 24 10 24
11 20 15 20
16 11 30 11
Average (Total count/90)
6.4 min (1 dec.) Average (Total count/90)
11.6 min (1 dec.)
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4.1 Distance VS Density
4.1.1 Density of the respondent’s residence
The above cluster bar graph shows that those who live in apartments/flats,
indicated as light brown, have the highest portion of people walking than other
housing types in any of the walking distance category. This happens across all
walking distances, except for walking distances greater than 30 minutes which
recorded zero participants. This graph shows that even with walking distances
beyond 10 minutes, those who lives in high density were still more likely to walk to
the train station. This is interesting as the number living in low density housing
would be expected to increase as distance from a transport node increases.
The survey shows a different reality. Low density residents are expected to be
less likely to walk for all walking distances than high density residents.
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(Note: Single detached, semi-detached and town houses have been recoded into one variable for the
purpose of a more robust Chi-Square test)
A Chi Square test confirmed that the relationship between the two variables
examined is significant. This variable shows positive relational results with walking
distance.
4.1.2 Density along respondent’s walking trip
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The above graph examines the presence of high density housing with walking
distances. The inconsistent pattern of opinion regarding this variable suggests
that the presence of high density, that is, apartments or flats, is not a significant
factor in influencing people to walk. A large proportion of those who are in the
walking categories - ‘Less than or equal to 5min’, ‘6-10min’ and ’11-15min’
experienced very little high density during their walking trips. For those who
walked ’16-30min’ to the train station, a larger portion fell into the experience of
‘All or Most’ high density on the trip. However, this stand alone difference is
inconsistent with other walking distance categories and it alone is not strong
enough evidence to form a connection between the presence of high density
during the trip and walking distances.
The cross tabulation table above shows the exact number of people who chose
to walk from different distances and if they experienced high density during the
walking trip. The result from the table coincides with the cluster bar graph
previously shown. More people walked with an experience of ‘A few’ or ‘none’
high density during their walking trips than those who experienced more high
density. This is evident across all walking distance category except those who
walked ’16 – 30 min’. This may be explained by the fact that there were fewer
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samples in this category. Both the bar graph and the cross tabulation table
show no potency for the connection between high density on the trip and
people choosing to walk from various distances.
This is not to say that the presence of low density is then a more significant factor
in influencing people choosing to walk to get to the train station. As ‘All or Most’
and ‘A Few or None’ are tied statistically in most walking distance categories
except in the instance of ‘less than or equal to 5 min’, which by far, ‘A Few or
None’ was the most dominant answer. This could be due to proximity to the train
station and transit oriented layout of the area, which means that land use
density would have been intensified. This is confirmed by the next figure
showing insignificant percentage differences between the variables ‘All or Most’
and ‘A Few or None’ in the test of presence of low density and walking
distances.
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The relationship between presence of low density on the walking trip and
walking distances is characterised by a relatively close gap in percentages
between the categories. Presence of low density on the trip is shown to have no
significant influence on people choosing to walk. This finding shows density
along a walking trip does not link to people’s choice of walking.
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4.2 Distance VS Diversity
4.2.1 Businesses around respondent’s resident
In the above graph, presence of businesses around residences has been tested
against different walking distances. For those who walk 10 minutes or less, more
people walk who live near businesses than those who didn’t. However, those
who don’t live near businesses still took up a substantial portion of about a third
of the total persons who chose to walk for distances up to 10 minutes. This is
unusual as businesses are prevalent within a 10 minute walk from the transport
node in a transit oriented suburb, yet those who lived near businesses did not
form the dominant pattern within these distances. This reality weakens the
relevancy for this variable. The relationship between presence of business
around residence and walking becomes even more irrelevant when the walking
distance gets beyond 10 minutes as a substantial portion of respondents do not
live near businesses. This is especially the case for those who live ’11-15 min’ from
the train station.
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4.2.2 Businesses along respondent’s walking trip
The strength of the diversity factor was further examined with the variable
‘presence of businesses on the trip’. The table above shows some dominant
pattern for the answer ‘All or Most’ for the question. The dominant pattern
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occurs at all walking distances except for the ’16-30 min’ category. To verify the
significance of this variable, a Chi Square test was used.
(‘All or Most and ‘Some’ have been recoded into one variable for more robust Chi Square test)
The test was inappropriate in this context as more than 15% of cells had
expected counts of less than 5. For now, it can only be said that presence of
businesses along a walking trip has some potency for those who chose to walk
from various distances but this is not statistically proven. For that reason, we may
look to the next variable, usage of business, for conclusive comment on the
relevancy of business with walking at different distances.
4.2.3 Business usage by respondent
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The insignificant influence of the business level on the walking trip may be
explained by the above graph indicating the proportion of people who actually
use the businesses along their walking trips. No dominating pattern is found with
lack of a constant tendency on either of the answers. More people answered
‘no’ for walking distances less than or equal to 5 minute and 11 to 15 minutes.
However, more people answered ‘yes’ for walking distances of 6 to 10 minutes
and 16 to 30 minutes respectively. Drawing from the results then, we conclude
that business is not a statistically significant factor and hence, the hypothesized
relationship between the previous variables about businesses near the residence
and on the trip is unlikely to have a significant influence on how long people
choose to walk. However, it should be noted that the relationship may differ if
the respondent was asked if he/she had used a business in the previous week
during their walk to the train station instead of for the duration of one walking
trip. This will increase the accuracy of whether the walkers were interested in the
businesses at all. This is however another hypothesis which requires further
investigation.
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4.3 Distance VS Design
4.3.1 Directness of the walking trip
Directness of the walking trip is very likely to have association with people
walking as a large portion of walkers selected ‘strongly agree’ in answering
whether their walking route was direct. Walkers appeared to have chosen their
walking route as directly to the train station as possible. The ’11 – 15 min’ walking
distance category ranked highest in disagreement (either somewhat or strongly
disagree) with their walking route being direct. This may be due to the fact that
the farther a site is located from a train station, the more corners may have to
be passed in order to get to the train station. This fact is very much true even for
transit oriented suburbs. However, interestingly, those who walked 16 to 30
minutes, have a lesser proportion of people who disagree with their walking
route was direct, in spite of being at locations farther than 15 minutes. This may
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be due to fewer samples in this category. Overall, those who chose to walk to
get to the train station were the ones who found themselves walking on a direct
route. A Chi Square test suggests that such relationship is significant.
(‘Strongly Agree’ and ‘Somewhat Agree’ have been recoded into one variable. ‘Somewhat Disagree’ and
‘Strongly Disagree’ have been recoded into another for this Chi Square test)
However, as there were, in this instance, more than 15% of cells that had an
expected count of less than 5, this finding is not a reliable one. A larger sample
size is required for a more appropriate Chi square test.
4.3.2 Availability of alternative walking route
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The table above shows a dominant pattern of walkers agreeing that they could
choose an alternative walking route to get to the train station. This is the case for
those who walked 6 to 10 minutes and 16 to 30 minutes. Only those who walked
5 or less minutes showed a different pattern. This different pattern may be
explained by the fact that the walking trip for those who live very close to the
train station could very well be as direct as one straight route and hence their
trend of fewer alternative routes. This variable was examined by the Chi Square
tests.
The Chi square test above suggests that the availability of an alternative route
has some relationship with the walking distance variable. It is noted that the
provision of an alternative route is dependent on street pattern and connectivity
from various studies. These results lead us to conclude that the street pattern
and level of street connectivity to the train station have some relationship with
people who chose to walk to the train station from different walking distances.
This is especially the case for people living beyond 5 minutes from the train
station.
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4.3.3 Well maintained sidewalks
(‘Strongly Agree’ and ‘Somewhat Agree’ have been recoded into one variable. ‘Somewhat Disagree’ and
‘Strongly Disagree’ have been recoded into another for this Chi Square test)
Provision of well maintained sidewalk is tested against different walking
distances. The tables above show there is no significant tendency of well
maintained sidewalk lead to the decision to walk from all walking distances.
However, a Chi Square test is inappropriate is this instance as more than 15% of
cells had expected count of less than 5. This leaves us with a suggestion that the
two variables may have some linear pattern of expectancy but the strength of
the relationship cannot be proven in our test.
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4.3.4 Availability of trees
(‘Strongly Agree’ and ‘Somewhat Agree’ have been recoded into one variable. ‘Somewhat Disagree’ and
‘Strongly Disagree’ have been recoded into another for this Chi Square test)
This time the variable of “availability of trees” during the walking trip is tested.
Like the previous variable, some tendency is found between high availability of
trees and the more people walking from different distances. However, a Chi
Square test refutes such theory. This finding shows the availability of trees is not
relevant to walking to a train station.
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4.3.5 Attractive natural and built environment
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The above results of the two variables on the perceived natural and built
environment show two trends. One is that the closer a person walks to the train
station, the more likely he/she dislikes the natural and built environment. The
other trend is there seemed to be a slight shift of opinion, from disagreeing to
agreeing, of the natural and the built environment for those who had to
walk’16 – 30min’. There may be various reasons for that including lesser tall
buildings and an increase of natural features as distance from the train station
gets longer. Overall, there are no signs that the natural and built environment
variables have any relationship with the walking distance variable as
inconsistent opinions were indicated at different walking distances. Hence, the
perceived attractiveness of the environment, both natural and built, is highly
unlikely to have any relevance to people choosing to walk from different
distances.
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4.4 Distance VS Safety
4.4.1 Safety from traffic
(‘Strongly Agree’ and ‘Somewhat Agree’ have been recoded into one variable. ‘Somewhat Disagree’ and
‘Strongly Disagree’ have been recoded into another for this Chi Square test)
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Some linear trend can be spotted with safety from traffic on the walk trip and
people who chose to walk from different distances. The answer of ‘Strongly
Agree’ with feeling safe from the traffic dominated all categories of walking
distance. The answer of ‘Strongly Disagree’ was either ranked last or nonexistent
for this test. From the sample collected, however, it was not possible to formulate
an appropriate Chi Square test as it is recorded that more than 15% of cells has
expected count of less than 5.
4.4.2 Safety from crime
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(‘Strongly Agree’ and ‘Somewhat Agree’ have been recoded into one variable. ‘Somewhat Disagree’ and
‘Strongly Disagree’ have been recoded into another for this Chi Square test)
Like the previous variable, some linear trend is evident with safety from crime on
the trip and people who chose to walk from different distances. The answer of
‘Strongly Agree’ with feeling safe from the crime dominated all categories of
walking distance. The answer of ‘Strongly Disagree’ was either ranked last or
nonexistent for this test. However, the strength of the relationship cannot be
estimated in this instance as a Chi Square test recorded that more than 15% of
cells has expected count of less than 5. The later test of the sense of safety
overall of the trip may help support safety from crime is a significant factor.
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4.4.3 Overall safety on the trip
Personal safety is an essential criterion when people make their daily life
decisions. This includes choosing the mode to travel. If a person found
something that will be unsafe to him/her, then that person will probably pursue
an alternative method to achieve his/her goal or simply not pursue it at all. In this
test of overall safety, only a ‘yes’ or a ‘no’ can be answered. This is to affirm
respondents’ real opinion of their sense of safety on the walk trip. The table
above indicates a linear relationship between overall safety of the trip and
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different walking distances. Those who walked less than or equal to 5 minutes
recorded the highest proportion of people feeling safe overall in their walking
trips. The trend continues in other walking distance categories, however, to a
lesser extent. It is recorded that the proportion of people who felt safe overall
dropped once the distance crosses the 5 minute mark, yet those who felt safe
were still the prevalent ones in other walking distance categories. The
relationship between the overall safety of the walk trip variable and the walking
distance variable is also supported by the Chi Square test, indicating such
pattern could only have occurred 22/1000 by chance. This result enhances the
validity of the previous two variables regarding safety from traffic and crime,
which cannot be statistically proven, as it is reasonable to suggest that they form
part of the intrinsic value of overall safety.
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4.5 Distance VS Other Socioeconomic Factors
A selection of socioeconomic factors is presented above for some general view
of who actually took part in the survey. Of the three train stations surveyed,
Parramatta was the only station which had a lower proportion of people who
walked less than 5 minutes than the other walking distance categories. Burwood
and Bondi Junction recorded the highest number of people who walked less
than 5 minutes, with Burwood ranked top. Parramatta was found to have the
highest number of people who walk 16 to 30 minutes. The figure is actually
higher than those who walked less than 5 minutes and tied with the number of
people who walked 11 to 15 minutes. This is less than comparable to the inner
suburb of Burwood with very few people willing to walk more than 15 minutes as
indicated.
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The survey found there are more males than females who undertook longer
walking trips. This is more the case as the walking trip gets longer. Females were
more likely to walk short distances in this instance.
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Those who chose to take part in this survey were in the age group 18 to 29 year
olds. This age group outnumbers all other age group in every other walking
distance category. On all occasions, this age group doubled or even tripled the
other age groups. This survey indicates that more 18 to 29 year old persons
walked to the train station than for other age groups.
The graph shows a significantly low proportion of people who were born in
Australia walked to the train station. This is the case across all walking distances.
The proportion of people who were born overseas dominates all specified
walking distances. A steeper drop of Australians who chose to walk occurred
when the walking distance had gone beyond 10 minutes. For those who were
born overseas, a drop was recorded once the walking distance gets beyond 5
minutes, however, the proportion of people remained constant for the walking
distances of 6 to 10 minutes and 11 to 15 minutes. Generally, the number of
respondents dropped further as the walking distance stretched farther.
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When comparing marital status, singles were the ones who dominated in
walking across all walking distances. The number of singles walking peaked at a
walking distance of less than or equal to 5 minutes.
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From this graph, it is easy to see that a lot more people who didn’t own a dog
chose to walk from all walking distances. The number of walkers who owned a
dog was very low from all walking distances and the distribution was fairly even.
This indicates that dog ownership does not have any impact on whether a
person would choose to walk longer or shorter to the station.
This graph shows that people who did not own a car were the ones who were
more likely to walk. This is the case across all walking distances. Car ownership
was lowest for walking distances less than or equal to 5 minutes and 16 to 30
minutes. However, the reasons would have been very different. Those who live
less than or equal to 5 minutes may not have needed a car as the train station is
nearby. But reasons for the lack of car ownership in the 16 to 30 minutes
category could be the fact that these people had no any other option but to
walk. This is, however, only speculative as car ownership dropped steeply down
to zero as the walking distance went beyond 15 minutes. This is opposed to the
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general tendency that car ownership increases following the walking distance
as indicated by the graph.
4.6 Primary Reasons
At the end of the survey, the respondents were allowed to answer freely the
primary reasons for choosing to walk on the day. It should be noted that their
reasons have been categorized as the seven reasons in the graph above.
“Quick and Short Distance of the Trip” counted 58
Both “Cost related” and “Health related” reasons counted 20
“No Choice” counted 10
The walk being “enjoyable and comfortable” counted 7
Both “En-route to other uses” and try to “Save the Environment” counted 1
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4.7 Results vs Literatures
According to the surveys, the average distance people chose to walk was 6.4
to 11.6 minutes. This result is very consistent with the findings of the authors from
the literatures, including Cevero and the Department of Planning in New South
Wales, which suggested that a 10 minute walking distance forms the catchment
which most people will tend to walk to a transit station. This study confirms the 10
minutes ped-shed theory is happening in Sydney’s TODs and is acceptable to
most travellers.
Environmental variables were used to test against walking distances to show if
the built and the natural environment are significant factors in influencing
people to walk to the transit station. Density type of the respondent’s residence,
street layout and overall safety of the trip were found to be significant. However,
there are doubts as to the significance of these variables in environmental
perspective.
Street layout is the only variable which is significant from an environmental
perspective. This is because the design of street layout creates an environment
that can make a walk more direct and having to walk less. As indicated in the
results, a majority of people from any walking distance categories chose to walk
to the train station as directly and quickly as viably possible. This is also consistent
with the answer that most people walked because the walk was short and quick
in the last open ended question about the primary reasons why chose to walk
on the day. This is the only design aspect which supports the literature about
promoting walking through designing inter-connected streets. This is suggested
by many such as Ewing (1996).
Type of housing that the respondent lives in and overall safety of the walking trip
show some relationship with the walking distance categories, however, there
are many doubts that the relation really is an environmental one that brought
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the connection. The theory of density impacts on walk distance relies on the
fact that higher density will induce more people on the street and hence
people feel more secure and invited to walk. However, the result that only at the
respondent’s residence shows significant density relationship with walking
distance and not during the trip meant that density of the trip show density is not
a significant factor when people choosing to walk. Such result discord the
theory that higher density results in more people willing to walk, which many
such as Ewing (1996) and the Department of Planning (2004) endorsed.
The 3Ds (Density, Diversity and Design) concept, encouraged by many authors
and organisations, was not imperative for people who chose to walk according
to our findings. The causes and implications of the results are discussed in
detailed in the next chapter.
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Chapter Five – Discussions
‘Type of housing’ that the respondent live in, ‘Directness of the trip’, ‘Availability
of alternative routes’ and ‘Overall safety’ show tempting results that the
environment is significant for people choosing to walk. It is noted that the test of
distance versus diversity has already ruled out that high level of mix use at any
stage of the trip does not form a significant relationship with walking distances.
‘Type of housing’ indicates the kind of density of housing that the respondent
live in. This variable belongs to the test of distance versus density. However, if the
theory that high density invites people to walk is true, then it must also be true
that there must be some, if not all, high density along the trip for those who
chose to walk. As such, the theory can only be confirmed correct if there are
some, if not all, high density along the walk trip that the people, who responded
to the survey, took to the train station. The result shows that high density was only
significant at one stage of the walk trip and that was at the respondent’s
residence. Clearly, the environmental aspect of this variable would not have
induced the relationship as explained. The variable, however, became much
more relevant if interpreted as a socioeconomic factor. The socioeconomic
data gathered shows us that those who chose to walk were mostly in their 18 to
29 years of age, born overseas, single and who don’t have a car. These suggest
that the respondents were probably modest in their socioeconomic status. This
information is more likely linked to the respondent’s choice of housing of high
density than the possibility of wanting to live in a high density housing and have
people live closely around. If such scenario is valid then the correlation of ‘type
of housing’ and walking distances become much more sensible as it explains
why density along a walking trip did not matter. Our study shows that more
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relevance can be drawn from a socioeconomic perspective more so than
environmental.
Both ‘Directness of the trip’ and ‘Availability of alternative routes’ are indications
of the kinds of street layout that people chose to walk in. This is the only relevant
environmental factor which showed a likely relationship with the walking
distance variable and can be explored further.
However, no other design features in both the built and the natural environment
were found to be significant. This weakens the association of design and walking
which was suggested by many such as Lee and Vernex (2006) and including
government agencies and organisation such as the Heart Foundation of
Australia.
It is not difficult to understand that safety on the trip was a basic requirement
when people choosing a transport mode. The results have shown the same
pattern that safety is a significant factor. This coincides with authors who
suggested that and more effort can be put in to create safer environment for
walking including more awareness for Crime Prevention Through Environmental
Design (CPTED).
5.1 So what really matters to them and to planners?
If the built environment does not matter, then what does? Drawing from the
graph showing the answers for the question of why people chose to walk to get
to the train station on the day, lesson can be learned from what really matters
for walkers. It is noted that the highest rated answer was ‘quick and short
distance of the trip’. This is a time factor in which can be remedial through urban
design of the place such as more focus on enhancing street connectivity and
placing housing and employment within direct route of the train station so
residents and employees can quickly get to the train station and other
destinations with shorter distance.
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Cost related answers were second most rated factor, together with the health
related factor. Cost is partially linked to the socioeconomic status of a person.
Walking has a good advantage in this category as it virtually cost nothing and it
will be a transport mode that is popular with people who wants to spend less.
Indeed, most of those who participated in the survey were the ones who
seemed to be less affluent. Most of them live in higher density housing such as
flats and apartments and do not own a car. In an urban planning perspective,
more affordable housing should be built around the 10 minute walking
catchment of a transit station as these people are more likely to walk and use
the public transport.
Walking, even it costs nothing, still appears to be less attractive to the majority of
the population as, at present, the cost of automobile is still acceptable and
comparable to public transport. As such, walking as an intermodal mode would
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only raise attractiveness if the cost of the subsequent mode is justified. Rail
transport as the subsequent mode is not the case at the moment. To rectify this
particular issue, it is recommended that some monetary reward program may
be initiated by railway operator to benefit those who ride regularly. Discount
may be offered to those which can verify living more than 800m (10 minute walk)
form the train station. This in turn will bring more people walking as cost is an
important integral factor when people decide on a transport mode.
Health related answers had the same level of counts as costs related answers.
Interestingly, not many over 30 year old participated for this survey. This is good
news for our younger generations but a bad news for those who are over 30
years old. More publicity can be made in relation to the benefits of walking,
especially longer walks, to those who are over 30s. The promotion could be a
message that in fact walking is healthy while costing nothing. At the moment,
there is no environmental instrument which planners can foster the message of
health. The Heart Foundation of Australia, instead of preparing more planning
guidelines, could be spending more time and effort in promoting the health
benefits of walking so people understand what as little as walking can do to
their health.
A decision matrix was prepared below to try to gain a clearer picture of how
attractive walking weight according to the three answers which were reported
to be important. It should be noted that the points and weighting given to each
situation are only estimations. The decision to give a high point for automobile
travelling time (Quick time-wise) was influenced by results of a transport
experiment conducted by Sydney Morning Herald on 1 August 2008 titled “The
great commuter race: car vs bike, scooter, foot and public transport”, in which
automobile was relatively quick even during peak hours compared to public
transport on a regular day. The higher the total point, the more attractive that
mode is to a commuter.
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DECISION MATRIX for a journey equivalent to 1 hour walking
Quick (Time-wise) Health Cost Totals
Walking 1 9 9 6.4
Walking + Public Transport 7 5 5 10
Automobile 9 2 5 11.1
Weighting (x1) (x0.3) (x0.3)
(The weighting was derived by the fact that ‘Quick and short distance of the trip’ accounted three times more of the ‘Health related’ and ‘Cost related’ reasons)
DECISION MATRIX for people with little health awareness
Quick (Time-wise) Health Cost Totals
Walking 1 9 9 4.6
Walking + Public Transport 7 5 5 9
Automobile 9 2 5 10.7
Weighting (x1) (x0.1) (x0.3)
DECISION MATRIX for people with little regard for costs
Quick (Time-wise) Health Cost Totals
Walking 1 9 9 4.6
Walking + Public Transport 7 5 5 9
Automobile 9 2 5 10.1
Weighting (x1) (x0.3) (x0.1)
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DECISION MATRIX for people who consider time was less important on a trip
Quick (Time-wise) Health Cost Totals
Walking 1 9 9 5.9
Walking + Public Transport 7 5 5 6.5
Automobile 9 2 5 6.6
Weighting (x0.5) (x0.3) (x0.3)
It is noted that under all circumstances but one, automobile is the more
probable decision. That particular exception occurs when a person considers
time is not an important factor in his or her journey. In that instance, it
accounted a point of 6.6. Walking and getting onto public transport only
became attractive in this particular circumstance, accounting a similar point of
6.5.
In saying that, such exception situations virtually do not exist in our daily lives. This
means people will always be driving their automobiles, until one day, driving is
not faster to get to a destination anymore. If the travel time for automobile
becomes slower combined with increased automobile running cost and
awareness of healthy lives, it will surely produce outcome according to the
findings. Until then, we can only hope neither our lives nor our planet die before
such realisation.
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Chapter Six - Conclusion
There were a number of issues which limited the type of sample this research
gathered. Time was an issue as it was virtually impossible to conduct a survey
during peak hours. No sample was gathered at peak hours as travellers were
rushing to get on one of the high frequency trains that depart every couple of
minutes from the train stations elected. The sample therefore had to be
collected during non-peak hours when travellers had the waiting time. Attitude
was another issue. Some over 30s were asked to participate in the survey,
however, a large number of them refused. These age groups were seemed to
be very sceptical in taking part in a survey. It is now understood, after some
failures in taking samples in this research, that surveying people, by itself, is a skills
that have to be learnt. There is a need to formulate strategy aimed specifically
at different age group for taking samples.
However, this research does tell us something about the topic of walking
distance and its’ connection with the environment. The result shows that
environmental variables do not matter very much overall. It is not a single
important factor when people choosing to walk. The causes of some variables
which strike significant statistics to the walking distance variable were rather due
to their non-environmental attributes. The decision matrix shows theoretically
people are more concerned about accomplishing getting to the final
destination as soon as possible rather than anything else. The three most
important factors of getting there quickly, being healthy and at minimum costs
suggest that people seemed to be more concerned about themselves rather
than environmental. As such, the final remark for this thesis is that only plans or
solutions that can translate environmental concerns into the ‘I’ or the ego
concerns will help walking to revive once again in our towns and cities. Until
then, the favourite still is cars, cars and cars!
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Reference
1 Newman, P 1992, ‘Planning and Healthy Cities: the renaissance of a movement to cope with automobile dependence’, in Allan Rees (ed.), Reshaping the Urban Environment: Proceedings of the Second National Conference, Australian Community Health Association, NSW, pp. 97-109.
2 Grava, S 2003, Urban Transportation Systems: Choices for Communities, McGraw-Hill, United States.
3 Bernick, M and Robert, C 1997, Transit Villages in the 21st Century, McGraw-Hill, United States.
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