SUSTAINABLE SUBURBAN TRAVEL – DO DEVELOPERS HOLD

SUSTAINABLE SUBURBAN TRAVEL – DO DEVELOPERS HOLD THE
KEYS?
Martin Gibson
Transport Research Institute, Napier University
Isle of Wight Council
1. ABSTRACT
For many years, urban transport issues have been the focus of attention for
policymakers and researchers, and more recently rural transport issues have
gained more prominence. This polarisation of transport by geographical
location has left suburban areas in something of a no-man’s land, and
research into transport in suburbs has been limited, particularly in the UK.
However, the importance of the suburbs is beginning to be appreciated in
relation to planning for sustainable travel. In the US there is renewed concern
about the impact sprawling suburbs have on car dependency, and in the UK
the need for research in this area has been highlighted recently by both the
Joseph Rowntree Foundation and the Independent Transport Commission.
Government policies aimed at reducing car use mean that car dominated
suburban developments are now deemed inappropriate, which raises issues
of whether different forms of development would be more sustainable, what
changes should be made to improve sustainability of new residential areas,
and how acceptable sustainable development patterns would be to
consumers.
This paper reports on research examining relationships between the built
environment, transport infrastructure, residential location choices and
sustainability of travel, and discusses the relevance of developers to ensuring
suburbs encourage sustainable travel. Initial findings on travel behaviour and
attitudes in suburbs from analysis of National Travel Survey data suggests
while residents of low density areas travel significantly further than those living
at high densities, the relationship between land use and travel behaviour is
not a straightforward one. These results are presented and discussed in the
context of previous suburban studies, and a methodological framework for
more detailed analysis of travel behaviour and attitudes in suburbs is put
forward.
© Association for European Transport 2002
2. SUBURBIA IN THE UK AND THE NEED FOR RESEARCH INTO
SUBURBAN TRAVEL
Love them or loath them, the suburbs are an important part of modern society.
They house the majority of the British population (Hansard HC, 1999) and
occupy a large area of the UK. Increasingly they not only house people, but
workplaces and leisure destinations as well. For many years transport in the
suburbs has not been the focus of significant attention for researchers and
policy makers, with urban and rural areas often seen as higher priorities. Most
Victorian and inter-war suburbs were served by efficient public transport,
serving the primary travel need of suburb to city commuting, with many
shopping journeys being possible on foot. As car use grew, the low densities
of many suburbs absorbed most of the impact of travel changes, but as we
enter the twenty first century, the strain is beginning to show in many
suburban areas, with some streets becoming as congested those in city
centres. Changes in shopping patterns and education, increases in car
ownership, suburbanisation of housing and employment and numerous other
factors have led to a situation where a variety of transport problems are
affecting suburbs, and the travel habits of suburban residents are putting
increasing pressure on those living in other areas.
In many parts of Europe, it is common to find the middle classes living in city
centres, while peripheral areas have large amounts of social housing. This
model is typified by cities like Amsterdam and Paris. In the US suburbs have
typically been built at very low densities, with the aim of accommodating car
use being influential in their design. The UK has been influenced to a degree
by both the European and American models, but typically policy approaches
have followed the prototypical American model more closely, despite its
apparent limitations with regard to sustainability. This has lead to urban forms
designed to simultaneously accommodate car use and mitigate against its
worst effects on the immediate area.
Against this background current government policy seeks to arrest the growth
in car use, and promote modal shift to more sustainable forms of transport,
and a reduction in the need to travel, and journey distances. The significance
of the built environment appears to be significant. This paper will discuss the
evidence on this issue, and describe research currently underway to further
investigate the influence of the built environment, and discuss the possible
role of developers in securing a more sustainable transport future.
This research into the sustainability of travel in suburbs is timely, with two
major reports drawing attention to problems in the suburbs, and government
policy starting to show a shift away from support of car dominated suburbs.
The 1998 Joseph Rowntree Report “Sustainable renewal of suburban areas”
(Gwilliam et al., 1998) highlighted various problem areas in suburbs, with
transport being one of the key issues involved in suburban decay. The
report’s authors highlighted the lack of research into suburbs as part of the UK
© Association for European Transport 2002
urban picture, suggesting “of analysis of changes, threats and opportunities
for the suburbs as a whole, there has been very little” (Gwilliam et al., 1998, p.
64). More recently the Independent Transport Commission highlighted
problems in suburbs of poor accessibility for those without cars and
congestion suffered by car users – its view was that the situation would grow
worse over the coming decades (Independent Transport Commission, 2001).
Suburban travel is one of the key areas that the ITC intend investigating.
Government policy in recent years has started to reflect concerns over car
based suburban development, this can be seen in planning guidance which
sets down minimum densities, promotes mixed use development and
supports reduced parking standards (Department of the Environment
Transport and the Regions, 1998, Department of the Environment Transport
and the Regions, 2000, Scottish Office, 1999). Most research into suburban
travel issues has been carried out in the US, where problems relating to
suburbs have been acute for many years. While this research gives a useful
base, the cultural context is significantly different, and results do not
necessarily transfer to the UK context.
3. CONVENTIONAL SCHOOLS OF THOUGHT ON SUBURBAN TRAVEL
AND URBAN FORM
The suburban transport debate is dominated by two main ideas, with most
authors suggesting one or other of these explains the difference in travel
behaviour between cities and suburbs. They can be broadly categorised as
follows:
•
•
As density decreases, so does accessibility and viability of local
services/public transport, hence car use increases.
Differences in travel are related to income and lifestyle – well off
households drive more, want to drive more, and are more commonly found
in suburbs – they don’t drive because they live in suburbs, in fact they may
choose the suburbs in part because they permit the levels of car use they
seek.
Findings of various authors broadly support the first idea. Newman and
Kenworthy’s research (1989)is some of the most extensive into transport
energy use and urban form, and has been the subject of comment by many
authors, as well as influencing government. They compared transport energy
use in 32 world cities, and concluded there is a string correlation between
overall density and energy use, even controlling for income, fuel cost and
vehicle efficiencies. Holtzclaw (1997) found that doubling residential density
reduces VMT and car ownership by between 14% and 16%, and 9% and 16%
respectively. This figure is greater if associated factors such as increased
transit frequency are considered. The figures were found to hold at various
densities (ie by doubling very low densities or relatively high densities). The
effect of household income is assessed, but while density is found to have a
smaller impact among higher income brackets, the reduction in VMT is still
© Association for European Transport 2002
substantial. Regional Alliance For Transit (RAFT) models of “traditional
development patterns” impact on travel suggests that if this form of
development were integrated into public polices, in 15 years VMT could be
reduced by 6%, based on a conservative model (Lewis, 1998). Frank et al.
(2000) have gone a stage further than most and analyse the link between land
use and emissions of private vehicles.
Their study shows a significant
negative relationship between household density and vehicle emissions.
UK studies have relied mainly on the rather restricted National Travel Survey
data. This can be analysed by density, but only within certain density bands
across the whole country, with no opportunity to specifically analyse any
particular area, or area type. ECOTEC (1993) found that increased density
reduced distance travelled to work and total car use, and increased the
proportion of travel to work made by public transport. Regardless of income,
car use is generally lower in high-density areas. Cooper et al. (2001a) found
that even in a highly car dependent survey group respondents in higher
density areas were more likely to walk to work or the shops than those in
lower density areas. A modelled densification along transport corridors
showed a 14-19% decrease in VMT, or a 28% increase if coupled with
substantial improvements to public transport in the corridors. (Cooper et al.,
2001b)
However some authors have found that any links between land use and
transport appear to be weak or non-existent, and support the hypothesis that
lifestyle is the significant factor. Gordon (1997) suggests that Newman and
Kenworthy’s work is affected by two or three unusual cities (particularly
Singapore and Hong Kong) and variation in petrol pricing, which he claims
accounts for more of the variability in energy use than density (results within
Newman and Kenworthy’s research did, however, include values controlled
for petrol price variation). Analysis of National Travel Survey data, and
census travel to work data did show reduced travel distance to work in higher
density areas, although the effect was not very strong. Boarnet and
Sarmiento (1996) found little evidence of a link between land use and non
work travel, suggesting residential location and thus nearby land use
characteristics should be regarded as endogenous in travel behaviour
models. In an article critical of opponents of suburban sprawl, Hayward
(1998) contends that rather than residential density being the driving force
behind increased private vehicle travel, it is in fact a measure of rising
affluence and changes in work habits that has been the primary cause of the
increase, and thus programmes of densification would be fruitless.
4. RETHINKING THE APPROACH TO INVESTIGATING TRAVEL IN
SUBURBS
Some authors have gone beyond these two ideas, suggesting the situation is
really rather more complex than either would suggest..
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Boarnet and Sarmiento (1996) conclude links between land use and non work
travel are weak, however they also indicate that the relationship between land
use and travel behaviour is complex, and non-work travel is poorly
understood. Susan Handy highlights the lack of consideration of attitudinal
influences in assessing land use and travel, suggesting these need to be
considered as well as a variety or urban structure variables in order to explain
more accurately differences in travel between areas (Handy, 1996). The
diversity of potential influences on travel patterns is highlighted by research
into the cultures of mothering and car use in suburbs of Sydney. It is
suggested that understanding the culture in which travel decisions are made
is imperative (Dowling, 2000). Crane (1996) suggests that standard urban
models assume residents never think about their second job, and highlights
the need for a less simplistic approach to modelling residential location choice
is needed.
Even in terms of urban form variables, many authors highlight numerous
macro and micro factors which are believed to influence travel. Rather than
just looking at key macro variables like density, aspects such as provision of
convenience shops within neighbourhoods, reduction of garden sizes,
narrowing of streets, and removing cul-de-sacs are also suggested (Adler,
1995, Cervero and Radisch, 1996, London, 1996)
Stead (2001) has carried out one of the most detailed analyses of the linkage
between land use, socio-economic factors and travel patterns in the UK. His
multiple regression analysis of National Travel Survey data revealed that
socio-economic characteristics explained around half of the variation in travel
distance per person, while land use characteristics explain around one third of
the variation. While this supports the thesis that socio-economic variables are
more relevant, it highlights the fact that independent of these variables, land
use explains quite a high proportion of travel distance. Stead also notes the
complexity of the relationships between land use variables, and with non-land
use variables, suggesting combinations of land use measures may create
synergies which have significant impacts on travel, and that non-land use
measures may compliment the effect of land use policies.
Based on this evidence from the literature, and the limitations of the simplified,
“single issue” concepts in consistently explaining a sizeable amount of the
variability in travel, it is suggested that looking at suburban travel as a
complex system will provide more useful insights into travel behaviour.
Rather than a simple explanatory factor, or combination of several factors, the
differences between suburban and urban areas are seen as the product of a
complex system comprising a large number of interrelated factors. The
system incorporates factors such as location choice, work/home relationships,
density, mixed use (or lack thereof), public transport infrastructure, street
layout, household income and family structure. The literature clearly indicates
that trying to take a simple approach to solving a complex problem is unlikely
to provide the most useful results. The role of the housing market is perhaps
key to understanding the complexities of the problem. Understanding subtle
© Association for European Transport 2002
segmentation of the market may provide insights into underdeveloped
markets, and potential models for urban forms which engender more
sustainable travel patterns.
What has only been touched on by previous authors is the potential effects of
other transport interventions on behaviour in different types of urban settings.
It may be that the impact of changes to development patterns per se may be
small, but that they would create an environment which allowed for more
sustainable travel when residents are given sufficient incentive to change their
travel behaviour.
5. ANALYSIS OF SECONDARY DATA
In the initial stages of the research, various secondary data sets were
analysed. This has involved the British Social Attitudes Survey (BSA) and the
National Travel Survey (NTS). The BSA has been used primarily for
background information, but will probably be integrated with other data later in
the process
Simple correlations between various factors in the NTS were analysed in
order to begin to assess the strength of relationships between factors such as
density and distance travelled, identify potential for further analysis, and
identify variables which can be transferred to census data to define areas for
primary data collection.
Following this answer tree analysis was performed to draw out patterns in the
data and identify potential subgroups.
5.1 Relationships between travel and urban form
On first inspection the NTS data appears to support the proponents of
densification. Figure 1 shows how average household VMT rises significantly
as postcode sector population density decreases, with households living at
low densities (<5pph) on average driving four times the distance of
households living at high densities (>70pph). Total distance travelled by all
modes shows a similar pattern (figure 2), although the disparity between the
highest and lowest is rather less, with those living at the highest densities
travelling slightly more than twice the distance of those at the highest. This
supports the idea that suburban residents travel further than their urban
counterparts, and that a greater proportion of travel is made by car. However,
analysis provided in table 2, reveals relatively weak correlations between
distance travelled and density. This suggests that while travel may be less
sustainable in the suburbs, there is no strong direct link between density and
distance travelled. Similarly there is only a weak correlation between
household car ownership and residential density, despite households in the
lowest density band owning on average twice the number of cars owned by
residents of the highest density areas.
© Association for European Transport 2002
There is very little sign of any systematic pattern in the relationship between
density and household income, with little correlation between the two
variables. Household income does show a strong correlation with both total
travel distance, and travel by car, however the degree of accuracy in
recording household income for the NTS is relatively low, so it is difficult to
draw definitive conclusions. Average number of children per household
generally increases with density, although there is very little correlation
between number of children and density. This suggests that the relationship
between lifestyle variables (such as income and number of children) and
density is more complex than it first appears.
© Association for European Transport 2002
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4000
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1000
Mean HH distance travelled - all modes
2000
1000
0
Mean HH distance travelled - Car Driver
Figure 1 – Mean household distance travelled as car driver and population
density
3000
Pop. Density (Pers/hec)
5000
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Pop. Density (Pers/hec)
Figure 2 – Mean household distance travelled by all modes and population
density
© Association for European Transport 2002
Table 1 - Correlations between selected socio-economic, urban form and
travel variables
HH
Distance
travelled
HH Car Driver .800
distance
Population
-.183
density*
Number
of .523
HH cars
HH Income
.467
No.
of .230
children in HH
HH
Car Populatio
n density*
Driver
distance
Number of HH
HH cars
Income
-.212
.609
-.215
.468
.080
-.071
.028
.561
.104
.134
* Population density is based on number of persons per hectare, measured at
postcode sector level
All values are Pearson Correlation “r values”, and are significant at the 0.01
level.
Table 3 – Correlations between selected urban form and travel variables for
middle income families sub-group
HH Car
distance
Population
density*
Number of
cars
HH
distance HH Car
travelled
distance
driver .712
-.254
HH .241
driver Population
density*
-.261
.377
-.187
All values are Pearson Correlation “r values”, and are significant at the 0.01
level.
© Association for European Transport 2002
Table 4 – Correlations between total household distance travelled and
household distances to work
HH
Distance
travelled
HH Average distance to .252
work
HH Cumulative distance to .304
work
All values are Pearson Correlation “r values”, and are significant at the 0.01
level.
© Association for European Transport 2002
Following on from this analysis, a sub group from the data set was analysed.
This group contained middle income households with one or more children.
Thus at a basic level this sub-grouping controls for income and lifecycle stage.
Correlation analysis of distance travelled and density within this group which
can be seen in table 3 is rather interesting. Whilst none are particularly
strong, total household distance travelled and car driver distance are notably
stronger than those for the whole sample, suggesting that density per se may
have more effect on this particular group. However, the correlation between
density and number of cars is weaker than that for the entire sample. This
may indicate that car ownership is more stable across varying densities for
this group, but car ownership per se does not have such a great effect on
travel behaviour. Given the magnitude of the differences it would be unwise
to draw any conclusions from this, but it does warrant further investigation.
These results are primarily intended to provide pointers for further statistical
tests which are currently being undertaken.
Answer tree analysis has provided some useful insights into sub-groups of the
data, as well as demonstrating that land use and accessibility variables do
have an impact across different socio-economic groups. Socio-economic
group and car ownership are the dominant variables, but density was relevant
in several of the trees, with several threshold values noted. These thresholds
are generally higher for higher socio-economic groups. Car ownership and
distance to work can fairly effectively predict overall travel distance, and their
effectiveness is notably higher within suburban density bands. However, a
ratio calculated from the analysis actually shows a slightly weaker correlation
than one calculated by experimenting with combinations of the original
variables. Accessibility of public transport featured in a few of the trees, and
fairly consistently divided cases around 3 minutes walk time. The accuracy
with which the variables used can predict travel is quite variable, with model
risk of between 20 and 50%, though generally towards the lower end. This
suggests that the variables seen as the “main” socio-economic and land use
factors which influence distance travelled can still only explain a moderate
amount of this variation.
5.2 Transfer to census data
The second purpose of the NTS analysis was to identify variables which could
be transferred to census data to allow more geographically accurate analysis,
and define areas for primary data collection. The census only contains a
limited amount of data relevant to travel, but some of the variables are
common to NTS and census data sets, and thus a series of variables could be
tested using the NTS data for suitability as indicators to highlight areas of
relatively high and low sustainability. Suburban variables were be developed
likewise to identify suburban areas from census data. Use of ACORN
classification data was considered, but the implications for matching a current
postcode based data set with an 11 year old ward based dataset made this
© Association for European Transport 2002
option too complex, with any accuracy gain offset by possible loss in the
conversion process.
The relevant variables available in the census data set are
•
•
•
Distance to work
Mode to work
Number of cars
To maximise the usefulness of these variables it is necessary to explore how
much of the variability in distance travelled each can predict, and to combine
them in these proportions into a sustainability indicator variable. Distance to
work shows a moderate correlation with total distance travelled, with
cumulative household distance to work showing a closer correlation than the
household mean value, as can be seen in table 4. There is also a moderate
correlation between number of household cars and total household distance
travelled shown in table 2.
These figures suggest that the variables investigated collectively provide a
reasonable indication of the relative sustainability of travel between different
areas. Further work to determine the best combination of these variables
showed no significant gain through using them other than in an equally
weighted ratio.
The distance to work variable proved to have only limited use, as it is only
available at ward level, whereas the analysis was to be conducted at
enumeration district level. Instead the proportion of employees working
outside of the district was used. This may introduce an element of error, as
those living close to the district border may well make a short commute
outside of the district, however in general this effect is likely to be fairly small.
6. METHODOLOGY FOR PRIMARY DATA COLLECTION
While the analyses of NTS data referred to earlier, adds some additional
insights to the data about suburban travel available from the literature, and
lends support to the idea that the link between density is not a simple
relationship, it still only gives a small part of the picture. By its nature the NTS
is a general survey, not targeted specifically at certain areas, and identifying
specific areas is not possible. The initial analysis does appear to confirm the
hypothesis that many factors are involved in influencing the travel patterns of
people in suburban areas. It may be that some of these are socio-economic,
some are related to the built environment and transport infrastructure, and
some due to psychological/perceptual issues. In order to examine the relative
importance of these factors more closely, and to test the acceptability of
measures to improve sustainability of travel in suburbs by addressing the
underlying issues, primary data collection is being undertaken. In order to
maximise the value of any survey work, the process through which survey
© Association for European Transport 2002
areas was chosen encompassed quantifiable factors and subjective
qualitative indicators. This process involved several stages, as follows:
1. Selection of cities/towns to consider for analysis. Originally this was
to be informed by census data, but due to financial constraints a limited
number of cities were considered, and detailed work to establish the
suitability of Southampton for analysis was undertaken, with other short
listed cities to be considered if Southampton did not provide suitable
survey areas,
2. Highlighting suburban areas within the city. This was achieved
using pre-selected indicators from the census data. Census boundary
data from UKBORDERS was used to map suburban areas using
ARCVIEW GIS and Map Explorer software.
3. Using sustainability indicators, suburban areas were graded into
bands of relative sustainability. Areas of relative high and low
sustainability within suburban areas were sought.
4. Areas selected were checked to see if they appear to meet the
requirements of a suburb (as defined for the purpose of this study).
This involved analysis of maps and aerial photographs, and information
from estate agents, primarily gathered over the Internet
5. Each area was visited to check the findings of desk based analysis
match the reality, and to allow for some of the more subjective features
of suburbia to be assessed.
A pilot survey is being carried out in July/August 2002 to test the survey
design, and determine the most cost effective way to distribute the survey
whilst maintaining a high response rate. Based on this pilot, any necessary
modifications to the survey implement and the data collection process can be
made. If changes are relatively minor, it may be possible to include pilot data
in the final analysis. The main survey will be carried out in September 2002.
The survey design will take the form of a self-completion questionnaire, and
will be administered either through a call and collect arrangement, or a postal
survey. It will gather data relating to travel behaviour, attitudes to access and
mobility. The survey will couple information on travel behaviour with attitudes
to travel and residential location choices in an effort to obtain a more complete
picture of the reasons why suburban residents travel in a less sustainable
manner than those living in denser inner areas.
This methodology is rather different to most previous suburban studies. In
general these have attempted to investigate one element of “suburban-nes”,
such as density or street layout. Locations are generally chosen to reflect
variation of this characteristic, and control for other differences. While this
method has its merits, it only looks at a single issue, rather than the complex
interrelation of issues which are believed to effect travel.
By selecting areas of relative high and low sustainability, this study attempts
to control for sustainability, and assess the characteristics of areas with
different sustainability characteristics. Data will be collected relating to two of
© Association for European Transport 2002
the main areas of trip production, shopping and commuting, from which it
should be possible to identify specific trip types which are different (in length,
mode, frequency etc.) between the survey areas. These differences can then
in turn be related to differences in the urban form. For example, in suburb A
households tend to drive to a supermarket 2 miles away in order to get basic
shopping, such as bread and milk, whereas those in suburb B are more likely
to walk to a local shop. Assessment of the two areas reveals most people in
suburb A are within a 5 minute walk of the local shop, while residents of
suburb B are between 10 and 15 minutes walk of the nearest shop. As such,
they drive, but to a supermarket rather than the closer shop. Similarly it may
be possible to relate a change in mode and distance used for clothes
shopping to the proximity of an out of town shopping centre.
7. THE ROLE OF DEVELOPERS
The initial stages of this research have shown a relationship between the built
environment and sustainability of travel appears to exist. However the impact
of the built environment is small compared to that of household income, which
acts as the main determinant of travel distance and car use.
However, while the direct impact may be small, it is hard to ignore the
likelihood that forms of development which promote ease of car use over
other modes provide an environment which is unsuitable for more sustainable
lifestyles. Thus for those living in such areas, no real transport choice exists.
Demand management measures or policies aimed at encouraging modal shift
are unlikely to be effective where no viable alternatives to the car exist.
What is not clear is which factors are significant in creating this “car only”
urban form, and which could improve the viability of more sustainable forms of
transport? It may be that developers need to change their approach to
building suburbs, but to do so based on speculation could be counterproductive. This research should move forward our understanding of the
changes that need to be made if sustainable transport is to become a reality.
Developers may indeed hold the key to sustainable suburban travel, but in a
conservative industry change is only likely to stem from strong direction from
government, or a clear defined market for sustainable housing. It may be that
such a market already exists, but is not being exploited by developers happy
to follow a traditional route as long as they can sell houses.
8. ACKNOWLEDGMENTS
The doctoral study this paper is based on is supported by a research
studentship funded by the Go-Ahead Group.
© Association for European Transport 2002
Its presentation has been made possible by support from the Transport
Research Institute and Isle of Wight Council.
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© Association for European Transport 2002