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APPENDIX A
THE TRANSPORTATIONS - LAND-USE INTERACTION
EMPIRICAL FINDINGS
.
This Appendix was prepared with He assistance of Dr. Dame! A. Badoe.
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A.1 EMPIRICAL STUDIES ON THE IMPACT OF URBAN FORM ON TRAVEL
BEHAVIOR
A.. Introduction
The review of the literature dealing with urban fonn impacts on travel behavior presented in this
section is divided into four sub-sections. The first two deal with "real-worId" observations
concerning urban form impacts on usage of transit and other vehicular modes (Section A. ~ .2), and
-
alk mode usage (Section A.I.31. Section A.!.4 then reviews simulation studies of urban form
impacts on travel behavior. Section A.. concludes this portion of the review with a brief
discussion of some common problems and identified directions for further research which emerge
from this review-.
A.~.2 Urban Form Impacts on the Use of Transit and Other Vehicular Modes
PBQD tI99~] provide a very comprehensive review of the important studies that investigated
the relationships between transit and urban form conducted over the last three decades. The key
domestic U.S. study mentioned is that by Pushkarev and Zupan tI977] who developed a set of
"land-use thresholds" that were necessary to justify financially different types of transit investments,
based on intermodal comparisons of transit unit costs and intercity comparisons of transit trip
generation rates. The land-use characteristics identified to be the determinants of transit demand in
this study were the size of the downtown, measured by the non-residential floor space, the distance
of a site to the downtown, and residential densities.
In a subsequent study Pushkarev and Zupan tI980] developed six demand-based threshold
criteria to determine the financial feasibility of fixed guide-way transit. The Pushkarev stuffy was
based on two assumptions that may not be presently applicable "Steiner, ~ 9944. First it assumed that
all work trips are to the central business district' in other words, a monocentric cites. This contrasts
with the multi-centered character of most metropolitan regions in the U.S today. Second. non-
residential lancI-uses were assumed to be segregated from residential uses. This contrasts sharply
with the mixed land-uses found in many neighborhoods tPBQD. 19954.
Not~thstar~ding the difference in Dreary form implied in the PusDkare~ study from today's urban
structure. the PusDkarev's study is still widely quoted and employed in determining feasibility of
proposed rail projects.
In another study~ Smith tI984] compared transit usage in six U.S. metropolises. and found that
the renumber of trips made by transit increased sharply when residential densities rose from
approximately 7 dwelling units to ~ 6 dwelling units per acre. In flew York city, for example. such
a density increase resulted in an increase in the renumber of transit mps made per person Tom a figure
of 0.2 to 0.6.
A study by Peat Warwick & Mitchell tI97 5] using data collected In the 1973 Nationwide
Personal Transportation Survey (NPTS) found that for both bus and raid systems, density among
other variables did not explain much of the variation observed in transit usage. Rather
socioeconomic characteristics of the residents appeared to better explain the observed variations.
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Levinson and Kumar tI994], who investigated for relationships between density and several
indicators of travel behavior using the 1990 NETS data found that the density-threshold for a
relationship between density and mode choice was ~ 0.000 persons per square mile. They, however
were critical of the thesis that density alone can explain travel behavior.
Burby, et at. t~ 974] compared travel behavior in fifteen new communities that had mixed land-
uses, with fifteen "semi-planned' conuoT suburbs. Notwithstanding the differences in urban designs
their study results shoaled no significant reductions in vehicle miles traveled or transit usage for all
trip purposes save recreational trips.
Fr~edmar~, et at. tI994] compared household trip-rates of residents of communities designed as
standard post-war suburbs with that for residents of older, more traditionally designed communities.
Data for this study were extracted from household travel surveys conducted in the San Francisco Bay
Area. The authors excluded data from households located within the city of San Francisco. stating
that its high level of transit service and utilization, and high jobs/housing ratio could not be
replicated in any new town or community to the extent that it exists in San Francisco. They also
excluded households with very Tow or very high incomes from the analysis, stating that based on the
price range of houses in some of the neo-traditionally designed neighborhoods under construction
at the time, Hey were urdikel, residential candidates. Trips were stratified by purpose and then by
mode, and household modal trip rates computed.
The major findings of this study include the 25 percent higher daily trip-rate and 32 percent
higher auto-dnver trip-rate that households in the "standard suburbs', made compared to households
in traditional neighborhoods. Auto-based modes had a mode-share of 86 percent in the suburbs
compared to 76 percent in Me traditional communities. Transit use in the traditional areas stood at
7 percent compared to 3 percent for the suburban areas, and walk mode share for all trips was 12
percent in the ~aditiona1 communities compared to ~ percent for the suburban communities. Clearly
all this study reveals is the existence of a difference in household tr~p-rate between residents of two
types of neighborhoods. No attempt Bras made to isolate the effects of other important factors that
could have contributed to this difference in observed tr~p-rates. Hence no conclusions can be drawn
Dom this study on the efficacy of neighborhood design schemes to reduce vehicle miles traveled or
increase the attractiveness of non-automobile modes.
Dur~phy and Fisher t! 996] report their findings of art investigation into the relationships between
urban densities, socioeconomic characteristics of residents and their travel characteristics. The
analysis was focussed first on regional comparisons of travel characteristics, using as the data-source,
the 1991 FHWA Highway Statistics. Specifically. the authors investigated the relationship between
average density of a number of metropolitan regions in the U.S. and annual vehicle miles traveled
per capita, as well as the annual transit trips per capita. The authors found that there was a general
tendency for less driving in higher density regions, with the notable exceptions of Sari Francisco and
Sari Jose where residents droxte far more than residents of other regions of similar average densities.
The analysis of trips by transit indicated a clear pattern of higher levels of transit trips per capita in
regions of higher density. leading the authors to conclude the existence of a positive relationship
between density and transit usage. In a bid to better understand the observed behavior of travelers
living in the different communities, as opposed to entire regions, the second part of the analysis
investigated the relationship between density. calculated at the zip-code level, with demographic and
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.
socioeconomic characteristics of residents, as well as their travel characteristics. The findings were
as follows:
I. household travel. measured in miles per household, increased with income;
per capita VMT was substantially lower at higher levels of density, up to a factor of 9 when
compared to driving by residents of the lowest density areas
similar to Handy's t! 995] finding that the average number of per capita trips by all modes
declined very little Mom the Cow- density neighborhoods to the high density neighborhoods;
4. the average number of trips per capita by the auto-driver mode declined by one-half as
density increased from 4.500 to 30.000 persons per square-mile, automobile person trips
similarly declined from 3.6 person trips to 0.6 person trips per day;
S. transit trips increased sharply above densities of ~ 0,000 residents per square mile, from less
than 0.2 to 0.5 hips daily; and
6. stalking and bicycling also become significant at higher densities, growing from about 0.3
trips by walk per day at densities of 4~00 persons per square-mile to I.S trips by the average
resident living at densities greater than 40.000 persons per square mile.
This latter study. although insightful and useful, suffers Tom a fen shortcomings. First. the use
of a single average density for a large urbanized region masks a lot of information, and does not help
to explain Ably why residents of communities of different densities exhibit differences in travel
behavior. As an example. the influence of the different neighborhood designs on mode usage is
completely ignored. Further, Me stud`; results demonstrated that notwithstanding Los Angeles' high
urban-density, it had much lower transit usage compared to New York. which had a lower population
density, suggesting that factors other than density also had an important role to play. Second, the
results are primarily drawn Tom one-~-ay cross-tabulations and simple plots. Thus the effect of each
variable is assessed without consideration of the impact of the remaining variables, or for any
possible interactions among them. Clearly, the explicit role each vanable plays in explaining travel
behavior can only be fully determined when all the variables and their interactions are
simultaneously considered in the analytical framework. Third. in comparing the different
metropolitan regions, the historical development of the cities is completely ignored. Fourth, no
explicit consideration is given in the analysis to the transit service provided in the various
communities or regions. Fifth. in the regional arlalysis, hardly any figures are quoted in the paper
to enable one to assess the extent of the relationship between density and travel behavior.
In a departure from the simple linear correlation approach of ins estigating the role, if any, of
urban form on travel behavior, Schimek tI996b] developed a multiple linear regression model of
vehicle travel which includes vehicle ownership as an intermediate factor, and which treats a
household's pick of neighborhood density and the amount of travel as a simultaneous relationship.
To better isolate the impact of density on trace] behavior, income and demographics were controlled
for in the mode} specification. The issue as Schimek, points out, "is not only whether density affects
automobile use, but whether the effect is strong enough so that attainable changes in density could
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make a substarthal contribution to efforts to improve air quality and provide other social benefits of
reduced automobile use". Using data drawn Tom the ~ 990 Nationwide Personal Transportation
Survey, Schimek obtained the following results hom his estimated models.
Members of households in higher-densit,~- areas make fewer automobile trips and travel fewer
automobile kilometers than those in low--density areas.
2. For trips, most of the effect of density is direct, but for distance driven, two-thirds of the
effect of density on automobile use comes through the mechanism of Tower rates of car
ownership in high-density areas. This lower rate in car ownership is not the result of the
association between income and density. because the model controls for the influence of
household income on residential density. Lower rates of vehicle ownership In higher-density
areas is likely the result of greater attractiveness of alternatives (walking and public transit)
and the greater difficulties and higher costs of motor vehicle storage in high-density areas.
3. The hypothesis of shorter car trips in higher density areas because of land-use clustering
appears to have only a small effect. In other words there may be more destinations within
a shorter distance, but in practice people appear not to take advantage of this density to
reduce vehicle travel. In shorts density matters. but not much.
~J
4. With respect to public transit use, much of Me difference in household travel associated with
the presence of transit comes from lower rates of vehicle ownership. This suggests that at
least some households locate near transit routes to reduce their vehicle ownership needs or
having done so. find that they can reduce automobile ownership without an unacceptable loss
of mobility.
Schimek concluded that his study results provided evidence that households in higher-densi0
areas travel less in private cars, all else being equal. However, the effect of density was found to be
so small Mat even a relatively large-scale shift to urban densities would have a negligible impact on
total vehicle travel. In quantitative teens, a 10 percent increase in der~sity leads to only a 0.7 percent
reduction in household automobile travel. By comparison, a 10 percent increase in household
income leads to a 3 percent increase in automobile travel.
Schimek's study pushes the state of the art forward In that it attempts to address the endogenous
nature of some of the explanatory variables specified in the models, particularly, vehicle ownership.
However, the vehicle ownership mode] is simple' and not derived from any explicit theory of
decision making. The study also uses spatial-units defined by zip-code to compute densities, units
that can hardly be described as homogeneous in urban character. Thus, spatial organization within
the zip-code areas is not controlled for in this study.
Kockelman tI997] employs multiple regression analysis and the binary logit model to explore
the association between several dimensions of urban form and travel behavior, after controlling for
socioeconomic factors. Several variables describing land patterns, such as accessibility, land-use
balance, mix and density are defined and tested in the mode] specifications. Travel data for the study
came Dom the ~ 990 San Francisco Bay Area Travel Survey which involved over 9,000 households
while the land-use data was largely constructed from the 1990 Association of Bay Area
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Gove~ment's land-use file. Several models were developed for: vehicle miles traveled (VMT) per
household. non-work home-based VMT per household. auto ownership models, and No mode
choice models.
The study results showed that after controlling for demographic and socioeconomic factors.
measures of accessibility. land-use mixing and land-use balance were influential in their impact on
all measures of travel behavior. With the exception of the vehicle-ownership model. the impact of
density on travel behavior was found: to be negligible after controlling for accessibility. Further. the
author found that arise balance. mix and accessibility were more relevant to travel behavior
prediction than several household and Raveler characteristics commonly used for this purpose. The
author concluded that the study lent empirical support to the neo-traditionalist claim that land-use
integration and compact development reduce automobile reliance.
This paper does well In defining several objective variables that describe the built environment
for testing in venous mode] specifications. However. a look at the estimation results show- some of
the models to be of quite low explanatory power. As an example the non-work home-based VMT
per household base mode! has a coefficient of determination of 0.0366, and after inclusion of the best
set of urban-form explanatory vanables, rises to 0.0~67. Thus, although signs of coefficients In these
models may reveal the impact of individual explanatory variables on the dependent variable. the
estimation results also indicate that as a whole, the models are able to account for only a small
proportion of the variation in the observed values of the dependent variables, or, in other words, that
other unidentified factors are primarily responsible for the variation in the data. Secondiv. auto-
ownership arid mode choice are not modeled within a consistent travel-behavioral framework. Auto
Ownership is modeled using linear regression anally sis, while mode choice is modeled with a binary
logit model, without any theoretically derived link between these models.
Cervero arid Kockelman [19973. in a very similar study to Kockelman tI997], investigated the
influence of the built environment on travel Remarry along the thee principal dimensions of density,
diversity, and design. The Ravel and socioeconomic data used in the analysis were drawn from the
1990-1991 Bay Area Travel Survey. The land-use and design-features data were collected through
field surveys of the 50 sampled neighborhoods Tom the San Francisco area the Association of Bay
Area Governments (ABAG) land-use inventory, and the Census Transportation Planning Package
(CTPP). Multiple linear regression and binary logit models were estimated to test for any association
between trip-rates, mode choice and vehicle miles traveled respectively, and several factors
describing the built environment. The model estimation results led to the conclusions that density.
land-use diversity, and pedestrian-oriented designs generally reduce trip rates and encourage non-
auto travel in statistically significant ways. though their influences appear to be fairly marginal.
Elasticities between each dimension of the built environment and travel demand were found to be
modest to moderate, though certainly not inconsequential. Residents of neighborhoods ~ ith grid-
iron street designs and resmcted commercial parking were found to average significantly less vehicle
miles of travel and rely less on single-occupant vehicles for non-~-ork trips. Within neighborhood
retail shoes were most strongly associated with mode choice for work trios.
.. ~ . ~ ~ ~ ~
~ ,,
Schimek tI996a] compared public transit use in Toronto to that in Boston, with the objective of
identifying the factors that would account for the differences in patronage levels. Choice of these
cities lay in their similarity in terms of size of population and geographic area. On the basis of the
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l
estimated hme series models of transit use for the two regions, which had several policy and control
variables specified, the author concluded that the higher residential densities, the greater
concentration of jobs in the CBD and the inner suburbs, the greater transit service provided, =d
relatively lower incomes and income growth in Toronto contributed to the higher observed use of
transit, compared to Boston.
Frank and Pivo ~1994] studied the impacts of land-use mix and density on use of the single-
occupant vehicle (SOV), transit and walk modes respectively for shopping and work trips. The
analysis was done at the census tract level. Sources of data for their study were the Puget Sound
Transportation Panel, the U.S. Census Bureau and a three local agencies in Washington State.
Similar to Schimek t] 996b]- a multivariate statistical approach was used in the analysis to control
for non-urbar~ form factors hypothesized to influence travel behavior, while assessing the possible
role density and land-use mix might have on travel behavior. The percentage of SOV, transit and
walking trips Mat onginated or terminated in a census tract were calculated for each census tract, and
each in turn served as the dependent variable in a multiple regression model. Four specific
hypothesis were tested:
I. population density, employment density, and land-use mix are related to mode choice;
population density, employment density, and land-use mix are related to mode choice when
non-urban form factors are controlled for;
a stronger relationship exists between mode choice and urban-form characteristics at both
trip ends than at one trip end; and
4. the relationship between population density. employment density, land-use mix, and mode
choice is non-linear.
From the results of a simple correlation analysis, the authors concluded that urban form and
mode choice were significantly related. The strongest linear relationships for work and shopping
trips respectively were between employment density and transit and walking. Land-use mix was not
found to be significantly correlated with any of the three modes for shopping trips.
Results Tom the regression analysis fed the authors to conclude that urban form is significantly
related to mode choice when non-urban form factors are controlled for. The authors state that the
percentage of transit arid walk trips for both work and shopping respectively had the highest
relationships with the urban-form variables. Urban form factors were found to be consistently
ne~ativeiv associated with the percent of SOV use and were nositivelv a~.int~1 with n~rn.ent
· . ~ tot · ~ ~ ~ ~ . ~ . ~ ~ ~ ~ ~ . , · ~ · ~ ~ _ .
transit use anct walking. ~ anally, the authors concluded that the relationship between mode choice
and employment density is nonlinear. Two employment-densit~r ranges at which significant modal
shifts from SOV use to transit and walking were identified. The first is at 75 employees per acre.
beyond which the percentage of trips by transit or walk increased dramatically. The second is
between 20 and 50 employees per acre at which there are moderate increases in the use of transit and
walk modes. The study findings suggest that population densities need to exceed ~ 3 residents per
acre for changes in mode choice to be detected. Further, the reduction in SOV travel was not as
significantly associated with increases in population density as it was with employment density. The
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relationships between land-use mix and mode choice were found to be relatively weak.
Handy tI993] addressed the question of how- alternative forms of development could affect
shopping travel patterns using the concept of accessibility. Two measures of accessibility were
defined In this process to reflect the Inking that Me amount oftravel made by a person is influenced
by bow the character ofthe local community person resides in, and the spatial structure ofthe region
of which the local community is a part. Both accessibility measures were calculated using art
exponential form of the gravity model. The first. local accessibility. was a measure of proximity to
locally oriented centers of activity. The measure of attractiveness was defined as the sum of retail,
service and other employment within the zone. The off-peak intra-zonal travel time by auto was
used in the impedance function. The second regional accessibility, measured how good
transportation links to large regionally oriented concentrations of activity were. The measure of
attractiveness was retail employment, with the impedance to travel being a Traction ofthe inter-zonal
travel time by auto. Handy tested four hypotheses:
I. that accessibility levels will be negatively related to travel distances
2. that there will be a positive relationship between trip frequency and accessibility;
3. that accessibility will have little impact on total travel as measured in average person
kilometers traveled; and
4. that the balance between regional and local accessibility of a community significantly
influences the travel patterns of its residents.
The study results showed that high levels of either local or regional accessibility were associated
with shorter average shopping distances, but not with trip frequency as hypothesized. This suggested
that there may be an average or standard number of trips that residents make, regardless of the
distance dew must travel. The amount of non-~-ork travel measured in person kilometers traveled,
was found to be significantly Tower in areas that had higher levels of accessibility at both the local
and regional level.
Har~dy's study, though useful. has a number of drawbacks. First, the measure of accessibility
treats all households/persons residing within a particular commuru~- as having ache same accessibility
regardless of whether they have a vehicle available to them or not. Second the measure of
accessibility employed is sensitive, in teens of system attnbutes. to only travel-time by automobile.
Thus, the level of transit service provided or network of ~alk-paths that determine Cracking distances
to retail activity do not reflect in the re:,ional or local accessibility of a location. Third, local
accessibility was aggregated to obtain an average value at a super-district level. From the discussion
~ the paper, the heterogeneity within these super-districts far exceeded that between districts -- this
raises the serious question of how representative the average values were in reflecting accessibility
for the entire super-district. Further, averaging reduces the amount of variability to be explained,
and this can lead to spurious results and conclusions. Aggregation to a super district level also meant
that an accessibility value did not consistently clearly map a neighborhood into one of the alternate
neighborhood types considered, namely. traditional. or neo-traditional, or suburban-type
neighborhood. Thus implications for policy may not be clearly defined. FiDch, the possible role
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played by socioeconomic and demographic characteristics of residents of the various local
communities in accounting for the vocations in observed shunning travel patterns is cc~mr,ieteiv
ignored in the analysis process.
-rr---= ~red -----a----
Handy (199~) describes an alternative approach to researching the link between urban form and
travel behavior. This approach is based on a theory analogous to that underlying the development
of discrete choice models. Succinctly, it suggests that urban fond must be evaluated in terms of the
sets of choices that it provides, in terms of the kinds of destinations that are found in the various
areas, in terms of the transport modes serving these areas, and the characteristics of these choices,
including the cost and comfort of travel, the amount and quality of activity at the destination, etc.
By this differences in travel characteristics in different neighborhoods are not simply attributed to
some being old while others are new. Rather the differences in travel characteristics are ascribed to
the different sets of choices inherent in the form of the neighborhood Hat influences travel behavior.
Thus urban form is evaluated in teens of the range arid nature of the choices inherent within it.
Handy's studs- focussed on non-work trips, specifically shopping Imps, which she argues are more
likely to be greatly- influenced by urban form due to the greater flexibility in terms of time and space
associated with this trip. Handy selected four neighborhoods in the San Francisco Bay Area for her
study. Selection -as based on three factors, namely, location writhing the region and accessibility
to regional centers of retail activity, the type of neighborhood, that is, whether "traditional" or
"typical", and finally, the socioeconomic characteristics of the residents in the communities. By
limiting the number of neighborhoods studied, Handy- was able to devote more attention to obtaining
good measurements of the attributes residents of the different neighborhoods were faced with in
making decisions concerning shopping in addition to their socioeconomic attributes. By studying
the variation in the travel patterns of residents of the different neighborhoods using the analysis of
variance procedure and controlling for socioeconomic effects, Handy found the following:
1. residents appeared to compensate for longer distances by making fewer trips,
2. residents in the traditional neighborhoods, which had more people living within walking
distance of a supermarket. had a higher percentage of the walk trips;
3. having a single supermarket close to a resident did not necessarily minimize the total amount
of travel to supermarkets since residents choose to shop at a variety of supermarkets;
4. residents of traditional neighborhoods, compared to residents of typical neighborhoods, had
a greater frequency of trips to convenience stores because of the greater accessibility to
convenience stores in these areas. These trips did not appear to substitute for trips to
supermarkets, as the frequency of trips to supermarkets by residents of the traditional
neighborhoods was not significantly different from the other study areas;
5. average frequency of trips using the walk mode for the purposes of pleasure or exercise did
not differ significantly between neighborhoods, suggesting that the differences in pedestrian
quality of these areas did not seem to foster walk-trips; and
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6. point (5) notwithstar~ng. the percent of respondents who walked to a commercial area at
least once in the previous month and the average frequency of ways to commercial areas did
vary significantly between the traditional neighborhoods and the typical neighborhoods. This
finding was partly explained by residents of traditional neighborhoods being more closely
located to commercial activity. Interestingly. in areas where links between residential areas
and commercial areas could be described as "pedestrian unfriendly" residents still used the
walk mode In significant numbers. Thus, Handy, concluded that having commercial activity
within walking distance is enough to encourage at least some walking but nedestnan-
oriented design encouraged it even more.
4 , ~
Handy concluded that urban form does in fact make a difference in determining whether
residents perceive walking as an option available to them. The relationship between residential and
commercial areas is important; distances must be short, and barriers such as major arterials should
be eliminated or avoided when possible. Commercial areas need to be designed for pedestnan access
as well as automobile access and for pedestnar~ circulation within the commercial area. This study
found no evidence that residential design (things like Dont porches, varied of materials and designs,
etc.) is particularly important in the decision to walk, contrary to what neo-traditionalists assert.
There was also no evidence that the option to walk would significantly reduce automobile travel.
A greater range of destination choices. at least up to a point, is valued by residents. although this
results in more travel and longer average tr~p-lengths.
Cervero tI996] examined how mixed land-uses and features of the built environment, like
residential densities, influences the travel choices of residents from large metropolitan areas. The
Gavel choices considered are the mode used for commuting, the commuting distance arid household
vehicle ownership level. Data for the stuffy were drawn from the 1985 American Housing Survey
and embraced ~ ~ Metropolitan Statistical Areas (MSAs). The mode choice models developed are
based on random utility theory and are modeled as Gnaw decisions. Thus. even though three modes
were modeled, namely, automobile (drive-alone arid shared ride), public transit and walk/bicycle,
each was modeled within a beam framework. The explanatory variables specified in the modal
utility functions were either classified as land-use variables or control variables. No attributes
explicitly describing the transport system In terms of times and costs were considered. The analysis
of commuting distance and household vehicle ownership levels employed multiple regression
models to identify the relevant related urban form factors. Five hypotheses were tested in the study.
These are (p.3631:
-
1. mixed-use neighborhoods induce higher shares of non-auto commuting among residents
2. mixed-use neighborhoods exert their strongest influence on non-motor~zed commuting,
specifically walk and bike travel to work;
3.
m~xed-uses only have a positive influence on transit-riding, walking, and bicycling to work
if they are close by (i.e., within several blocks of a residence);
non-residential uses. such as grocery and drug stores that lie between several blocks and a
mile or so of a residence induce auto-commuting and trip-chaining; and
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density jobs-housing balance dummy. and accessibility; and at the destination zone. employment
density and accessibility for non-home based trips. Four attributes of travel were modeled using
linear regression. These were trip rates. trip times, mode shares and vehicle hours of travel. The
findings of the study include:
I. development patterns do have a significant impact on household Aver beyond that explained
by socio-demographic attributes -- "placing households in more accessible residential
locations will cut down significantly on their vehicular travel"
good regional accessibility cuts down on household vehicular travel to a far greater extent
than does localized density or mixed use -- the jobs-housing balance. after accounting for
socioeconomic attributes. had a pronouncedly weak relationship with travel behavior;
3. accessibility of residences to a mix of land-uses as opposed to one tone of use (e at. work
shopping) had a significant impact on ~ ehicular travel; and
, ~. ,
good accessibility of work place to other activities resulted in additional trips being made
from work. although the average length of these trips was shorter, and reduced the number
of trips made independent of work.
This study does well in attempting to isolate the effects of urban form factors on travel behavior.
However, some of the models on which the latter findings are based, have extremely low coefficient
of determinations - four of Me eight models has-e R' values that range from 0.02 to 0. ~ 0, suggesting
that as a whole, the vanables specified provide very little explanation of the variation in the
respective dependent variable.
A.~.3 Urban Form Impacts on Walk Mode
Handy tl996b] points out that oniv few of the studies investigating the relationship between
urban form and navel behavior have attempted to understand the more complex causal links between
urban fond and travel behavior; most have typically relied on simple correlations between variables
to establish association. This has led to little being known about exactly what attributes of the built
environment Influence travel behavior. and how important these built-environment attributes are
relative to the other factors influencing travel. Handy tI996b] therefore explores hove urban form
fits into a more comprehensive mode] of choices about pedestnan trips. The focus is on walking
hips. which is posited to be influenced be the surrounding environment and urban form more so than
trips by any other mode. The hypothesis is that walk-trips, classified as "strolling trips (objective
is the walk itself)" or "walks to a destination (objective is to reach an activity of interest)" have as
primary causal factors individual motivations and individual limitations. Urban form is hypothesized
to be an external factor that could encourage or discourage chalk trips, given motivations and
~ . · .
mltatlons.
Using data collected on six neighborhoods in the Austin area. selected on the basis of the era of
development, location within the city, aIld to control as much as possible for average socioeconomic
characteristics, He author explored the relationship between urban form and pedestrian choices. The
neighborhoods were selected such that pairs of them were similar. Three pairs were thus obtained
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and these were descnbed as "traditional", "early-modern", and "late-modern". Having similar pairs
allowed for testing of the differences between types of neighborhoods as well as an analysis of
variation between neighborhoods of the same type. Several variables were then used to describe the
neighborhood transportation and -use characteristics. The v~abies fall under the categories:
street system, transit system. commercial area and commercial establishments per ~ 0~000 population.
Data on pedesman choices were collected through a mail-out. mail-back survey. The survey
included sections on supermarket trips, walking trips trips to local commercial areas. and socio-
demo=~raphic characteristics. as well as questions on feelings about and perceptions of a varietal- of
up form charactenstics. A thousand questionnaires were mailed out, with the overall response
rate being 25 percent Handy's study had the follow-in" findings:
1. the results supported the proposed model that is, Mat individual motivations and limitations
are central to the decision to walk
':
urban form was foment to be a secondary- factor that encouraged or discouraged walking,
given the motivation to walk and the absence of limitations.
A.
4.
urban form was also found to play a greater role than other factors in the choice to walk to
a destination, with the distance from home to destination being the most important factor.
the latter factor mentioned in point (3), together with the quality of the pedestrian
environment at the destination. outweighed the quality of the pedestrian environment around
home in the choice to walk to a store; and
S. a crude assessment of the possibility that walk trips to the store might replace drives to the
store, under He most optimistic of assumptions' showed that only 0.4 percent of the average
distance driven per month would be substituted for by walking.
..
Handoffs study, although focussed on pedestriarls. represents one of the few- attempts at
identifying, if anti what it is about ache urban environment that may hex e some relationship with the
travel behavior of residents.
Loutze~eiser [1997] reports on a study; to identify the factors influencing the choice of the
access-mode of stalk for passengers using the BART system. Data for the -study was collected
through an outboard survey conducted over a two-day penod. in the Fall of ~ 992. These data were
supplemented with data from the ~ 990 US Census. The approach adopted was first to attempt to
identify the factors influencing the choice of the walk access-mode for BART users. second, to
examine the role of urban fonn/desi~n and station area characteristics in the decision to access
BART by the walk-mode; and finally. to identify the impact of urban design factors on access-mode
choice after controlling for the individual characteristics of B ART users. Three binary logit models
of access mode choice there developed to identify the factors influencing the choice of the walk
mode. These models were (~) walk versus all non-walk trips, (2) walk versus transit and (3 ) stalk
versus the automobile. The author hypothesized that the choice of BART access mode is a function
of the characteristics of the traveler" the characteristics of the access trip, and the assailability of
alternative access modes. The variables found to be the primary determinants of access mode choice,
from the model-estimation results. were distance-to-station, gender, ethnicity, age and car
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availability,
Furler analysis revealed that the importance of these factors varied widely by B ART stations,
and that specifying dummy variables to capture these station area effects was not adequate in
explaining the relative roles of these vanables. Hence, the second part of the study investigated the
impact of urban fonn and design on access mode choice. Multiple linear regression models. which
related walk mode share at each station to various urban fo~m/design characteristics and average
socioeconomic characteristics of residents of the neighborhoods around the station, were developed.
The regression-results showed that population density was by far the most important variable to
explaining the variation in walk mode share. Further, it was found that the proportion of BART
users in the neighborhood of a station. who walked increased with the level of education of the
residents. and with income. Parking capacity was found to have a negative impact on walk mode
share, while proximity to an activity center had a positive effect on walk-share. To properly assess
the effects of urban form factors on access mode choice, the aggregate station area characteristics
and indix idual characteristics of respondents were combined in a single specification for mode]
estimation. This so-called "combined model's show-cd that population and dwelling unit densit arid
transit availability were no longer significant factors in the decision to walk. Median household
income which previously had a counter intuitive sign, had a negative coefficient, hence impact on
choice of the walk mode. The impact of urban design attributes was mixed.
Loutzenheiser's results demonstrate the dangers of conducting a partial analysis; that is either
developing a mode choice mode] that omits some variables, or developing an aggregate station-area
mode] of walk mode share alone that omits variables descnbing individuals. As the study showed,
this can lead to erroneous results and conclusions. Clearly, for the impact of any variables ore choice
to be properly assessed, it must be included in a specification that includes the effects of all other
variables. The study also illustrates some of the potential dangers in using average values for
development of regression models -- it can lead to coefficient estimates with counter intuitive signs
te.g. De Donnea. 1971], which the author found for the case of income. Other concerns with this
study are with the vanables omitted in the transit utility, which may perhaps be responsible for the
relative!! low percent-correct reported for transit. goodness of fit measures for the binary- logit
models are not reported, and this prevents any comments being made about He overall utility of the
models. Further, only a third of the available data were used for modeling, and no figures are given
on the mode split of this modeling-data. Data from five stations, which had relatively low walk
access-mode-shares for BART users, were deleted from the analysis in order to improve the fit of
the model to the data. The objective of the study was to identify factors that influenced use of the
walk mode for accessing BART; but, clearly. such data trimming measures have the unfortunate
impact of not helping to identify why certain areas have low use of the walk mode, and perhaps of
over-estimating the importance of other attributes.
A.~.4 Simulation Studies
In an interesting presentation on the impacts sprawl has on transportation demand, Eager ~ ~ 995]
uses data from the 1990 National Personal Transportation Survey to argue that the expectation of
increased travel by transit, walking and bicycle and decreased travel by automobile through increased
density, may occur only at very- high densities, far beyond densities of development that would be
realistic for 95 percent of urban America. More importantly his test scenario of doubling urban
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densities shows that even though household automobile trip-rates and automobile share of trips
would fed at very high densities. the total number of trips bit automobile would also increase several
times or en Easter argues Mat t~sit-proponents only take a partial look at the picture of travel: the
increased use of transit, without looking at the grown In the overall number of trips by automobile.
Eager's study concludes Mat the spot light should not only be on mode share and trip rates' but also
on the total trips by mode.
Bland tI983] examined the relationship between land-use patterns, particularly town shape, size
and population density, aIld travel for all purposes in a set of nine hypothetical towns. based in part
on modeling using the LUTE-model of walking, car arid bus travel Bland. 19824. The LUTE mode!
was calibrated using data from the UK National Travel Survey (NTS), and a land-use pattern
synthesized Mom UK Defacto Urban Areas population density data to fix the modal split parameter
and the behavioral values of three and money for each mode and tup-pu~pose, prior to examining
travel in the nine hypothetical areas. These latter areas vaned in tenth Tom 3 to ~ Km, and in width
from ~ to 3 Km, with rural population density values of 2 persons/hectare to urban values of 10 to
ALSO persons/ha up to 400 persons/ha. From the mode} results obtained, Bland concluded that the
model-predictions were in good agreement with observed travel patterns. Specific conclusions
include:
I. use per car varies little with land-use pattern or bus service levels, although car ownership
`~-as lower where Incomes are lower, or where congestion and parking difficulties or Rood
access by public ~ar~sport or on foot make car ownership less worthwhile;
2. higher densities are not effective in reducing car ownership or use; further. Me UK NTS data
did not show higher densities to reduce the amount of travel;
A.
moving homes arid jobs closer together did not appear to reduce travel based on the modeling
results and from comparisons of more arid less compact cities; and
4 higher densities favor public transport use, although this did not imply any net savings in the
resources devoted to mechanized transport, since the majority of trips carried by public
transport would o~erv`Tise be made on foot rather than by car.
... . .. . .. . . . .
McNally and Ryan t1993] examined the claim Mat transportation benefits. namely. reduced
travel distances and times, cart be derived from ne - traditionally designed neighborhoods. Two
hypothetical networks were developed to replicate a neo-traditional and a conventional subdivision.
These two networks were developed with the guidance of several sources to ensure consistency with
realistic networks arid land-uses. The road-attr~bute of prime concern in this studs was the shape of
the networks, with factors such as street-width, s~eet-environment etc. being neglected. The
hypothetical subdivisions had approximately the same level of activity. However, certain aspects
of site-design were not modeled. e.g. mixed land-uses in traditional neighborhoods. Travel
parameters, such as land-use trip-rates. were adopted from those developed for the City of Irvine,
California Conventional transportation planning models were used as tools to evaluate the
performance ofthe hypothetical networks in the two community types. Results of the study showed
that the neo-traditional network resulted in approximately ~ O percent fewer vehicle-kilometers of
travel during the morning peak compared to the conventional network. Further total hours spent
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traveling during the morning peak period in the traditional network was approximately 27 percent
less than on the conventional network. Finally. the mean trip-length in the neo-traditional network
was approximately T: percent shorter than in the conventional network.
Ryan and McNally ticks] also cite the results of the work by Stone arid Johnson tI 992], who
used site impact assessment techniques. to compare two hypothetical subdivisions and found that
the neo-traditional neighborhood had 2: percent less vehicle delay, 20 percent fewer Hips generated,
and 30 percent more entry points (used to define accessibility) than a conventional suburban
neighborhood. to support their latter results.
Handy [1 996a] also reports a study by Rabeiga and Howe [1 994]. who examined the impact of
neighborhood design on selected Gavel charactenstics, using four neighborhood types that differed
with respect to street layout and location of retail activity. "A sample of 120 origin points was
selected in each neighborhood. hip tenths were calculated to a random choice of retail destination,
and total travel was then calculated for these 120 tnps" tHandy, 1996a, p. 1543. Both measures
showed a reduction in total travel coupled with an increase in average speeds in favor of neo-
traditional networks relative to conventional networks.
Although these simulation studies may yield useful insights of how different neighborhood- and
street-designs may impact on travel patterns, they are based on simplifying assumptions of urban
form and travel behavior, and hence their conclusions should be treated as unproven and speculative.
A.~.S Problems and Some Directions for Future Work
The empirical studies reviewed have all used cross-sectional data and models for their analysis.
Yet, the dimension of interest is a temporal one; that is, the goal has been to learn how residents in
a given nei~hborhood-type would respond to changes in their built environment. Thus, the use of
cross-sectional data in these analyses is with the assumption that travel-behavioral response of an
analysis unit over time can be inferred from the differences in the behavior of the analysis-units
surveyed at a specific point in time. In the travel demand literature, generally, this has not been
found to be so ~Kitamura. ~ 9903. Use of cross-sectional data therefore essentially allows only for
the associations between variables describing urban form and travel-behavior, at a given point in
time, to be determined, they do not provide any direct evidence of how residents of a typical
suburban-type neighborhood would respond. in the travel context, to changes in the buiTt-
environment of their neighborhood. To appropriately address the question of travel behavioral
response to neighborhood design and land-use changes, time-series data would be necessary. As a
first step, before and after studies should be conducted to give insights into how residents are likely
to respond to changes in the built environment.
Very often, the data available for analysis have been at a gross spatial level. This has led to the
majority of studies making use of averages (e.g.. averages densities) for their analysis. First, these
gross spatial units can hardly be described as homogenous in terms of neighborhood design, density
and land-use mix, and hence do not always lead to clear-cut conclusions. Second, these average
values can not be described as representative of the analysis-units, given that "within-unit
heterogeneity" is in some cases comparable to "between ts heterogeneity". Future research should
ensure that spatial definitions do respect the differences in density, Arouse mix and neighborhood
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. .
design to allow for clear interpretable results.
The literature review revels Me complexly of He phenomenon under study -- how people make
choices with respect to where they will reside in space (residential location), the household auto-
holdings, the mode for the journey to work. and the travel-modes and frequencies for non-work
travel. This is a multidimensional choice problem. which involves a set of related choices. As an
example, the number of vehicles a household ma\; decide to own is related to where they decide to
live and the level of service provided by alternate modes serving the area. Thus any attempt at
modeling arty of the dimensions of this multidimensional choice problem should first, respect the
inter-related nature of the choices on hand arid therefore provide an internally consistent method of
modeling the dimension, and second, provide for a theoretically sound approach for linking these
sub-models. The majority of the studies reviewed have been pumarilv correlative in nature,
developed partial models in that they have botany ignored impacts on the other choices on hand, and
not been based on any explicit theory of human decision making.
~ ~ ~ · ~ ~ ~ ~ ~ ~ · ~ . .
Clearly. if progress is to be made In determining the likely responses of residents to changes in
urban for =d transport system attributes. then a comprehensive behavioral approach to modeling
the several choices on hand has to be adopted. As Anas and Moses fI978, p. 163] point out,
"elasticity series do not throw- much light on the locational adjustments households will make in
response to changes in the cost of travel. This problem is better addressed by urban simulation
models in which the location of activity and the demand for transportation are determined
simultaneously". Consumer theory in economics provides such an approach, the random utility
approach, for modeling these different dimensior~s of choices in a theoretically sound fashion. This
involves the establishment of a choice hierarchy, which could presumably have residential location
at the top of Me hierarchy, and household-vehicle Moldiness work-mode choice respectively at Tower
levels tBen-Akiva and Lerman, 1985~. Sub-models, based on this theory have feedback between
them, hence choices made at a higher level are done with Input from Tower-leve] choices. McFadden
[1978] develops He theoretical framework for such models and their estimation, arid this could form
the basis of fixture mode! development ~ the quest to better understand how- urban form impacts on
travel behavior.
A.2 EMPIRICAL STUDIES OF TRANSIT IMPACTS ON URBANE FORM
Transit undoubtedly had a great impact on urban grown In the ~ 9th century.- -The dominant mode
of travel prior to transit was the walk mode, hence the geographic spread of cities was limited to
walking distances tSchaeffer and Scalar. 19753. The arrival oftransit resulted in decentralization
and relatively Tower density development [Muller, 1995; Black. 19954. PBQD tI995] summarize
the classic work by plainer tI962], who traces how the extension of electric streetcar lines to
suburbia arour~d He turn-of-the-century led to massive decentralization in Boston, the San Francisco
Bay Area, and Southern California Smerk tI967] estimated that as much as one quarter ofthe U.S.
population resided at that time in urban and suburban areas whose spatial organization was shaped
by the street car. Black tiffs] also cites a study by Hoyt tI933] who confine that transit with
its most important routes being the radio lines that met at the city center, strengthened the CBD and
made cities monocentnc. The main alternative mode to transit during the latter ~ gth century and eddy
part of the 20th centur was the walk mode hence the significant impact transit made to urban
development and structure. However, in the latter part of the 20th century, transit's major modal
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competition has been the auto, a far more convenient mode, Thus as Knight tI980] points out,
transit improvements today do not result in the kind of drastic improvement in overall accessibility
associated w~ earlier transit improvements. Hence new- transit lines are less likely to affect urban
form they were they did several decades ago tBlack, 19953. Evidence from recent studies has been
mixed, with some concluding transit to have a major impact on urban form under "naht" conditions.
___1_ ·1 _ _ `1_ _ _ _ 1~ _ _ _ 1 ~ _ ~ ~1 ~ 1 _ _ (_ 1 _ _ _ · , ~ ~ ,1 , t
wrn~e owners nave concluded anal ~ nas tar less impact. come of these squares are presented below.
Heilburn tI981] reports the findings of Webber's tI976] assessment of BART after a year of
operations. This was an extremely short period for assessing its possible impact on urban form,
hence the evaluation was pnmarily on the other touted benefit of diverting suburban car users to rail.
From a survey conducted In 1976, Webber found that only about 44,000 daily B ART users were
recorded as previously making the trip by car. This represented about 35 percent of BART trips.
UnexpectedIx7, however, "about 50,000 BART riders, and as much as half ofBART's transbay traffic,
were diverted hom the over form of mass transportation -- He motor bus" [Heilburn, ~ 98 I, p. 2553.
Overall, Webber concluded that BART had not effected a significant charge In auto use habits.
Giuliano tI995] also reports on a survey of the impacts of B ART, five years after it came into
service. Although still relatively not too long a period for assessing its impact on urban for, the
findings are nevertheless important. The survey showed that transportation access was seldom a
factor in job location choice, and access to B ART was a minor consideration in household location
choice. Important factors influencing household location decisions were housing tYne. general
~r
_
. ~· ~t ~. · . · ~At
~. _% ~
~ 1, . ~
access to the workplace and nelg~oor~ooa characteristics. further access to bAK1 was not an
important factor in the location decision of employers -- important location factors included site
availability-. price, and proximity to other fimns. The conclusion of the B ART-study team was that
BART's impact on land-use after its five years of operation was insign~ficar~t tGinTiano, ~ 9954.
Cervero arid Landis tI997] conducted an in-depth study on the Impacts of BART on land-use and
development twenty years abler service started. The authors found that land-use changes associated
with BART have been largely localized, limited to downtown Sari Francisco and Oakland and a
handfi~} of suburban stations. Elsewhere, they report Hat few land-use changes occurred either due
to neighborhood opposition or a lack-lustre local real estate market. Although crediting B ART with
bringing about a multi-centered regional settlement pattern, they also note that it has done little to
stem the tide of freeway-oriented suburban employment growth over the last two decades. Office
development seen near some of the suburban stations is found to pale in comparison to the amount
of floor space built in non-BART freeway corridors. The multi-famils~ housing built around several
suburban stations is in a large part credited to lock redevelopment authorities who helped leverage
_ ~ . , . _
.. . . . . ,. . ~ . . . .. . . . ... . . ..
these projects by providing various financial Incentives and assistance with land assemblage.
Cervero and Landis concluded that BART, in and of itself, has not been able to induce large-scale
land-use changes although under the right circumstances, it appeared to have been an important
contributor. Stronger public policy Initiatives was stated by the authors as a necessary condition for
BART to be able to achieve the compact, multi-centered urban form initially envisaged.
Workman and Brod t! 997] investigated the neighborhood benefits of rail transit accessibility.
A hedonic price function specified in the form of a multiple regression model, was used to estimate
property values and the impact of proximity to rail stations. Two sets of data from different cities
were employed in the study. The first source of data was collected for homes around Pleasant Hill,
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one of the B ART stations In the San Francisco Bay Area. The second data set was collected for
homes around Free stations on Po~and's MAX light rail system. The researchers found proximity
to Pleasant Hill station to be a key determinant of property values in the Pleasant Hill neighborhood.
Their results showed that single family homeowners were willing to pay. on average, nearly $ ~ 6
more in home-pr~ce for each foot closer to BART within the study area. Further they found that
homeowners were willing to pay nearly $8 in home-price for every foot further from the freeway
interchange nearest the study area.
The Portland data, however. gave much weaker resets. Indeed. based on the entire three-station
Portiar~d data He key viable of "distar~ce of home from station" had a coefficient sign contrary to
the expectation ofthe researchers. One interpretation given to the contrary- result was that possibly
the effects of light rail could be different from that of heavy rail (e.~.. BART). Further. the light rail
line runs close to a major arterial, whose effect the researchers thought confounded the effect of
distance to the station. Massaging of the data Cats done to include homes within 2~00 and :280 feet
Of the line. This time amours, He results Bough very weak, agreed with intuitive expectations. The
authors concluded from their mode] that property values increased by about $0.76 for every foot
closer to light raid within the 2500-5280 feet bared defined.
A similar study on property values, which focussed on the same stations in Portland by Al-
Mosaind, et al [19933 ford a statistically insignificant property value premium for station
proximity. Black tI995] also reports a study by Arrington tI9893. who tabulated $693 million of
new development adjacent to stations on the Portland light rail line after the decision to build it in
~ 979. Arrington also suggested that light raid might have a greater impact that heard rail on urban
form because light rail operates on land-surface arid makes adjacent businesses visible to thousands
of passengers. which is contrary to the suggestions of Workman and Brod tI9973.
Nelson and Sanchez tI997] came up with mixed results when they studied the influence of the
Metropolitar1 Atlanta Rapid Transit Authority (MARTA) on population and employment location.
While the population of the Atlanta metropolitan area grew by 29 percent or nearly half-a-million
people, He population within one-half mile of MARTA stations fell by more than ~ ~ percent, with
the regional share of population living within one-half mile falling bit one-third. - The regional share
of employment within walking distance of MARTA stations also fell by one-quarter. However,
actual employment within half-a-mile of the stations rose 13 percent, indicating that job growth
outside the station area of Influence was much greater.
Hunt, et al. [1994] in Heir investigation ofthe relative impacts of various transportation and non-
transportation factors on the perceived attractiveness of residential locations using stated preference
techniques. concluded that the transport system has ~ strong influence on the attractiveness of
residential locations. The authors found from their empirical study that being within walking
distance of a light-rai] transit station was worth about 217 Canadian dollars per month.
Gentlemen. ef al. tI983] undertook an extensive study to identify the effects of two major rail
investments in Glasgow: the British Rail (BR) Argyle Line and the modernized Underground on
travel, activities and land-use in Glasgow. The study conducted several before-and-aher surveys:
a survey of all travel by households within the raid combor, survey s of BR. bus and underground
passengers, arid surveys of users of shops, workplaces, hospitals. health centers. and a number of
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leisure facilities. The latter surveys were supplemented by data over a longer period on planning
applications and house paces, rail ticket sales and turnover and catchments from shops and other
services. Since this study was conducted one year aver the opening ofthese services, major changes
in land-use and property development were not expected. since these are more long term. Further,
neither rail services was entirely new: the Argyle line replaced a line closed ~ 5 years previously, and
the Underground was withdrawn for 3 years. Thus, the previous services helped shape the urban
structure existing then, and therefore may have limited the impact of the "new" services.
Nevertheless, the authors reported an increase, relative to the rest of Glasgow in planning
applications for retail, office, storage and manufacturing development in the inner areas served by
the Argyle Line and Underground. Based on sales data, the authors also reported clear evidence of
a reversal of a downward trend in house prices, relative to the rest of Glasgow, in the areas
associated with the new services. The authors also reported no systematic take-up of v acant land
near raid lines, which could be identified as being due to the new- services. Small increases in
population, stemming population decline, were noted around some of the Underground stations
though further evidence was needed to confirm this as a trend. The raid lines also had some impact
on travel. After the opening of the BR Argyle line, 24 percent of the passengers were new to the BR
network. 75 percent of them had previously made the same journey by another mode and the rest
were making new trips. Ofthose who had changed mode. 72 percent were from bus, 19 percent from
car and 9 percent previously walked. All Underground travelers were effectively new users because
the service had been closed for several years. The authors report that the proportion who transferred
from bus or walk was similar to BR, but here, only 9 percent previously used car.
Other studies on the impact of transit and development include that by Baker tI983] who fourth
that the Washington D.C. Metro attracted considerable non-residential development to station areas.
Baker reports that between 1979 and 1982. $2 billion out of $3.7 billion of public and private
nonresidential construction in the metropolitan area occurred within 7/10's of a mile of stations.
Green and James tI993] in a study of the Washington system as well, also concluded that the rail
system had significant development impacts, noting that rail corridors had developed more than other
places, and within raid corridors, that station areas had grown much more than other areas.
Knight and Trygg tI977] examined the land-use impacts of rapid transit in several North
American cities. Toronto, one of the few North American cities in which transit has done relatively
well, is orate of those reviewed. Significant urban development is reported by the authors to have
taken place in the lands adjacent to the rapid transit corridor dunng the period of the transit systems
staged development. Heenan t1966, 1968] in his papers on the impact rapid transit had on land
values in Toronto, claimed that the subway was responsible for igniting $10 billion in development
along its route, and also for two-thirds of the appreciation in the physical value of all lands and
facilities in Metropolitan Toronto during a 10 year period. Heenan's findings were however
contradicted by Meyer and Gomez-Ibanez tI981], who studied the Toronto case, and concluded that
the subway had a much less impact. Knight and Trygg t! 977] also found Heenan's findings of the
Toronto rapid-transit impact on lar~d-use to be considerably overstated.
Knight and Trygg also report the cor~clusions of two statistical studies conducted with the
objective of assessing the subway systems impact on land value. The first of these. bar Abouchar
tI973], concluded that the subway had no impact on the value of properties studied. Data for
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Abouchar's study however, came from the period eleven years after the first subway- line was
opened, and also after most of the rest of the system was either approved or well under construction.
Thus, this study was criticized on the grounds that it was likely most of the impact on values had
occulted prior to the period from which the analysis data was drawn. The second by Dewees tI975],
however, concluded that the subway line did have a positive impact on residential values, but did
not attempt to quantify this. Davies tI 974] examined the impact of the Yonge street subway line on
population density, charges. Census data for the years of 1951 1956 and 1961 were used in the
study. Davies concluded that there was no effect in 1956, which was two years after the line was
opened. However, density near the line was fourth to have increased significantly; faster between
1956 and 1961 compared to areas much farther array from the fine.
Knight arid Trying after
examining the Toronto case more closely concluded that it was quite unique. in that zoning was
closely coordinated win the rail lines. a coordination that has not been common for new transit
facilities in the United States. In short that transit. in arid of itself. is unlikely' to have chalked up
the relative success seen in Toronto, without the complement of urban policies to ensure this.
Deakin tI990] notes that the impact of raid transit on urban development has been mixed; in
some cases they have helped achieve more compact and dense growth, but at the same time, at a
regional level, these same rail systems have made previously poorly accessible suburban locations
able to support suburban development. Deakin. similar to Knight and Trying, echoes the important
impact that transit availability and quality have on location and land-use, but goes on to stress that
they represent just two of many other factors. Thus, urdess the remaining factors are also supportive
of transit, then transit investments would be unlikely to make a difference on development.
Knight and Trvgg tI977] also surveyed rapid transit systems and lines in a number of other cities
including Montreal, Boston, Chicago, Cleveland and Philadelphia. In Montreal after reviewing the
evidence and local studies. they concluded that the nature and intensity of retail shopping in the COD
had been influenced by Metro, although other factors, such as the developable Iand, had played a
strong role in the downtown revitalization. Outside the CBD, with the exception of two stations,
little development had occulted. In Phiiadelphia. the focus Bras on the Lindewold high speed line.
Here the authors concluded that the single most important impact of the line in the areas it served
was the substantial increase in residential properly values. Notwithstanding He evidence that office
development occurred who equal or greater intensity in some other areas of Philadelphia and South
Jersey not served by the line, the line was cited for its contributory effect on the location of new
suburban offices and apartment developments nearby, and its influence in local zoning decisions as
well as in actual investments. Evidence from the extensions and improvement to the Boston rail
system on land-use appeared to be mixed. In North Quincy, the line service was cited as a strong
influencing factor in the selection of that location for several major developments, though other
important complemental,- factors. such as land a~'a~labilin,;. reasonable land prices. etc. played a role.
North Quincy aside, verily little impact was observe ed at the stations on the line. Improvements to the
Chicago system generated no land-use impacts. Several reasons are given for this, notably, the
already well developed nature of the downtown district and the high land costs. Similar to Chicago,
the impact of the Cleveland rapid transit system was found to be minimal.
Clearly, Dom the foregoing rail transit is one of several factors that contribute to the shaping of
art urban area. The rail lines and stations in arid of themselves cannot shape urban form without the
other factors also in sync.
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A-26
Representative terms from entire chapter:
travel behavior
