| MEASURING
SPRAWL AND ITS IMPACT
The
Character & Consequences of Metropolitan Expansion
Executive
Summary
Much
as Justice Potter Stewart said of pornography, most people would be hard
pressed to define urban sprawl, but they know it when they see it.
Increasingly, however, that is not good enough. As more and more metropolitan
areas debate the costs and consequences of poorly managed expansion, there
is an increasing need to be clear about the terms of the discussion. Politicians
and planners aiming to contain sprawl also must have an agreed-upon way
to define and measure it in order to track their progress. Beyond that,
it is important for policy makers to be able to demonstrate how, and to
what degree, sprawl has real implications for real people.
The study underlying this report, the product of three years of research
by Reid Ewing of Rutgers University, Rolf Pendall of Cornell University,
and Don Chen of Smart Growth America represents the most comprehensive
effort yet undertaken to define, measure and evaluate metropolitan sprawl
and its impact. This report is the first in a series of findings to be
issued based on the ongoing analysis of that work.
Sprawl Defined
Beginning with an
exhaustive review of the existing academic and popular literature, the
researchers identified sprawl as the process in which the spread of development
across the landscape far outpaces population growth. The landscape sprawl
creates has four dimensions: a population that is widely dispersed in
low density development; rigidly separated homes, shops, and workplaces;
a network of roads marked by huge blocks and poor access; and a lack of
well-defined, thriving activity centers, such as downtowns and town centers.
Most of the other features usually associated with sprawl—the lack
of transportation choices, relative uniformity of housing options or the
difficulty of walking—are a result of these conditions.
Creating an Index of Metropolitan Sprawl
Based on this understanding,
the researchers set about creating a sprawl index based on four factors
that can be measured and analyzed:
- Residential
density;
- Neighborhood
mix of homes, jobs, and services;
- Strength
of activity centers and downtowns;
- Accessibility
of the street network.
Each of these factors is in turn composed of several measurable components,
a total of 22 in all. Residential density, for example, includes the proportion
of residents living in very spread-out suburban areas, the portion of
residents living very close together in town centers, as well as simple
overall density and other measures. Before being included, each variable
was tested through technical analysis to ensure that it added something
unique to the overall portrait of sprawl.
The information assembled for each of 83 metropolitan areas (representing
nearly half of the nation’s population) produced a richly textured
database that offers the most comprehensive assessment of metropolitan
development patterns available to date. This study is the first to create
such a multidimensional picture of the sprawl phenomenon and analyze related
impacts.
Comparing and Evaluating Metro Regions
Based on its performance, each metro area earned a score in each of the
four factors, indicating where it falls on the spectrum relative to other
regions. Much of the value of this study is in this ability to look at
the particular ways in which individual regions sprawl.
Some metro areas were found to sprawl badly in all dimensions. These include
Atlanta, Raleigh and Greensboro, NC. A few metros did better than other
regions in all four factors; among them are San Francisco, Boston, and
Portland, Oregon. Other metro areas are more of a mixed bag; in those
cases, the individual factor scores can tell us more about the characteristics
of individual metro areas. For example, while the Columbia, SC or Tulsa,
OK metro areas contain large swaths of low-density development, the presence
of a number of strong centers bring them up in the overall ranking. And
while San Jose, California, has slightly higher density than most metro
areas, its lack of centers of activity pulls it down in the overall ranking.
The scores for the four factors were combined to calculate the overall
Four Factor Sprawl Index, ranking the most and least sprawling metropolitan
areas. On the Index, the average is 100, with lower scores indicating
poorer performance and more sprawl, while higher scores show less sprawl.
Using this Index, the most sprawling metro area of the 83 surveyed is
Riverside, California, with an Index value of 14.22. It received especially
low marks because:
- it has
few areas that serve as town centers or focal points for the community:
for example, more than 66 percent of the population lives over ten miles
from a central business district;
- it has
little neighborhood mixing of homes with other uses: one measure shows
that just 28 percent of residents in Riverside live within one-half
block of any business or institution;
- its residential
density is below average: less than one percent of Riverside’s
population lives in communities with enough density to be effectively
served by transit;
- its
street network is poorly connected: over 70 percent of its blocks are
larger than traditional urban size.
In
the overall national ranking, Riverside is followed by Greensboro, NC;
Raleigh, NC; Atlanta, GA; Greenville, SC; West Palm Beach, FL; Bridgeport,
CT; Knoxville, TN; Oxnard-Ventura, CA; and Ft. Worth, TX.
Metropolitan Region Overall Sprawl Index Score Rank
Riverside-San Bernardino, CA PMSA 14.2 1
Greensboro-Winston-Salem-High Point, NC MSA 46.8 2
Raleigh-Durham, NC MSA 54.2 3
Atlanta, GA MSA 57.7 4
Greenville-Spartanburg, SC MSA 58.6 5
West Palm Beach-Boca Raton-Delray Beach, FL MSA 67.7 6
Bridgeport-Stamford-Norwalk-Danbury, CT NECMA 68.4 7
Knoxville, TN MSA 68.7 8
Oxnard-Ventura, CA PMSA 75.1 9
Fort Worth-Arlington, TX PMSA 77.2 10
At the other end of
the scale, the metro area with the highest overall score is, not surprisingly,
New York City, closely followed by Jersey City just across the Hudson
River. (New York and Jersey City are such extreme “outliers”
that they were excluded from most of the comparative analysis discussed
later in the report.) Providence, San Francisco, and Honolulu round out
the top five most compact metros, followed by Omaha, NE, Boston, Portland,
OR, Miami, and New Orleans.
Sprawl’s Impacts on Quality of Life
This initial report
examines several transportation-related measures and impacts and finds
that people living in more sprawling regions tend to drive greater distances,
own more cars, breathe more polluted air, face a greater risk of traffic
fatalities and walk and use transit less. Although this study was not
designed to prove that land-use patterns cause those conditions, sprawl
and its component factors were found to be a greater predictor than numerous
demographic control variables that were also tested.
Among the impacts of sprawl found:
- Higher
rates of driving and vehicle ownership. The research indicates that
in relatively sprawling regions, cars are driven longer distances per
person than in places with lower-than-average sprawl. Over an entire
region, that adds up to millions of extra miles and tons of additional
vehicle emissions. Also, the study found that in the ten most sprawling
metropolitan areas, there are on average 180 cars to every 100 households;
in the least sprawling metro areas (excluding New York City and Jersey
City, which are outliers), there are 162 cars to every 100 households.
The research indicates that this is not simply a matter of greater or
lesser affluence; even controlling for income, households are more likely
to bear the expense of additional vehicles in more sprawling areas.
- Increased
levels of ozone pollution. The study found that the degree of sprawl
is more strongly related to the severity of peak ozone days than per
capita income or employment levels. The difference in ozone peaks appears
significant enough to potentially mean the difference between reaching
or failing to meet federal health-based standards. Failing to reach
the standard not only imperils the health of children and other vulnerable
populations, but also subjects regions to a raft of rigorous compliance
measures.
- Greater
risk of fatal accidents. Residents of more sprawling areas are at
greater risk of dying in a car crash, the research indicates. In the
nation’s most sprawling region, Riverside CA, 18 of every 100,000
residents die each year in traffic crashes. The eight least sprawling
metro areas all have traffic fatality rates of fewer than 8 deaths per
100,000. The higher death rates in more sprawling areas may be related
to higher amounts of driving, or to more driving on high-speed arterials
and highways, as opposed to driving on smaller city streets where speeds
are lower. Speed is a major factor in the deadliness of automobile crashes.
- Depressed
rates of walking and alternative transport use. In more sprawling
places, people on their way to work are far less likely to take the
bus or train or to walk. Twice the proportion of residents take public
transit to work in relatively non-sprawling metro areas versus those
with below-average scores. Likewise, thousands more residents walk to
work in regions that sprawl less.
- No
significant differences in congestion delays. The research found
that sprawling metros exhibited the same levels of congestion delay
as other regions. This finding challenges claims that regions can sprawl
their way out of congestion.
Policy Recommendations
This study shows that
sprawl is a real, measurable phenomenon with real implications for peoples’
everyday lives. Regions wishing to improve their quality of life should
consider taking steps to reduce sprawl and promote smarter growth. Based
on this research, Smart Growth America offers six policy recommendations:
1) Reinvest in Neglected Communities and Provide More Housing Opportunities
2) Rehabilitate Abandoned Properties
3) Encourage New Development or Redevelopment in Already Built Up Areas
4) Create and Nurture Thriving, Mixed-Use Centers of Activity
5) Support Growth Management Strategies
6) Craft Transportation Policies that Complement Smarter Growth
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