Sprawl and Urban Development

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					Sprawl and Urban
  Development
         Nonurban Sprawl
• The county’s growth rate is in the upper
  quartile of the “economic area’s” annual
  county household and employment growth
  rates
• The county’s growth rate exceeds the
  average annual national county growth
  rate
• The county’s absolute level of growth
  exceeds 40% of the average annual
  absolute county growth.
        Urban Sprawl Defined
• 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.
  Measuring Sprawl Objectively
• 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 Sprawl




• The places where housing is most spread out include a
  number of medium-sized metro areas in the southeast.
• These are places where growth has mostly occurred
  during the automobile era, and have been without
  topographic or water related constraints that otherwise
  restrict development.
• The prevalence of low residential densities in this
  particular region is striking and merits further
  investigation.
     Neighborhood Mix of Homes,
         Shops, and Offices




•   One of the characteristics of sprawl is the strict segregation of
    different land uses. In sprawling regions, housing subdivisions are
    typically separated—often by many miles—from shopping, offices,
    civic centers, and even schools.
•   This separation of uses is what requires every trip to be made by car,
    and can result in a “jobs-housing imbalance” in which workers cannot
    find housing close to their place of work.
•   More traditional development patterns tend to mix different land uses,
    often placing housing near shops, or offices above storefronts.
•   Measuring the degree of mix is therefore an important descriptor of
    sprawl.
Comparison of Low-Density Sprawl
      With New Urbanism
 Strength of Metropolitan Centers




• Metropolitan centers are activity centers that help businesses thrive
  and support alternative transportation modes and multipurpose trip
  making.
• Connectedness can be represented by concentrations of
  employment or population.
• It can also represent a single dominant center or multiple
  subcenters.
    Lessons from The Most Sprawling
             Metro Regions




•   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.
Impacts of Sprawl on Travel
   What is a Growth County?
• Have Maintained Double-Digit Rates of Population
  Growth for Each Census Since 1950
• Are Located in the Nation’s 50 Largest
  Metropolitan Areas as of the 2000 Census
• Come in Three Sizes:
  – “MEGA” Over 800,000 People
  – “Edge” Between 200,000 to 800,000 People
  – “New Metropolis” Under 200,000 People
• BoomBurb
        Three Types of Growth
              Counties
• MEGA Counties - 23 massively enlarged, growth-
  accelerated counties with a total population of 37 million
• Edge Counties – 54 areas mostly at or near the edge of
  their regions and often at the leading edge of
  metropolitan growth with a total population of 20.8
  million.
• New Metropolis Counties – 47 counties lying mostly at
  the regional fringe, generally do not contain large
  concentrations of commerce, and are updated versions
  of bedroom suburbs with a total population of 4.7 million.
                MEGA Counties
• Found mostly in booming regions of the Sunbelt.
   –   Harris County, TX        - Maricopa County, AZ
   –   Travis County, TX        - Palm Beach, FL
   –   Orange County, CA        - Broward County, FL
   –   Clark County, NV         - Miami–Dade County, FL
   –   Santa Clara County, CA   - Travis County, TX
   –   Fairfax County, VA       - Santa Clara County, CA
   –   Maricopa County, AZ      - Dallas County, TX

• They can be big suburban counties outside the
  nation’s largest cities
• Now perhaps as important to the nation’s commerce
  as any of its large traditional cities.
• Home to many of the largest office centers in the
  nation that lie outside of a central business district
                Edge Counties
• Typically contain “Edgeless Cities” which are a form of
  sprawling office development that never reaches the
  densities or cohesiveness of Edge Cities (mostly isolated
  office buildings at varying densities over vast swaths of
  metropolitan space).
• Older metropolitan areas have high-density traditional
  cores and rings of older, pedestrian-oriented suburbs,
  they also feature new, so-called sprawling growth, which
  is often found in Edge Counties.
• Edge Counties are growth engines because in many of
  these older regions they account for a majority of new
  people added despite often containing just a small share
  of the total metropolitan population.
    New Metropolis Counties
• So-named because they are new to their regions -
  having been added to the official metropolitan
  statistical area after 1971.
• They reflect the new metropolitan growth pattern -
  they are all low-density, centerless, and sprawling.
• The New Metropolis Counties may be Edge
  Counties in formation.
• Residents of New Metropolis Counties often work in
  Edge Counties, which means that more commutes
  are originating in what were once rural areas.
• Thus, commercial development in Edge Counties
  fuels the emergence of New Metropolis Counties,
  which in turn promotes even more population growth
  farther and farther from the regional core.
• New Metropolis Counties are the new suburbs of
  suburbs, which in the future may spawn even more
  distant suburbs.
                   Boomburbs
• A boomburb is a large, rapidly growing city that remains
  essentially suburban in character even as it reaches
  populations more typical of urban core cities.
• A boomburb is an area that currently has more than
  100,000 residents and has maintained double-digit rates
  of population growth in each recent decade, but is not
  the largest city in its metropolitan area.
• Boomburbs almost never have a dense central business
  area.
• And their housing, retail, entertainment, and offices are
  spread out and loosely configured.
              Boomburbs
• They're located in 14 metro areas
  surrounding Phoenix, Los Angeles, San
  Diego, San Francisco, Denver, Miami,
  Tampa, Chicago, Las Vegas, Portland,
  Dallas, Salt Lake City, Norfolk and Seattle.
• Boomburbs range from Mesa, Ariz., with
  nearly 400,000 residents, to Westminister,
  Colo., with just over 100,000.
1989
                                 2009




On the southeastern outskirts of the Phoenix metropolitan area, Chandler grew
from just 3,799 residents in 1950 to 176,581 residents in 2000, based on 10-year
census figures. The differences between these images indicate that a significant
portion of that growth happened after 1989.
1989 Florida Growth Pattern Study: Capital Facility
                  Costs Under
      Sprawl Versus Compact Development
         (per dwelling unit; 1990 dollars)
Comparison of Residential Densities on
         Costs & Revenues
       Monterey County, CA




                                   2002
Built Environment Effects to
       Travel Behavior
 (Ewing and Cervero, 2002)
       REGIONAL EFFORTS TO
       CONTROL URBAN FORM
• Inasmuch as land use planning is usually at the center of
  regional planning, regional planning efforts usually focus
  on how the urban area could look different than it would
  have otherwise.
• The desired difference is usually in the direction of more
  centers and density.
• At the regional level, the options for urban form are few
  in theory and in practice. For any predicted amount of
  growth, a region can
   – (1) continue what has in U.S. cities been a universal pattern of
     suburbanization (residential growth accommodated in relatively
     low density development, primarily at the urban fringe);
   – (2) try to get that growth to concentrate more in the central city
     and major subcenters within the existing metropolitan area
     (urban growth boundaries); or
   – (3) deflect the growth to satellite cities not contiguous to the
     metropolitan area.
      Comparing and Evaluating
        Metropolitan Regions
• 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.
Sprawl’s Impact on Quality of Life
• Higher rates of driving and vehicle
  ownership.
• Increased levels of ozone pollution.
• Greater risk of fatal crashes.
• Depressed rates of walking and
  alternative transport use.
• No significant differences in
  congestion delays
Alleged Negative & Positive
     Impacts of Sprawl
Markets Where Policies to Change Urban Form are Likely to Have
            Direct (Internalized) Effects on Prices

                                •   This figure shows the hypothesis
                                    that the main effects of a change
                                    in form should be captured
                                    through changes in the costs of
                                    providing infrastructure services.
                                •   An important and defensible
                                    assumption is that the effect of
                                    urban form on households,
                                    businesses, and governments
                                    occurs mainly through a derived
                                    demand for infrastructure, an
                                    intermediate good.
                                •   The conclusion is that the impact
                                    of changes in urban form on the
                                    cost of infrastructure is probably
                                    the single most important impact
                                    to evaluate.
                                •   That approach, with infrastructure
                                    as the sole concern, does not
                                    cover everything, either technically
                                    or politically.
    Sprawl and Health Concerns



• Because this study is ecologic and cross-sectional in nature, it
  is premature to imply that sprawl causes obesity, hypertension,
  or any other health condition.
• Our study simply indicates that sprawl is associated with
  certain outcomes.
• Future research using quasi-experimental designs is needed to
  tackle the more difficult job of testing for causality.
  “Relationship Between Urban Sprawl and Physical Activity, Obesity, and Morbidity” by Reid Ewing, Tom Schmid, Richard Killingsworth,
  Amy Zlot, Stephen Raudenbush in the American Journal of Health Promotion, Inc., September/October 2003, Vol. 18, No. 1
Sprawl, Weight and Blood Pressure
Sprawl & Obesity
  Policy Recommendations for
Regions Wishing to Reduce Sprawl
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
 Selected Statistics On Urban/Suburban
Density & Growth In 15 MSAs, 1990–2000
                                Population Per Square Mile
                                         Statistics
                                                                                                               MSA             2000 Density
                                                                                                  Little Rock-N. Little Rock            201
                                                                                                            Syracuse                    238
                                                                                                          Rockford IL                   239
                                      Normal(675.26, 399.60)                                              Chattanooga                   255
                 1.8                                                                                        Knoxville                   281
                                                                                                            Nashville                   302
                 1.6                                                                                        Memphis                     378
                                                                                                     Portland-Vancouver                 382
                 1.4                                                                                      New Orleans                   394
                                                                                                          Sacramento                    399
Values x 10^-3




                 1.2                                                                                      St. Louis MO                  407
                                                                                                          Jacksonville                  418
                 1.0                                                                            Charlotte-Gastonia-Rock Hill            444
                                                                                                     Minneapolis-St. Paul               490
                 0.8                                                                                       Pittsburgh                   510
                                                                                                  Seattle-Bellevue-Everett              546
                 0.6                                                                                         Denver                     561
                                                                                                             Dayton                     565
                 0.4                                                                                          Dallas                    569
                                                                                                      Ft. Worth-Arlington               584
                 0.2                                                                                         Atlanta                    672
                                                                                                            Houston                     706
                 0.0                                                                                Buffalo-Niagara Falls               747
                                                                                                        Washington DC                   756
                       0.0


                              0.2


                                       0.4


                                               0.6


                                                       0.8


                                                             1.0


                                                                   1.2


                                                                            1.4


                                                                                   1.6


                                                                                         1.8
                                                                                                    Salt Lake City-Ogden                825
                                             Values in Thousands                                   Cleveland-Lorain-Elyria              832
                                                                                                 Tampa-St. Pete-Clearwater              938
                     <                           0 %
                                                9 .0                               .0
                                                                                  5 %    >                 Baltimore                    979
                    .0 8
                   0 1                                                    .3 3
                                                                         1 3                                  Detroit                 1,140
                                                                                               New Haven-Bridgeport-Stamford          1,261
                       Source: U.S. Census Bureau                                                            Newark                   1,289
                                                                                                            San Jose                  1,304
                               Statistical Abstract of the United States, 2002                              Oakland                   1,642
                                                                                                         San Francisco                1,705
                                    Median
            Central City Employment Statistics
                                                                                                        MSA             % CC Emp
                                                                                                      Newark             10.44%
                                                                                                    Pittsburgh           13.88%
                                                                                          Tampa-St. Pete-Clearwater      14.66%
                                                                                                     Oakland             15.09%
                            Normal(0.32440, 0.18489)                                         Salt Lake City-Ogden        15.62%
4.0
                                                                                                      Dayton             15.65%
                                                                                                       Detroit           16.16%
                                                                                            Cleveland-Lorain-Elyria      17.39%
3.5
                                                                                                     Syracuse            20.00%
                                                                                        New Haven-Bridgeport-Stamford    20.39%
3.0                                                                                                 Baltimore            21.04%
                                                                                             Buffalo-Niagara Falls       24.02%
2.5                                                                                              Washington DC           24.25%
                                                                                                      Denver             24.39%
2.0
                                                                                                   Sacramento            24.77%
                                                                                           Seattle-Bellevue-Everett      25.51%
                                                                                              Portland-Vancouver         25.63%
1.5
                                                                                                     Knoxville           26.14%
                                                                                               Ft. Worth-Arlington       29.82%
1.0                                                                                                   Atlanta            31.13%
                                                                                                   New Orleans           32.15%
0.5                                                                                        Little Rock-N. Little Rock    32.65%
                                                                                                   Chattanooga           33.38%
0.0
                                                                                         Charlotte-Gastonia-Rock Hill    37.18%
                                                                                                   Rockford IL           37.82%
      0.0


              0.1


                      0.2


                             0.3


                                    0.4


                                          0.5


                                                0.6


                                                        0.7


                                                              0.8


                                                                      0.9


                                                                            1.0


                                                                                  1.1              St. Louis MO          41.83%
                                                                                                  San Francisco          43.83%
       <                      0 %
                             9 .0                                    .0
                                                                    5 %           >
                                                                                                     Nashville           45.99%
       .0 0
      0 2                                        .6 9
                                                0 2                                                  Houston             46.82%
                                                                                                     San Jose            50.55%
      Source: US Census Bureau data                                                                  Memphis             55.78%
              www.demographia.com                                                                  Jacksonville          65.84%
                                                                                                       Dallas            66.34%
                                                                                              Minneapolis-St. Paul       96.84%
                    Median
Exurban Living
Comparing Sprawl and Smart
         Growth
Surface Coverage of Different
     Land Use Classes
Automobile Contributions
    Toward Sprawl
 Household Annual Municipal
Costs by Residential Densities
Transportation Costs That
   Increase with Sprawl
Annual Household Auto Costs
   Under Four Densities
                Sprawl – A Reprise




•   Automobile dependency has a number of negative land use impacts.
•   It increases the amount of land paved for roads and parking which has
    economic, social and environmental costs.
•   Automobile oriented cities devote up to three times as much land to roads
    and parking as traditional, pedestrian-oriented cities.
•   Automobile dependency tends to result in lower density, urban periphery
    development (sprawl), which imposes a number of economic, social and
    environmental costs.
•   Sprawl increases the amount of land used per capita for roads, parking, and
    buildings and reduces the land left for agricultural and wildlife habitat.
•   Under most conditions it increases costs for public services.

				
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