Answer:
They are nearly equal culprits in sprawl nationwide.
Graphic Illustration: View a bar graph
that shows the nationwide growth in each factor.
Explanation: Approximately
two dozen major factors have been suggested as culprits in sprawl:
| |
1. |
One
factor is population growth. |
| |
2. |
All
the other factors combine to create growth in per capita
land consumption -- in other words, an increase in the
average amount of urbanized land used by each resident
of a city. |
A major
controversy in the efforts to halt the rural land loss is
whether land-use and consumption decisions are the primary
engines of urban sprawl, or whether it is the nation's continuing
population boom providing most of the power driving the expansion.
A careful
analysis of U.S. Census Bureau data found that the two sprawl
factors share equally in the blame:
(1)
Population Growth: The other half of sprawl is related to
the increase in the number of residents within those 100
Urbanized Areas.
(2) Per Capita Sprawl: About half the sprawl nationwide
appears to be related to the land-use and consumption choices
that lead to an increase in the average amount of urban
land per resident.
On average,
there are more of us, and each of us is using more urban land,
and therein lies the two halves of the problem.
By placing
the Per Capita Sprawl percentage next to the Population Growth
percentage for each Area, we can visually and immediately
gain a fairly clear idea about which factor has played a larger
role in the equation that has produced an Urbanized Areaœs
sprawl.
Despite
the considerable complexity of sprawl in an urban area, nearly
all of the complexity can be boiled down to what ends up being
a rather simple equation:
[The amount
of land covered by an Urbanized Area]
is equal to
[the average amount of urban land per resident]
multiplied by
[the number of residents].
Overall
Sprawl then is the change in that amount of total urban land
and can be calculated using the change in per capita land
consumption and the change in population.
A sample
village illustrates how growth factors work.
We can
see this equation at work by visualizing a small village with:
- 400
residents
- an
average of 0.200 acre land consumption per resident for
all housing work, retail, recreational, transportation and
other needs
- a fully
developed area of the village of 80 acres (400 X 0.200 acre)
Letœs
say we revisit this village a few years later and find that
the fully developed area has expanded 50% to 120 acres. There
can be only three types of explanation:
1. The
400 villagers may have expanded their per capita land consumption
by 50% from 0.200 acre to 0.300 acre (400 X 0.300 acre = 120
acres). This could have happened by households dividing by
divorce or children leaving home and the departees starting
new households, by people expanding the size of their houses
and yards, by constructing additional public and business
buildings, and by abandoning homes and stores within the old
boundaries to move just outside those boundaries, perhaps
adding a shopping mall and large parking lot on the townœs
edge.
2. OR
the per capita land consumption may not have risen at all
while 200 additional people moved into the village, causing
a 50% increase in population to 600 (600 X 0.200 acre = 120
acres).
3. OR
there may have been some combination of both population growth
and per capita land consumption growth. One example would
be that population grew 25% to 500 and per capita land use
grew 20% to 0.240 acre (500 X 0.240 acre = 120 acres).
Each of
the nation's sprawling Urbanized Areas has been expanding
in one of those three ways.
Since
all of Overall Sprawl is explained by the combination of population
change and per capita consumption change, we can learn much
about their relative roles by simply lining up those percentage
changes side by side.
The bar
graph at the bottom of the page lumps all 100 Urbanized Areas
together and finds that their population change was 23.6%
and their per capita land change was 22.6%. Thus, we easily
see that the roles of the two growth factors are nearly identical
in urban sprawl nationwide.
|
| |
Urbanized
Area
(number is where city ranks
in square miles of sprawl)
|
Sprawl
Factors
Percent Growth
|
|
|
Population
|
Per
Capita Land
Consumption
|
 |
Akron,
OH (79)
|
-2.7%
|
29.9%
|
 |
|
Albany-Schenectady-Troy,
NY (75)
|
4.6%
|
32.5%
|
|
|
Albuquerque,
NM (44)
|
67.1%
|
18.1%
|
|
|
Allentown-Bethlehem-Easton,
PA (85)
|
12.9%
|
27.8%
|
|
|
Atlanta,
GA (1)
|
84.0%
|
42.0%
|
|
|
Austin,
TX (23)
|
112.5%
|
49.9%
|
|
|
Bakersfield,CA
(87)
|
71.8%
|
0.0%
|
|
|
Baltimore,
MD (14)
|
19.6%
|
60.0%
|
|
|
Baton
Rouge, LA (52)
|
46.7%
|
49.5%
|
|
|
Birmingham,
AL (27)
|
11.5%
|
59.3%
|
|
|
Boston,
MA (19)
|
4.6%
|
28.2%
|
|
|
Bridgeport-Milford,
CT( 99)
|
0.1%
|
7.9%
|
|
|
Buffalo-Niagara
Falls, NY (68)
|
-12.2%
|
52.1%
|
|
|
Charleston,
SC (32)
|
72.5%
|
46.6%
|
|
|
Charlotte,
NC (39)
|
63.0%
|
40.3%
|
|
|
Chattanooga,
TN-GA (37)
|
32.8%
|
65.7%
|
|
|
Chicago,
IL-NW Indiana (13)
|
1.2%
|
22.6%
|
|
|
Cincinnati,
OH- KY (25)
|
9.2%
|
39.8%
|
|
|
Cleveland,
OH (100)
|
-14.4%
|
15.0%
|
|
|
Colorado
Springs, CO (60)
|
72.4%
|
13.8%
|
|
|
Columbia,
SC (53)
|
35.8%
|
41.8%
|
|
|
Columbus,
OH (46)
|
19.6%
|
22.9%
|
|
|
Corpus
Christi, TX (96)
|
26.9%
|
-5.9%
|
|
|
Dallas-Fort
Worth, TX (7)
|
58.7%
|
-15.1%
|
|
|
Dayton,
OH (83)
|
-10.6%
|
36.4%
|
|
|
Denver,
CO (29)
|
44.9%
|
8.1%
|
|
|
Des
Moines, IA (82)
|
14.8%
|
27.5%
|
|
|
Detroit,
MI (18)
|
-6.9%
|
37.9%
|
|
|
El
Paso, TX-NM (51)
|
69.2%
|
9.1%
|
|
|
Flint,
MI (71)
|
-1.2%
|
72.1%
|
|
|
Ft.
Lauderdale-Hollywood-Pompano, FL (43)
|
101.7%
|
-23.6%
|
|
|
Fresno,
CA (80)
|
72.5%
|
-2.7%
|
|
|
Grand
Rapids, MI (65)
|
23.7%
|
23.4%
|
|
|
Greenville,
SC (64)
|
58.0%
|
32.2%
|
|
|
Harrisburg,
PA (69)
|
21.7%
|
57.1%
|
|
|
Hartford-Middletown,CT
(45)
|
17.5%
|
57.4%
|
|
|
Honolulu,
HI (97)
|
43.0%
|
-15.7%
|
|
|
Houston,
TX (2)
|
72.9%
|
26.4%
|
|
|
Indianapolis,IN
(59)
|
11.5%
|
10.3%
|
|
|
Jackson,
MS (35)
|
52.2%
|
97.4%
|
|
|
Jacksonville,
FL (31)
|
39.4%
|
3.6%
|
|
|
Kansas
City, MO-KS (15)
|
15.7%
|
33.4%
|
|
|
Knoxville,
TN (40)
|
59.8%
|
59.0%
|
|
|
Lansing-E.
Lansing, MI (95)
|
15.5%
|
16.4%
|
|
|
Las
Vegas, NV (47)
|
194.6%
|
-35.3%
|
|
|
Little
Rock-North Little Rock, AR (50)
|
37.2%
|
52.4%
|
|
|
Los
Angeles, CA (6)
|
36.5%
|
-8.4%
|
|
|
Louisville,
KY-IN (67)
|
2.1%
|
31.5%
|
|
|
McAllen,Edinburg-Mission,
TX (56)
|
188.8%
|
31.6%
|
|
|
Memphis,
TN (34)
|
24.3%
|
40.4%
|
|
|
Miami-Hialeah,
FL (54)
|
57.0%
|
-13.2%
|
|
|
Milwaukee,
WI (76)
|
-2.1%
|
14.6%
|
|
|
Minneapolis-Saint
Paul, MN (10)
|
22.0%
|
20.8%
|
|
|
Mobile,
AL (74)
|
16.7%
|
16.5%
|
|
|
Nashville,
TN (38)
|
27.8%
|
10.1%
|
|
|
New
Haven-Meriden, CT (62)
|
29.6%
|
35.0%
|
|
|
New
Orleans, LA (61)
|
8.2%
|
35.7%
|
|
|
New
York City-N.E. New Jersey (3)
|
-1.0%
|
23.6%
|
|
|
Norfolk-Virginia
Beach-Newport News, VA (20)
|
41.3%
|
6.2%
|
|
|
Ogden,
UT (55)
|
73.1%
|
44.8%
|
|
|
Oklahoma
City, OK (12)
|
35.3%
|
41.0%
|
|
|
Omaha,
NE-IA (86)
|
10.7%
|
15.3%
|
|
|
Orlando,
FL (17)
|
190.4%
|
3.2%
|
|
|
Oxnard-Ventura,
CA (84)
|
96.4%
|
-28.3%
|
|
|
Pensacola,
FL (58)
|
52.2%
|
53.7%
|
|
|
Philadelphia,
PA (5)
|
5.0%
|
47.5%
|
|
|
Phoenix,
AZ (9)
|
132.4%
|
-17.7%
|
|
|
Pittsburgh,
PA (24)
|
-9.1%
|
43.5%
|
|
|
Portland-Vancouver,
OR-WA (42)
|
42.1%
|
2.4%
|
|
|
Providence-Pawtucket,
RI-MA (77)
|
6.4%
|
15.0%
|
|
|
Raleigh,
NC (48)
|
100.9%
|
24.2%
|
|
|
Richmond,
VA (30)
|
41.6%
|
47.8%
|
|
|
Riverside-San
Bernardino, CA (33)
|
100.5%
|
-25.9%
|
|
|
Rochester,
NY (66)
|
3.0%
|
46.5%
|
|
|
Sacramento,
CA (57)
|
73.1%
|
-21.0%
|
|
|
St.
Louis, MO-IL (16)
|
3.4%
|
52.9%
|
|
|
Salt
Lake City, UT (70)
|
64.7%
|
-16.3%
|
|
|
San
Antonio, TX (21)
|
46.2%
|
34.4%
|
|
|
San
Diego, CA (11)
|
96.0%
|
-7.5%
|
|
|
San
Francisco-Oakland, CA (22)
|
21.5%
|
5.7%
|
|
|
San
Jose, CA (73)
|
40.0%
|
-12.8%
|
|
|
Scranton-Wilkes-Barre,
PA (98)
|
-9.1%
|
22.4%
|
|
|
Seattle,
WA (26)
|
40.9%
|
1.0%
|
|
|
Shreveport,
LA (81)
|
9.3%
|
42.1%
|
|
|
Spokane,
WA (91)
|
21.5%
|
20.2%
|
|
|
Springfield,
MA-CT (72)
|
3.6%
|
22.6%
|
|
|
Stockton,
CA (94)
|
63.4%
|
-3.5%
|
|
|
Syracuse,
NY (90)
|
3.4%
|
34.3%
|
|
|
Tacoma,
WA (49)
|
49.5%
|
21.0%
|
|
|
Tampa-St.
Petersburg- Clearwater, FL (8)
|
97.8%
|
12.9%
|
|
|
Toledo
,OH-MI (93)
|
0.3%
|
16.5%
|
|
|
Trenton,
NJ-PA (92)
|
8.9%
|
34.5%
|
|
|
Tucson,
AZ (36)
|
96.9%
|
19.6%
|
|
|
Tulsa,
OK (41)
|
27.8%
|
32.3%
|
|
|
Washington,
DC-MD-VA (4)
|
35.5%
|
40.9%
|
|
|
West
Palm Beach-Boca Raton, FL (28)
|
176.4%
|
-18.7%
|
|
|
Wilmington,
DE-NJ-MD-PA (63)
|
21.1%
|
41.2%
|
|
|
Wichita,
KS (88)
|
12.1%
|
22.7%
|
|
|
Worcester,
MA- CT (78)
|
27.6%
|
28.8%
|
|
|
Youngstown-Warren,
OH (89)
|
-8.6%
|
42.3%
|
|
|
Average
Urbanized Area (mean)**
|
41.7%
|
23.5%
|
|
|
Aggregate
average***
|
23.6%
|
22.6%
|
|
|
