1. Comparison: Urban Sprawl in the US and
“Sprawl-like patterns” in China: Quantitate
Studies, Theoretical Basis, and Driving
Factors
Wenjiao Wu
Geography and Planning Department, University at Albany
Introduction
Urban sprawl in the United States has been an important issue ever since World War
II and is widely studied. On the other side of the world, the term “urban sprawl” is
also used to describe the growth pattern of Chinese cities in recent studies. Two cities
in each country are chosen to analyze their urban growth patterns and land cover
changes, by processing Landsat images and taking quantitate methods. The theoretical
basis of urban planning and social/economical background in each country are shortly
discussed, and the driving factors of urban growth pattern in each city are analyzed
separately. The results of comparison indicate that it is still controversial to use the
term “urban sprawl” in Chinese city studies.
Background
After World War II, Americans’ way of living has changed dramatically. The
structure of urban system can be summarized in terms of two apparently
contradictory (but in fact interrelated) outcomes: regional decentralization and
metropolitan consolidation. A dramatic spurt in suburban growth occurred, and the
1950s became the decade of the greatest-ever growth in suburban population. While
central cities in the United States grew by 6 million people (11.6 percent), suburban
counties added 19 millionpeople (45.9 percent). In almost every metropolitan area
the suburban grew much faster than the central city (or cities) (McCarthy & Knox,
2005). The trend continues till today: while more than one-half of the world’s
population now living in urban areas, every two American urban cores that are
growing, and three are shrinking. In the United States alone, 59 cities with a
population of 100,000 or more have lost at least 10 percent of their inhabitants since
1950 (Duany, Speck & Lydon, 2010).
The product is sprawl, which is described as “Buildings rarely rise shoulder to
shoulder, as in Chicago’s loop. Instead, their broad, low outlines dot the landscape
like mushrooms, separated by greensward and parking lots” (Garreau, 2011), the most

2. popular form of house for the new suburbs is a single-story structure with a low-slung
roof, large windows, and a carport or garage (McCarthy & Knox, 2005). In the second-
half 20th century, living in such suburban area with individual lawn and enough
space has become the new “American dream” for white middle-class Americans
(Ibid).
Sprawl is usually defined as ‘haphazard growth’ of relative low density over an
extended region, with residential units dominated by single family homes (Gottdiener
& Budd, 2005), or in an economics perspective, as spatial growth of cities that is
excessive relative to what is socially desirable (Brueckner, Mills, & Kremer, 2001).
Ever since suburbanization became a mass phenomenon in the 1950s, urbanists have
lamented the pattern of sprawl characteristic of that growth like the US and Canada
(Gottdiener & Budd, 2005), for it raises clear efficiency and equity concerns:
unproductive congestion on roads, high levels of metropolitan car pollution, the loss
of open space amenities, and unequal provision of public goods and services across
sprawling metropolitan suburbs that give rise to residential segregation and pockets of
poverty (Nechyba & Walsh, 2004).
On the other side of the world, China is facing unprecedented prosperity (in terms of
economics) and rapid urbanization after Deng Xiaoping’s opening-up policies in early
1980s. The term “sprawl” is used in recent studies to describe urban growth patterns
of cities or metropolitan area such as Guangzhou, Nanjing, and Western Taihu Lake
watershed area (Yu & Ng, 2007; Su et al., 2010; Feng & Li, 2012).
Study Area
1. Yinchuan: the capital of Ningxia Hui Autonomous Region, 38.4667° N,
106.2667° E, one of the transportation junction cities in North Western China,
located on the west bank of the upper course of the Yellow River, in the
south-central section of the Helan Mountains and Ordos Desert
(approximately on the boundary of animal husbandry culture areas and
cultivation culture areas, and the boundary of Northern-Western arid/semi-
arid areas and Eastern monsoonal areas), desert climate.
2. Xiamen: 24.4798° N, 118.0894° E, located on the southeast (Taiwan Strait)
coast, also historically known as Amoy, one of the earliest port cities in China.
The first city of Fujian Province by 2013 (in terms of per capita GDP), one of
the four original Special Economic Zones opened to foreign investment and
trade when China began economic reforms. Monsoonal humid subtropical
climate.
3. Atlanta, GA: the capital of Georgia State, 33.7550° N, 84.3900° W. One of the
cities grew rapidly in the late half of 20th
century because “increased
accessibility, combined with the attractions of cheaper land, lower taxes, lower

3. energy costs, local boosterism, and cheaper and less-militant labor, allowed
cities in the South and West to grow rapidly”, a notably Sunbelt city that
offered strong locational and entrepreneurial assets (McCarthy & Knox, 2005).
Atlanta metro area is the most sprawling among the US metro areas in the
2014 sprawl index rankings (Ewing & Hamidi, 2014). Humid subtropical
climate.
4. Phoenix, AZ: the capital of Arizona State, 33.4500° N, 112.0667° W. The most
populous state capital in the United States, as well as the sixth most populous
city nationwide, one of the largest cities in the United States by land area (U.S.
Census Bureau). It is not so much meaningful to study Phoenix city alone as
the area is a polycentric area without too much space between the cities,
therefore the study area locates in the whole area.
Table 1
Quickfacts about the Chinese citiesstudied
Xiamen Yinchuan
Land area (km²) 1,699 4,467
Population (million) 3.73 2.08
GDP Per Capita (USD) 13,166 9,956
GDP Composition
Primary Industry (Agriculture) 0.90% 4.40%
Secondary Industry (Industry & Construction) 47.50% 54.00%
Tertiary Industry (Service) 51.60% 41.60%
Population Density (per km²) 2,195 466
Source: Xiamen Economic and Social Development Report 2013, Yinchuan Economic and Social
Development Report 2013
Table 2
Quickfacts about the US citiesstudied
Atlanta
Atlanta
Metropolitan
Area
Phoenix
Phoenix
Metropolitan
Area
Land area (km²) 343 21,694 1338 37,725
2013 Estimated Population
(million)
0.45 5.52 1.51 4.40
Population Density (per km²) 1312 251 1129 117
Housing units, 2010 224,573 2,165,495 590,149 1,537,137
Housing units in multi-unit
structures, percent, 2009-2013
53.90% N/A 31.90% N/A
Per capita money income 2010 35,453 37,493 19,833 24,809
Source: U.S. CensusBureau.
Fig. 1. Map of Yinchuan,1989-2013

4. Fig. 2. Map of Xiamen, 1996-2014
Fig. 3. Map of Atlanta, 1984-2014

5. Fig. 4. Map of Phoenix,1985-2914
Data and Methods
A series of Landsat images downloaded from United States Geological Survey (USGS)
EarthExplorer (http://earthexplorer.usgs.gov/) were used for this study, four images of
each city respectively in 1980s, 1990s, 2000s, 2010s were chosen to study the
landscape variation tendency. (There was not proper image of 1980s’ Xiamen
available, and the artificial island construction during 2000s had caused different
numbers of class from the other images, therefore there were only two images of
Xiamen were analyzed.)
Fig. 5. The classification results with artificial islandsimpact, 1996-2014

6. The product chosen was Landsat Climate Data Record Category (CDR) – (Land
Surface Reflectance Datasets). Images of 2010s were from Landsat 8 OLI (Operational
Land Imager) and TIRS (Thermal Infrared Sensor) and the others from Landsat 4-5
TM (Thematic Mapper). CDR product was surface reflectance product hence no
atmospheric correction was needed, cloud and cloud shadow masks could also be used
to eliminate impacts of clouds, if there were any.
Then the images were classified in Erdas Imagine 2014, types and numbers of classes
of each city are different based on real dominant land cover types. The methods were
ISODATA unsupervised classificationcombined with supervised classification, and
Google Earth was used as a reference to improve accuracy.
Post-classification comparison was used as change detection technique since it can
provide thematic maps and complete matrix of change information (Lu et al., 2004).
After classification, transition matrices were generated in Erdas Imagine 2014 by
creating a criteria function model in model maker.
To quantify spatial patterns, a suite of landscape-level metrics were calculated in
Fragstats version4.2. They include compositional and configurational metrics:
compositional metrics are Percentage of Landscape (PLAND), Patch density (PD),
Edge density (ED), Shannon’s Diversity Index (SHDI), Largest Patch Index (LPI),
Mean Patch Area (AREA_MN), and Patch Area Standard Deviation (AREA_SD),
configurational metrics are Perimeter-Area Fractal Dimension (PAFRAC), and
Contagion (CONTAG) (Buyantuyev, Wu & Gries, 2010).
Table 3
List of landscape metrics used in the study (based on McGarigal and Marks, 1995)
Landscape metric Description
Patch density (PD) The numberof patchesin the landscape,divided by total
landscape area (unit: patches/100 ha)
Largest Patch Index (LPI) Percent of the landscape occupied by the largest patch
(unit:%)

7. Edge density (ED) The total length ofall edge segments per hectare for the land-
cover class or landscape ofconsideration (unit: m/ha)
Mean Patch Area (AREA_MN) The average area of all patchesin the landscape (unit:ha)
Patch Area Standard Deviation
(AREA_SD)
The standard deviation ofpatch size in the landscape
(unit:ha)
Perimeter-Area Fractal Dimension
(PAFRAC)
2 divided by the slope of regression line obtained by
regressing the logarithmof patch area (𝑚2
) against the
logarithmof patch perimeter (m)
Contagion (CONTAG) Measures spatial aggregation ofpatchesby computing the
probability that two randomly chosen adjacent grid cellswill
be of the same patch type
Shannon’sDiversity Index (SHDI) Minus the sum, across all patch types, of the proportional
abundanceofeach patch type multiplied by that proportion
Percentage of Landscape (PLAND) The sum of the areas of all patchesof the corresponding
patch type,divided by total landscape area (unit:%)
Results
The four cities all have an ascending Patch density (PD), which indicates higher
spatial heterogeneity in the process of urbanization of suburban sprawl; a descending
Mean Patch Area (AREA_MN), which indicates higher habitat fragmentation –
Yinchuan has the most growth rate of PD and the most decrement rate of AREA_MN
(based on definition of the two indices, the rates actually the same value); a
descending Patch Area Standard Deviation (AREA_SD), which indicates lower patch
size variability; an ascending Edge density (ED), which means there are higher total
length of edge segments in an unit area – it is noticeable that Atlanta has the highest
absolute magnitude edge density, which is corresponding to its typical suburban
sprawl land cover type: Fig. 14 actually shows that how little natural habitat is “safe”
from sprawl. The complexity index Perimeter-Area Fractal Dimension (PAFRAC)
does not show significant change for all the cities, except for a tiny rise in Atlanta and
Phoenix from 2000s to 2010s. The richness and evenness index Shannon’s Diversity
Index (SHDI) has some fluctuation for the four cities, stable in general though. The
patch/patch type interspersion index contagion (CONTAG) has a descending trend for
all the four cities, which means the patches are getting smaller and more dispersed,
thus more poorly interspersed.
Fig. 6. Landscape metrics of Yinchuan

8. Fig. 7. Landscape metrics of Xiamen
Fig. 8. Landscape metrics of Atlanta

9. Fig. 9. Landscape metrics of Phoenix

10. Fig. 10. Percentage of Landscape (PLAND) of Yinchuan
Fig. 11. Percentage of Landscape (PLAND) of Xiamen
0.0
5.0
10.0
15.0
20.0
1 dense veg 2 water 3 sparse veg 4 high density
built-up area
5 low density
built-up area
6 sand
1995 2013

11. Fig. 12. Percentage of Landscape (PLAND) of Atlanta
Fig. 13. Percentage of Landscape (PLAND) of Phoenix
Table 4. Transition matrix of Yinchuan (Probabilitiesof>0.15 are shown in bold, hereinafter inclusive)
water dense veg high
density
built-up
area
sparse veg low
density
built-up
area
sand
dense veg 0.02 0.30 0.18 0.28 0.15 0.06
water 0.31 0.20 0.22 0.12 0.11 0.04
sparse veg 0.02 0.30 0.23 0.21 0.17 0.06
high density built-up area 0.06 0.22 0.33 0.14 0.19 0.06
0.0
5.0
10.0
15.0
20.0
25.0
1 water 2 dense veg 3 sparse veg 4 cropland 5 low density
urban
6 high density
urban
1996 2014
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
high density veg low density veg low density built-up high density built-up
1984 2014
0.0
5.0
10.0
15.0
20.0
25.0
30.0
bare veg soil urban veg/soil mix sand rock/road
1985 2014

12. low density built-up area 0.03 0.16 0.23 0.09 0.30 0.18
sand 0.01 0.09 0.15 0.08 0.34 0.33
Table 5. Transition matrix of Xiamen
water dense veg sparse veg cropland low density
urban
high density
urban
water 0.85 0.02 0.00 0.01 0.07 0.05
dense veg 0.06 0.52 0.19 0.06 0.10 0.06
sparse veg 0.01 0.22 0.62 0.09 0.04 0.02
cropland 0.01 0.13 0.26 0.28 0.23 0.09
low density
urban
0.01 0.06 0.11 0.26 0.41 0.16
high density
urban 0.01 0.07 0.06 0.19 0.43 0.24
Table 6. Transition matrix of Atlanta
low density
built-up
high density veg low density veg high density
built-up
high density veg 0.32 0.44 0.16 0.08
low density veg 0.08 0.57 0.25 0.10
low density built-up 0.18 0.24 0.45 0.13
high density built-up 0.20 0.04 0.18 0.58
Table 7. Transition matrix of Phoenix
rock/road veg bare urban soil veg/soil
mix
sand
rock/road 0.72 0.03 0.05 0.16 0.02 0.01 0.01
bare 0.12 0.01 0.58 0.15 0.11 0.02 0.01
veg 0.15 0.27 0.05 0.22 0.13 0.09 0.08
soil 0.07 0.01 0.14 0.10 0.38 0.25 0.04
urban 0.21 0.06 0.07 0.42 0.16 0.04 0.03
veg/soil mix 0.07 0.03 0.03 0.11 0.12 0.44 0.20
sand 0.10 0.08 0.03 0.16 0.14 0.15 0.34
Fig. 14. Locality ofAtlanta’s suburban sprawl, 1984

13. Yinchuan (nickname “a city with thousands of lakes” has experienced the most
dramatic change in the last two decades. Built-up area has grown for a great extent,
both high-density and low-density, almost every land cover type has a significant
probability of changing into built-up area; large areas of wetlands or lakes are
developed into residential area or paddy fields, in this case classified as dense
vegetation (see Table 4). The percentage of water in the studied area decreases from
18.2 to 4.3, the change mainly happens in wetlands or lakes, the flow of Yellow River
does not show significant change. Some part of the sand near the city has been
transformed into low density built-up area, which is corresponding with first
observation.
Some of Xiamen’s low density residential areas become more compact, and there are
some mutual transition between croplands and low density residential areas, and
between dense vegetation and sparse vegetation. The urban area does not show an
increasing tendency, on the contrast, the vegetation increases.
In Atlanta, the high density built-up area almost stays the same and low density built-
up area decreases. The result is counter-intuitive, possibly caused by some driving
factors besides climate disparity in different years (discussed below).
The urban area of Phoenix Metropolitan Area continues to grow, almost every land
cover type has a significant probability of transforming into urban area. The
vegetation which occupied a quite small percentage of the study area continues to
decrease. It is noticeable that rock/road (it is always difficult to distinguish these two
land cover types when numbers of the classes is small) land cover type has increased
significantly.

14. Discussion
1 US
Tradition, philosophy, “bottom-up” planning theory.
To have a better understanding why American cities have faced the problem of
suburban sprawl from 1950s till today, it is necessary to know the theoretical basis of
the planning theory and how it developed. Duany et al. (2001) state that unlike the
traditional neighborhood model, which evolved organically as a response to human
needs, suburban sprawl is an idealized artificial system. The sprawl planning theory is
“sweeping aside of the old”.
The left-wing geographical ideology can probably trace back to Geographer Patrick
Geddes (1854-1932), who shared similar ideas with anarchist scholars Élisée Reclus
(1830-1905) and Peter Kropotkin (1842-1921) (Hall 2014), Geddes and Kropotkin
almost simultaneously rejected the palaeotechnic city, argued planned
decentralization from the congested Victorian industrial city and the transformation
from palaeotechnic to neotechinic urbanism, from the age of coal and steam to the
age of electricity and the motor vehicle (Hall 2000).
Planning laws and codes impacts
Whether the theory had an important impact on Government’s decision, it was until
a series of planning policies occurred that American really got on the road from “top-
down to bottom-up” (Hall 2000) planning. Those policies conspired powerfully to
encourage urban dispersal, the most significant of these were the Federal Housing
Administration and Veterans Administration loan programs which in the years
following the Second World War, provided mortgages for over eleven million new
homes. These mortgages which typically cost less per month than paying rent, were
directed at new single-family suburban construction (Duany, Plater-Zyberk & Speck,
2001).
And the “bottom-up” theory went on. The most notable was Frank Lloyd Wright,
whom we shall logically consider as a leading exponent of the roadside city. He had
thought a city built by its own inhabitants, using mass-producted components. Many
of his thoughts, whether consciously or not, were shared with the Regional Planning
Association of America: anarchism, liberation by technology, naturalism, agrarianism,
the homesteading movement (Hall 2014). This ideology of self-build was widely
attacked that it went underground for another 30 years, until it reappeared as
Berkeley, in the writings of Christopher Alexander (Ibid). The third world informal
housing also had few echoes in the first world in 1968 (Ibid).
Social and economic changes
From Hall (2014)’s statement, the “bottom-up” theory was not the mainstream of
urban planning theories, however, we must admit that social/economic condition and

15. the emergence of suburban sprawl is supplement to each other. After 1945 a second
surge of growth in car ownership occurred in the United States. From just under 26
million in 1945, the number of cars on the roads jumped to more than 52 million in
1955 and just over 97 million by 1972 (McCarthy & Knox, 2005). During the same
time, a 41,000-mile interstate highway program coupled with federal and local
subsidies for road improvement had occurred (Duany, Plater-Zyberk & Speck, 2001).
Moreover, a rapid decline of the old base of manufacturing industries was followed by
the onset of a “new economy” based on digital technologies and knowledge-based
industries, which divided the labors, international finance, and the ascendance of
neoliberal politics and policy (McCarthy & Knox, 2005) - “bottom-up” theory was
logically a part of it, the result was a dramatic spurt in suburban growth. Geddes and
Kropotkin’s “palaeotechnic to neotechinic urbanism” had come true with a more
complex sort of economy than they had planned.
The two cases studied
Atlanta, the center of an approximate hexagon formed by several interstate highways,
is the distribution, financial and communications hub of the southeastern region. The
radical pattern is convenient for burgeoning subdivisions, in other words, sprawl to
grow (a growing built-up area along the highway can be observed in the study area).
Since 1960, simultaneous outflow of Whites and inflow of Blacks had resulted in a
nominal increase in population and poverty. A study at that time indicated the city
should not continue to engage in massive and disconnected clearance projects and
relocation programs (Kaplan et al. 1969). Then Model City Program, an element of
U.S. President Lyndon Johnson's Great Society and War on Poverty, began with the
Demonstration Cities and Metropolitan Development Act of 1966, Atlanta city was
one of the focal points that got funds. The program emphasized on not only
rebuilding, but also rehabilitation, social service delivery, and citizen participation
(local decision-making). However, the nation moved to the right after the urban riots
of the late 1960s and the program ended in 1974 (Weber and Wallace, 2012).
And time went by. The study result of Atlanta 1984-2014 shows ecological restoration
and the Atlanta city itself seems become more compact, though Atlanta Metropolitan
Area has the highest sprawl index in the US. Yang and Lo (2003) simulate the
development trend of Atlanta when the growth rate is slowed down and the growth
pattern is altered – their results show that with a smart growth strategy with
emphasis on environmental protection, much more greenness and open space,
including buffer zones of large streams and lakes could be preserved. Whether the
change of the city is result of an altered growth policy is yet to be studied. It is also
possible a result of temporary economic decline in around 2008 and 2009 (Fig. 15).

16. Fig.15. Per capita personal income in Atlanta Metropolitan Statistical Area,shaded areas indicate US
recessions. Source: U.S. Bureau of Economic Analysis and FRED economic data website.
Fig.16. Hypothetical sequence ofthe spatial revolution ofan urban area. Source: Dietzel et al. (2005)
The urban area expansion of Phoenix Metropolitan area follows the diffusion-
coalescence model described by Dietzel et al. (2005) (Fig. 16). As “new development
cores” around Phoenix city share high homogeneity from observation, it makes more
sense to study the whole urban area rather than the principal city Phoenix city itself.
The process starts with the expansion of an urban area seed or core area. As the seed
grows, it disperses growth to new development centers or cores. While urban
diffusion continues, it is accompanied by organic growth which leads to the outward
expansion of existing urban areas and the infilling of gaps within them. At the end,
the diffusion of urban areas reaches a point where they begin to coalesce towards a
saturated urban landscape (Dietzel et al. 2005). At the beginning time period of this
study, Phoenix Metropolitan area has already reaches the step between highly
diffusion and finally coalesces. By now, the limited spaces between the municipal
cities almost vanish. Besides urban expansion, the increasing of “road” land cover type
probably indicates there is a growing transportation need between the cities.
With a relatively lower tax in the United States and warm weather in winter,
Phoenix attracts large amount of “seasonal” elderly population and tourists, which call
for more residential/creational places and public infrastructure to be built. Heim

17. (2012) argues that tax revenues competition between the local governments has
resulted in extensive urban growth and “boundary wars”.
Both located in desert area, Phoenix and Yinchuan have a notable urban expansion,
but the growth patterns differ: polycentric diffusion-coalescence and unicentric
expansion.
2 China
Planning history
Chinese cities had experienced a “medieval urban revolution” during 589-1368. It was
a time period that the ancient Chinese settlements evolved into urban systems to
serve administrative and military functions to meet the need of the emperor; free
trade was prosperous and population burst. In the following 1368-1911 period there
were some “top-down” planning projects like the Forbidden City. After the emperor
collapsed, a series of treaty port cities grew dramatically under the planning of
“foreign forces” like Shanghai, Xiamen and Harbin (Wu & Gaubatz 2012). Then China
fell into Mao’s ultra-left regime: international investments were forced to withdraw,
urban population were expelled to rural areas. In conclusion, China has no scientific
or systematic urban planning theory; the process of urbanization is highly influenced
by central governments or driven by external forces.
The emergence of private economy and public-ownership of land
Escaped from Mao’s code which had a rigorously control on the exchange of product
and migration, China’s economy has had a skyrocketing increase (Fig. 17 and Table 8
). According to United Nations’ prediction, Shanghai, Beijing, Shenzhen, Chongqing,
Guangzhou will be on the “Trading Places on the Top 25 List: The World’s Largest
Metropolitan Areas” in 2025, while in 1990 only Shanghai and Beijing were on the
list (http://esa/un.org/unpd/wup/index.htm).
The rapid urbanization results from relatively free flow of labor force. Labor market
did not exist under China’s command economy (Wu & Gaubatz 2012), in which the
change of residence or working place is highly limited or even restricted. “Danwei”
(refers to official organizations or public-own industries) does not play a dominant
role in every ordinary man’s life anymore, they move from less-developed areas to
cities or “arrival cities” (discussed below) to seek a living – the increasing percentage
of tertiary industry and decreasing percentage of primary industry indicate that
people are less “bounded” to their farmlands (Table 8). In urban or urban-buffer area,
individual or family-unit economies are raising, which causes dramatic urban-
suburban area expansion in those cities with smaller limitation of terrain (like
Yinchuan) and significant centralization effect in those cities limited by mountains
(like Xiamen). In Yinchuan many people are occupied in modern agriculture, while in

18. Xiamen large amounts of migrants will engage themselves to private or international
labor-intensive industry or tertiary industry.
Another driving factor of rapid urbanization is the public-ownership of land.
Practically China has accepted free market economy; it still sticks to socialism in
terms of ideology and propaganda, though. People cannot really buy or own the land
legally; instead, they can only rent it from governments. They leave the rural land
which costs huge efforts but get little outputs, to seek new fortunes toward the
direction of cities. Elder population and under-aged children are left in rural area,
which brings a series of critical social issues – that is another topic.
In comparison, the conflicts and tensions caused by urban spaces are more acute in
the United States because of the civil liberties enshrined in private land ownership. It
did not take long before some groups mobilized against the land users they perceived
as threats, hazards, or nuisances. Their objective was the legal exclusion of particular
land uses from certain parts of the city. The outcome was principle of land use zoning,
established in the Euclid v. Amber case in 1926, allowed uniform residential tracts
with stable property values (McCarthy & Knox, 2005), and known to be as a
regulatory mechanism that would become a key instrument the specialization and
segregation characteristic of land use in U.S. cities (Ibid).
Fig.17. China’sGDP growth, 1978-2010. Source: China Statistical Yearbook 2011
Table 8. Shares of GDP and annual growth rates for primary, secondary,and tertiary industries,1978-2010.
Source: China Statistical Yearbook 2011
Percentage
0
5000
10000
15000
20000
25000
30000
35000
Per capita GDP (RMB)

19. GDP (100 million
RMB) Primary Industry Secondary Industry Tertiary Industry
1978 3645.2 28% 48% 24%
1990 18667.8 27% 41% 32%
2000 99214.6 15% 46% 39%
2010 401202 10% 47% 43%
Annual Growth Rate
1978-2010 9.9 4.6 11.4 10.9
1991-2010 10.5 4 12.5 10.7
2000-2010 10.5 4.2 11.5 11.2
The two cases studied
Located in the desert, Yinchuan which has strong reliance on the Yellow River is a
critical wheat-and-rice producing area in Northwest part of China since ancient
times. Agriculture still plays an important part in its economy nowadays (Table 1.)
when compared with Xiamen, the urbanized area began to rapidly grow only after
1990s. More wetlands were transformed into croplands to meet the need of boosting
urban population. As a transportation junction in less-developed Northwest area and
less land use limitation (in terms of nature), it shows somehow “sprawl-like” patterns
for its rather low population density and large areas of low density built-up, however,
it can be distinguished from sprawl due to the centralization trend (high density
built-up area is also growing rapidly). It has a relatively fragile ecosystem, and the
ecological consequences of these kinds of rapid urban expansion and development are
yet to be studied.
Located along the southeast coast, Xiamen has experienced the first wave of
international investments and migrants from rural areas or inner provinces inrush.
The study results in Xiamen seem anti-intuition. In consideration of there being
certainly not an economic decline and population decrease, it is probably because the
“centralization” effects and higher-rise buildings (note: as one of the Special
Economic Zones, Xiamen is the only city in Fujian Province that does not include
counties or cities at county level, only districts), and the afforestation of urban area
and arterial streets (mainly classified as dense vegetation). See Fig.18, the
neighborhood becomes more organized also. The high urbanization level and on-the-
way centralization indicates that it is also far from sprawl.
Fig.18. Locality ofXiamen’s urban afforestation and planning

20. 3 Comparison and Further Discussion
Decentralization and urbanization trend in the two countries
The term “edge city” is invented by Garreau (2011). He seems to have a positive
attitude towards the edge city: “It is about Americans who, when confronted by crisis,
do not wait for the authorities to show up.” Other scholars have different points of
view. According to Nechyba & Walsh (2004), edge city (clusters of population and
economic activity at the urban fringe) is one of the forms of urban sprawl as well as
low-density residential developments. Edge city is a product of decentralization –
American city centers, once filled up with jobs, become concentration of aging, poor
population and “minorities are the majority”, while the suburbs are getting more
homogeneously young, white, middle-class, and more retailing, commerce and
industry (Gottdiener & Budd, 2005). See Table 2, per capita income of Atlanta
Metropolitan area and Phoenix Metropolitan area is higher than that of Atlanta city
and Phoenix city respectively, which shown to be a significant indicator of the
decentralization trend. Similarly, Saunders (2011) invents a term “arrival city” to
describe the suburban areas of developing countries or some regions in developed
countries. It refers to an area of rural, poor, or minority population settlement before
they struggle into cities. They take cities as a hope of themselves and their families. In
other words, urbanization process is still on the way, just like what is observed in
Xiamen and Yinchuan.
With completely different theoretical basis, historical and current
social/economic/political settings and urban development trends, I believe that it is
highly controversial to use the term “urban sprawl” in Chinese city studies, or more
interpretation is needed if it is going to be used.
Government leading, or “bottom-up”?
One of the “local-decision making and war on poverty” program – Model Cities
Program was agreed to be a failure by both conservatives and radical historians,
though for very different reasons (Weber and Wallace, 2012). Hall (2014)’s one

21. example of “bottom-up” planning on the other side of the world is China “goes to the
Mountains and the Country” under Mao’s regime. A compelling example of “self-
build industry” - the rural industries, such as the notorious backyard steel furnaces of
the 1950s, proved to run at very high cost (Hall 2014). However, the so-called
“bottom-up” here is different from Geddes and Kropotkin’s anarchy “bottom-up”, the
former cannot be isolated from the power of government as Model Cities Program is
depended on Federal government’s funding.
On contrast, Xiamen has experienced great success in not only economic growth but
also city beautification and afforestation, which cannot be achieved with high tax
revenue and high city construction funds. That is not to say big government should
get back on the stage – the historical lessons have taught us, and American
conservatives have warned us enough. In fact, Chinese government takes great effort
to contain the speed of urbanization: for example, starting from 1996, anyone who
converts farmland to non-agricultural uses must recreate the same amount of land as
farmland; the household registration system is kept until today, therefore the
consideration of social welfare and education makes it difficult for elder and juveniles
to migrant into cities with the main labor force of the family; house purchase
restriction… The measures cannot solve problems essentially and even bring up more
social issues. In Ming and Qing Dynasties, the central government banned on
maritime trade or intercourse with foreign countries, however, a series of mega cities
along the coasts appeared. It is still needed to discuss whether the development
pattern like Xiamen is sustainable, and how long it will last.
With completely different social/economical/political backgrounds, whether “organic
growth” is good is far more than a philosophical issue. It must be considered
comprehensively in practical context.
References
Brueckner, J. K., Mills, E., & Kremer, M. (2001). Urban sprawl: Lessons from urban economics
[with comments]. Brookings-Wharton papers on urban affairs, 65-97.
Buyantuyev, A., Wu, J., & Gries, C. (2010). Multiscale analysis of the urbanization pattern of the
Phoenix metropolitan landscape of USA: Time, space and thematic resolution. Landscape and
Urban Planning, 94(3), 206-217.
Dietzel, C., Herold, M., Hemphill, J. J., & Clarke, K. C. (2005). Spatio‐temporal dynamics in
California's Central Valley: Empirical links to urban theory. International Journal of Geographical
Information Science, 19(2), 175-195.
Duany, A., Plater-Zyberk, E., & Speck, J. (2001). Suburban nation: The rise of sprawl and the
decline of the American dream. Macmillan.
Duany, A., Speck, J., & Lydon, M. (2010). The smart growth manual. New York: McGraw-Hill.
Ewing, R. H., & Hamidi, S. (2014). Measuring sprawl 2014.

22. Feng, L., & Li, H. (2012). Spatial pattern analysis of urban sprawl: Case study of Jiangning,
Nanjing, China. Journal of Urban Planning and Development,138(3), 263-269.
Garreau, J. (2011). Edge city: Life on the new frontier. Anchor.
Gottdiener, M., & Budd, L. (2005). Key concepts in urban studies. Sage.
Hall, P. (2000). The centenary of modern planning. Urban Planning in a Changing World: The
Twentieth Century Experience, 20-39.
Hall, P. (2014). Cities of Tomorrow: An Intellectual History of Urban Planning and Design Since
1880. John Wiley & Sons.
Heim, C. E. (2012). Border wars: Tax revenues, annexation, and urban growth in Phoenix.
International Journal of Urban and Regional Research, 36(4), 831-859.
Lu, D., Mausel, P., Brondizio, E., & Moran, E. (2004). Change detection techniques. International
journal of remote sensing, 25(12), 2365-2401.
Marshall Kaplan, Gans, and Kahn. (1969). The model cities program; a history and analysis of the
planning process in three cities: Atlanta, Georgia; Seattle, Washington; Dayton, Ohio.
Washington, Dept. of Housing and Urban Development; [for sale by the Supt. of Docs., U.S.
Govt. Print. Off.]
McCarthy, L. M., & Knox, P. L. (2005). Urbanization: An introduction to urban geography.
Pearson Prentice Hall.
McGarigal, K., & Marks, B. J. (1995). Spatial pattern analysis program for quantifying landscape
structure. Gen. Tech. Rep. PNW-GTR-351. US Department of Agriculture, Forest Service, Pacific
Northwest Research Station.
Nechyba, T. J., & Walsh, R. P. (2004). Urban sprawl. Journal of economic perspectives, 177-200.
Saunders, D. (2011). Arrival city: How the largest migration in history is reshaping our world.
Vintage.
Su, W., Gu, C., Yang, G., Chen, S., & Zhen, F. (2010). Measuring the impact of urban sprawl on
natural landscape pattern of the Western Taihu Lake watershed, China. Landscape and Urban
Planning, 95(1), 61-67.
Weber, B. A., & Wallace, A. (2012). Revealing the Empowerment Revolution: A Literature Review
of the Model Cities Program. Journal of Urban History, 38(1), 173-192.
Wu, W., & Gaubatz, P. R. (2012). The Chinese city. Routledge.
Yang, X., & Lo, C. P. (2003). Modelling urban growth and landscape changes in the Atlanta
metropolitan area. International Journal of Geographical Information Science, 17(5), 463-488.
Yu, X. J., & Ng, C. N. (2007). Spatial and temporal dynamics of urban sprawl along two urban–
rural transects: A case study of Guangzhou, China. Landscape and Urban Planning, 79(1), 96-
109.
Zhang, T. (2000). Land market forces and government's role in sprawl: The case of China. Cities,
17(2), 123-135.
Acknowledgements
I would like to thank Professor Buyantuyev for the technical support and patience,
we have a great time exchanging ideas; Professor Pipkin who has profound
knowledge. Thank all the professors in Geography and Planning Department, I have

23. had a pleasant journey of study from you in two years. Thank my beloved fiancé
Peter Zhang, who gave me encouragement and inspiration; the two Chinese cities
meant a lot to you.