Comparison: Urban Sprawl in the US and “Sprawl-like patterns” in China:

Quantitate Studies, Theoretical Basis, and Driving Factors

Wenjiao WuGeography and Planning Department, University at Albany

IntroductionUrban 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.

BackgroundAfter 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 million people (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 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 Area1. 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 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 1Quickfacts about the Chinese cities studied

Xiamen Yinchuan

Land area (km²) 1,699 4,467Population (million) 3.73 2.08GDP 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 466Source: Xiamen Economic and Social Development Report 2013, Yinchuan Economic and Social Development Report 2013Table 2Quickfacts about the US cities studied

AtlantaAtlanta Metropolitan Area

PhoenixPhoenix Metropolitan Area

Land area (km²) 343 21,694 1338 37,7252013 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 1,537,137Housing 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. Census Bureau.Fig. 1. Map of Yinchuan, 1989-2013

Fig. 2. Map of Xiamen, 1996-2014

Fig. 3. Map of Atlanta, 1984-2014

Fig. 4. Map of Phoenix, 1985-2914

Data and MethodsA 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 islands impact, 1996-2014

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 classification combined 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 3List of landscape metrics used in the study (based on McGarigal and Marks, 1995)Landscape metric DescriptionPatch density (PD) The number of patches in 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:%)Edge density (ED) The total length of all edge segments per

hectare for the land-cover class or landscape of consideration (unit: m/ha)

Mean Patch Area (AREA_MN) The average area of all patches in the landscape (unit:ha)

Patch Area Standard Deviation (AREA_SD)

The standard deviation of patch size in the landscape (unit:ha)

Perimeter-Area Fractal Dimension (PAFRAC)

2 divided by the slope of regression line obtained by regressing the logarithm of patch area (m2) against the logarithm of patch perimeter (m)

Contagion (CONTAG) Measures spatial aggregation of patches by computing the probability that two randomly chosen adjacent grid cells will be of the same patch type

Shannon’s Diversity Index (SHDI)

Minus the sum, across all patch types, of the proportional abundanceof each patch type multiplied by that proportion

Percentage of Landscape (PLAND)

The sum of the areas of all patches of the corresponding patch type, divided by total landscape area (unit:%)

ResultsThe 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

Fig. 7. Landscape metrics of Xiamen

Fig. 8. Landscape metrics of Atlanta

Fig. 9. Landscape metrics of Phoenix

Fig. 10. Percentage of Landscape (PLAND) of Yinchuan

1 dense veg

2 water 3 sparse veg

4 high density built-up

area

5 low density built-up

area

6 sand0.04.08.0

12.016.020.0

1995 2013

Fig. 11. Percentage of Landscape (PLAND) of Xiamen

1 water 2 dense veg

3 sparse veg

4 cropland 5 low density urban

6 high density urban

0.05.0

10.015.020.025.0

1996 2014

Fig. 12. Percentage of Landscape (PLAND) of Atlanta

high density veg

low density veg low density built-up

high density built-up

0.05.0

10.015.020.025.030.035.040.0

1984 2014

Fig. 13. Percentage of Landscape (PLAND) of Phoenix

bare veg soil urban veg/soil mix

sand rock/road0.05.0

10.015.020.025.030.0

1985 2014

Table 4. Transition matrix of Yinchuan (Probabilities of >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 0.06water 0.31 0.20 0.22 0.12 0.11 0.04

sparse veg 0.02 0.30 0.23 0.21 0.17 0.06high density built-

up area 0.06 0.22 0.33 0.14 0.19 0.06low density built-up

area 0.03 0.16 0.23 0.09 0.30 0.18sand 0.01 0.09 0.15 0.08 0.34 0.33

Table 5. Transition matrix of Xiamenwater dense

vegsparse

vegcropland low

density urban

high density urban

water 0.85 0.02 0.00 0.01 0.07 0.05dense veg 0.06 0.52 0.19 0.06 0.10 0.06sparse veg 0.01 0.22 0.62 0.09 0.04 0.02

cropland 0.01 0.13 0.26 0.28 0.23 0.09low density

urban 0.01 0.06 0.11 0.26 0.41 0.16high

density urban

0.01 0.07 0.06 0.19 0.43 0.24

Table 6. Transition matrix of Atlantalow density

built-uphigh density

veglow density

veghigh density

built-uphigh density veg 0.32 0.44 0.16 0.08low density veg 0.08 0.57 0.25 0.10

low density built-up 0.18 0.24 0.45 0.13high density built-

up 0.20 0.04 0.18 0.58

Table 7. Transition matrix of Phoenixrock/road

veg bare urban soil veg/soil mix

sand

rock/road 0.72 0.03 0.05 0.16 0.02 0.01 0.01bare 0.12 0.01 0.58 0.15 0.11 0.02 0.01veg 0.15 0.27 0.05 0.22 0.13 0.09 0.08soil 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 0.03veg/soil

mix 0.07 0.03 0.03 0.11 0.12 0.44 0.20sand 0.10 0.08 0.03 0.16 0.14 0.15 0.34

Fig. 14. Locality of Atlanta’s suburban sprawl, 1984

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.

Discussion1 USTradition, 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 impactsWhether 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 changesFrom 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 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 studiedAtlanta, 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).

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 of the spatial revolution of an 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 (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 ChinaPlanning historyChinese 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 landEscaped 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 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’s GDP growth, 1978-2010. Source: China Statistical Yearbook 2011

1978198

0198

2198

4198

6198

8199

0199

2199

4199

6199

8200

0200

2200

4200

6200

8201

00

5000

10000

15000

20000

25000

30000

35000Per capita GDP (RMB)

Table 8. Shares of GDP and annual growth rates for primary, secondary, and tertiary industries, 1978-2010. Source: China Statistical Yearbook 2011

PercentageGDP (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 Rate1978-2010 9.9 4.6 11.4 10.91991-2010 10.5 4 12.5 10.72000-2010 10.5 4.2 11.5 11.2

The two cases studiedLocated 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 of Xiamen’s urban afforestation and planning

3 Comparison and Further DiscussionDecentralization and urbanization trend in the two countriesThe 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 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.

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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.

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AcknowledgementsI 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 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.