Available online at www.sciencedirect.com
ScienceDirect Procedia Engineering 198 (2017) 915 – 925
Urban Transitions Conference, Shanghai, September 2016
Spatial Patterns of China’s Major Cities and Their Evolution Mechanisms during the Past Decades of Reform and Opening Up J. LVa, B.D. Yanga, Y.J. Yanga, Z.H. Zhangb, F. Chena,c*, G.J. Liuc a
School of Environmental Science and Spatial Informatics, China University of Mining and technology, Xuzhou, Jiangsu 221116,China; b China Land Surveying and Planning Institute, Beijing, Beijing-100029, China; c School of Mathematical and Geospatial Sciences, Royal Melbourne Institute of Technology University, Melbourne 3000, Australia;
Abstract This study focused on the patterns of urban sprawl in China’s major cities since1978. Information about the major urban built-up areas in China was extracted from the remote sensing images from multiple sources, such as the QuickBird, SPOT and TM, using the soil-vegetation-adjusted building index (SVBI). The trend of urban sprawl was analyzed by measuring the rate of urban expansion and growth rate of urban area. Then qualitative methods were employed to classify the spatial patterns of these cities and discuss the transformation mechanisms of these patterns. The results show that the rates of expansion and area growth in China’s major cities were stable between 1984 and 1994 and then sharply increased between 1994 and 2004, followed by a slowdown during 2004-2014. Natural setting was found to be the most essential and limiting factor in a city’s morphology. The qualitative analysis suggests that the sprawl patterns of China’s major cities were categorized into four groups: circular, leapfrog, interactive and belt-like patterns. Besides, traffic can guide the direction of urban sprawl. It was considered an important factor in urban sprawl and a determining factor in the transformation of urban morphology. Technological, socio-economic development was proved to have played a key role in the development of urban morphology and have acted as the greatest power for cities to withstand the impact of natural setting on their morphology. Moreover, city-industry integration and administrative divisions have also affected the development of spatial patterns of these cities. They have altered the internal links between different parts of a city and the driving forces behind urban development, facilitating formation of new spatial patterns. The findings about urban morphology and its transformation mechanisms can provide a scientific basis for cities to efficiently raise their management levels and formulate more rational plans for urban-space use. © 2017 The Authors. Published by Elsevier Ltd. © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license Peer-review under responsibility of the organizing committee of the Urban Transitions Conference. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the Urban Transitions Conference
* Corresponding author. Tel.: +86-0516-83883501; fax: +86-0516-83883501 E-mail address:
[email protected]
1877-7058 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the Urban Transitions Conference
doi:10.1016/j.proeng.2017.07.137
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J. LV et al. / Procedia Engineering 198 (2017) 915 – 925 Keywords: spatial pattern; spatial structure; dynamic mechanism; urban land; Chinese cities
1. Introduction Since the beginning of the reform and opening up, Chinese cities have achieved significant socio-economic progress during the remarkable urban development across the country [1-2]. However, the economic-growthoriented urban development also gives rise to unplanned and irrational urban sprawl [3,4] and the consequent waste of urban land, environmental pollution and higher transportation cost, and other prominent problems[5-8]. For this reason, a thorough investigation into the process, pattern and mechanism of urban sprawl as well as timely and accurate measurements can provide an important basis for search of forces driving urban development, control of unplanned urban sprawl, sustainable urban development and proper land management. Urban morphology refers to the characteristics of forms of cities during their development and transformation. The morphology of a city is the result of interaction between multiple factors such as natural setting, historical evolution, the functional structure of the city, spatial development policy, urban planning and management [9]. Scholars from China and other countries have carried out many studies of urban sprawl and morphology. In terms of research content, these studies have mostly focused on analyzing the process, mechanism, and characteristics of transformation of urban morphology and the driving forces behind urban sprawl, exploring the patterns of transformation and theoretical urban spatial patterns, and modeling urban sprawl [10-20]. Research methods used in these studies mainly include mathematical statistics, GIS spatial analysis, shape index, compactness, fractal dimension, convex hull, affinity propagation, landscape indexes, cellular automaton, information entropy, degree of freedom of urban sprawl, CONTAG, and sensory quality [21-36]. In terms of research scale, some studies focused on individual cities and urban agglomerations, while others were conducted on a regional or even national scale [37-39]. For instance, Lu Yi and Hu Shougeng used three indices, including the degree of freedom of sprawl, CONTAG and sensory quality, to measure the characteristics of sprawl of 216 Chinese cities during the period from 2000 to 2012 in a comprehensive way. They found that the Chinese cities surveyed were compact overall during expansion, and the cities in eastern and central China exhibited higher degrees of freedom of sprawl and CONTAG than those in other regions [40]. Through measuring the compactness, shape index, and fractal dimension of the built-up areas in 62 China’s major cities, Pan Jinghu and Dai Weili discovered that, during the period between 1990 and 2010, the cities in eastern China expanded at the fastest rates, followed by western cities, while the cities in central China showed the slowest rates of expansion [41]. However, few studies have examined the urban sprawl of Chinese cities during the period of reform and opening up on a national scale. In this study, data of polygons representing construction land in the central urban areas of 24 major cities in China was acquired from multi-period remote sensing images from QuickBird, SPOT and TM and then the sprawl patterns of these built-up areas were derived from the extracted data. The trends of urban expansion of the cities during three periods were analyzed from both macro and micro perspectives by measuring the rate of urban expansion and growth rate of urban area. The sprawl patterns of these cities were qualitatively analyzed based on the sorting of geographical information about the construction land in the 24 cities’ central urban areas in conjunction with GIS overlay map. The purpose of the study is to provide a scientific reference for making proper and efficient schemes of urban growth management in a new context. 2. Methods and Data Processing 2.1. Methods The sizes of the built-up areas in different years were obtained from the data of polygons representing built-up areas using GIS spatial analysis. Then the variation in area of the built-up land was analyzed. 2.1.1 Rate of urban expansion The rate of urban expansion of a city can be calculated using the following formula:
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V
A A b
a
˄1˅
T
Where V is the rate of urban expansion; Aa is the area of built-up land in the city’s built-up area at time a; Ab is the area of built-up land in the city’s built-up area at time b; and T represents time interval between times a and b. 2.1.2 Growth rate of built-up area The growth rate of built-up area can be calculated as follows:
A A A b
a
u 100%
˄2˅
a
Where Ø is the growth rate of built-up area; other parameters are the same as above. 2.2. Data processing The data used in this study includes high-resolution images from QuickBird, SPOT, and TM, as well as the cities’ topographic maps, land-use maps, graphs illustrating urban expansion and variation in administrative divisions since the beginning of reform and opening up, DEM data with a resolution of 30 m, and socio-economic and demographic statistics. Information about construction land in China’s major cities was extracted using ArcGIS10.2 and the soilvegetation-adjusted building index (SVBI) [16]. Figure 1 shows the specific steps of this method. DEM Data
High-resolution spatial images (QuickBird) Check and rectify
Supervised classification
Multi-temporal images TMǃSPOT
Image preprocessing
Topographic map, Land-use map Geometric correction Image enhancement
Remote sensing image based data
Extraction of urban built-up area information
Mosaic, cutting
SVBI
Raster conversion vector (RTV)
Extraction of urban Built-up area boundary
The terrace of the city boundary Fig. 1. Framework of data processing and analysis.
3. Results and Discussion 3.1. Analysis of characteristic quantities of urban sprawl Table 1 shows that during the periods between 1984 and 1994, between 1994 and 2004, and between 2004 and 2014, the expansion rates of Beijing, Harbin, Shanghai, Nanjing, Fuzhou, Guangzhou, and Chengdu followed an
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inverted-V pattern. Fourteen cities exhibited steady increases in expansion rate, including Tianjin, Shijiazhuang, Changchun, Shenyang, Hefei, Nanchang, Jinan, Zhengzhou, Nanning, Chongqing, Guiyang, Xi’an, Xining, and Urumqi. The expansion rates of Taiyuan and Lanzhou moved in a V pattern. The radar map in Figure 3 (a) illustrates the variation in the expansion rates of China’s major cities. As shown in the radar map, the expansion rates of China’s major cities during 1984-1994 were generally located within the first and second circles, indicating the expansion rate varied slightly between the cities; during 1994-2004, the expansion rate varied significantly from city to city, with Beijing located within the fifth circle, and Shanghai and Guangzhou within the fourth circle; during 2004-2014, these cities, excluding Chongqing, were located within the second and third circles, suggesting that the expansion rates of these cities differed slightly. As shown in Table 1, during 1984-1994, Shanghai demonstrated the highest growth rate of urban area, at 93.7%, while the growth rate of urban area of other cities tended to stabilize. During 1994-2004, all the cities underwent rapid expansion; the growth rates of urban area of 9 cities exceeded 100% and the highest rate reached up to 297.94%. During the period from 2004 to 2014, the urban expansion of these cities slowed down; 7 cities showed growth rates of urban area higher than 100%, with a maximum of 165.54%. The radar map depicting the variation in the growth rates of urban areas of China’s major cities shows that, overall, the growth rates of urban areas were relatively higher in the second period and dropped in the third period. Table 1 Urban expansion rate and Area growth rate of major cities in China from 1984 to 2014 Urban
Urban expansion rate (km2/year)
Area growth rate (%)
84-94
94-04
04-14
84-94
94-04
04-14
Beijing
10.1
71.5
12.4
27.60
153.10
10.49
Tianjin
9.7
16.1
23.6
40.08
47.49
47.20
Shijiazhuang
2.9
6
6.2
43.94
63.16
40.00
Taiyuan
3.2
0.9
14.3
23.53
5.36
80.79
Shenyang
3
9.7
16.4
18.29
50.00
56.36
Changchun
1.2
7.6
25.9
11.43
64.96
134.20
Harbin
0
13.7
9.8
0.00
87.82
33.45
Shanghai
16.9
43.1
10.5
93.37
123.14
13.44
Nanjing
3
33.4
22.8
25.00
222.67
47.11
Hefei
2.2
6.7
24.5
37.29
82.72
165.54
Fuzhou
1.8
10.2
8.2
39.13
159.38
49.40 85.19
Nanchang
0
7
11.5
0.00
107.69
Jinan
2.5
10.4
15.5
28.41
92.04
71.43
Zhengzhou
3.3
8.6
19.5
47.83
84.31
103.72
Guangzhou
1
45.4
35.4
4.85
210.19
52.84
Nanning
0.7
5
15.8
10.29
66.67
126.40
Chengdu
1
28.9
14.3
11.49
297.94
37.05
Chongqing
4.4
31.4
68.4
60.27
268.38
158.70
Guiyang
3.3
4.3
10.1
62.26
50.00
78.29
Kunming
4.1
7.4
20.7
54.67
63.79
108.95
Xi'an
1.5
7.4
20.2
11.28
50.00
90.99
Lanzhou
-1.6
-2.2
6.6
-8.94
-13.50
46.81
Xining
0.4
1
2.3
8.33
19.23
37.10
Urumqi
1.8
10.6
21.8
36.73
158.21
126.01
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84-94
94-04
04-14
84-94
Beijing Urumqi Tianjin 80 Xining Shijiazhu… 60 Lanzhou Taiyuan 40 Xi'an Shenyang 20 Kunming Changchun 0 Guiyang Harbin -20 Chongqing Shanghai Chengdu Nanjing Nanning Hefei Guangzhou Fuzhou Zhengzhou Nanchang Jinan
94-04
04-14
Beijing Urumqi Tianjin 300 Xining Shijiazhu… Lanzhou 200 Taiyuan Xi'an Shenyang 100 Kunming Changchun 0 Guiyang Harbin -100 Chongqing Shanghai Chengdu Nanjing Nanning Hefei Guangzhou Fuzhou Zhengzhou Nanchang Jinan
Fig. 2. Urban expansion rate (a) and Area growth rate (b) of China’s major cities
3.2. Analysis of patterns of urban sprawl The morphology of a city is determined by various factors, such as geographic conditions, economic development, and population. Table 2 summarizes the geographic conditions of China’s major cities studied here. Then the patterns of sprawl of these cities were qualitatively analyzed based on the geographic conditions in conjunction with the GIS overlay maps (Figure 3). The analysis found that some cities, such as Beijing, Shijiazhuang, Changchun, and Harbin, exhibited a circular pattern of sprawl due to few natural limitations, while cities with more natural limitations like rivers and mountains demonstrated leapfrog sprawl. In Shenyang, for example, the urban development of the Hunnan district had long been stagnant before the 1990s, because the Hun River forms a natural barrier against the southward expansion of urban Shenyang. Thanks to the scientific and technological development over the later years, especially after the establishment of the Hunnan New Area in 2001, the city enhanced its primary strategy ĀBig Hunnan, New Shenyang” and determined to extend its urban area beyond the Hunhe River. Moreover, some river-valley cities, such as Lanzhou, Xining and Urumqi, showed a beltlike sprawl pattern. Table 2 The expansion pattern of major cities in China Type
Sprawl pattern
City
locational factor
Beijing Shijiazhuang Changchun Shanghai Circular Plain city
Hefei Fuzhou
Around these cities in plain areas, due to the extension resistance is very small, So they generally were classified as Circular expansion.
Zhengzhou Nanning Chengdu Xi’an Shenyang Leapfrog
Harbin Nanchang
Shenyang, Harbin, Nanchang are plain cities, but as a result of crossing the river, they were classified as Leapfrog expansion.
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Belt-like
Star network
Jinan Guangzhou
Kunming
Jinan, Guangzhou in plain areas, but they are surrounded by mountains, rivers, and other restrictions, Jinan, Guangzhou were classified as Belt-like expansion. Kunming is located within the Kunming Basin. Geographically, its northwestern and northern parts are bounded by hills and low mountains and its southern part is restricted by the Dian Lake. So Kunming was classified as Star network expansion.
Lanzhou River-valley city
Belt-like
Xining
Affected by the valley, urban expansion has been largely restricted to strip along the valley.
Urumqi Circular
Chongqing
Although Chongqing is a mountain city, the urban geographical condition is good, Chongqing was classified as Circular expansion.
Leapfrog
Guiyang
Guiyang in relatively flat terrain, but is surrounded by mountains, urban expansion is restricted greatly, then expand to Jinyang district and Huaxi district, Guiyang was classified as Leapfrog expansion.
Belt-like
Taiyuan
Taiyuan is bounded by mountains on the west, north and east. The south-central part of the city features an alluvial fan created by the Fen River, which flows through the city from the north to the south. Taiyuan was classified as Belt-like expansion
Mountainous city with numerous rivers
Leapfrog
Nanjing
The Yangtze River and purple mountain are natural barriers to the expansion of the city, with the construction of Nanjing Yangtze River Bridge and the development of transportation, Nanjing was classified as Leapfrog expansion.
Port city
Circular
Tianjin
Situated in the northeastern part of the North China Plain, Tianjin is surrounded by the Bohai Sea to the east and the Yan Mountains to the north.
Mountainous city
3.3. Main factors affecting transformation of urban morphology 3.3.1 Socio-economic development City is an important carrier of social and economic development, and economic growth is the biggest driving force of urban spatial expansion, there is a stimulating effect of the social and economic development on the demand of urban land. Since the reform and opening up, China's social and economic gets rapid development, promoting urban infrastructure, based industrial, commercial and residential development and improving the urban demand, and thus promoting the urban spatial expansion. 3.3.2 City-industry integration and administrative divisions City-industry integration means the functional and spatial integrations of industries and cities for integrative development on the basis of cities. It affects urban expansion by strengthening the links between industries and cities and propelling urban expansion towards industrial clusters. Incorporating counties into urban districts by administrative means can drive the development of the new urban districts and thereby affect urban expansion. Urban expansion governed by city-industry integration and administrative divisions was classified as interactive expansion. 3.3.3 Traffic improvement Changes in traffic conditions are the most direct cause of variation in urban expansion. Physical connections between cities, hinterlands, and regions outside hinterlands primarily depend on traffic lines, and communication and transportation change the scale of urban expansion and urban morphology. China’s major cities largely expanded outward along traffic arteries, indicating that a city’s traffic pattern can guide the development and transformation of its spatial structure. The urban area of Beijing, for instance, initially expanded in concentric circles around the central urban area, and after a certain period, it tended to expand radially along the directions of least resistance, which was guided by traffic corridors. 3.3.4 Technological advance
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Fig. 3. The terrace of the built-up area of china’s major cities since 1978
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Natural setting affects the pattern of urban expansion. For example, rivers and mountains can impede urban expansion. Since the beginning of the reform and opening up, the rapid economic development and technological advance in China have substantially removed the obstacles to urban growth. In Shenyang, for example, the urban development of the Hunnan district had long been stagnant before the 1990s, because the southward expansion of the city’s urban area was obstructed by the Hunhe River due to a lack of technology. Thanks to the scientific and technological development over the later years, especially after the establishment of the Hunnan New Area in 2001, the city began to extend its urban area beyond the Hunhe River and concentrate efforts on construction of the Hunnan New Area under its primary strategy “Big Hunnan, New Shenyang”. As a result, the original spatial structure of urban Shenyang changed to a new one that was characterized by “one city with two urban areas”. In Nanjing, the Nanjing Yangtze River Bridge has guided the city’s urban area to grow towards the Jiangbei area (i.e. the area north of the Yangtze River) and economic and technological development have reduced the limitations to urban sprawl posed by rivers. 4. Conclusions This study investigated the urban expansion, spatial patterns, and the corresponding transformation mechanisms of 24 major cities in China through quantitative (calculation of the rate of urban expansion and growth rate of urban area) and qualitative analyses. Remote sensing and GIS were used to acquire information about urban sprawl of these cities. The following conclusions can be drawn from this study: (1) During 1984-1994, the expansion rates of China’s major cities were relatively slow and slightly varied between cities. During 1994-2004, the expansion rates of these cities varied significantly; Beijing exhibited the highest expansion rate, followed by Shanghai and Guangzhou. During 2004-2014, the expansion rates differed slightly among the cities excluding Chongqing and declined compared to the second period. The cities showed stable growth rates of urban area during 1984-1994, with a maximum of 93.7% in Shanghai. From 1994 to 2004, the growth rates of urban area soared and the cities expanded rapidly, resulting in problems such as shrinkage of farmland and wasteful land-use. During 2004-2014, the growth rate of urban area dropped compared to the last period but still remained high. (2) Based on geographical information of urban built-up areas and GIS overlay maps, the sprawl patterns of these cities were classified into four groups: circular, leapfrog, interactive, and belt-like patterns. (3) Natural setting was found to be the most essential factor that affected the urban sprawl and morphology of the cities. Traffic has guided the direction of urban sprawl and affected the formation of urban morphology. Technological advance and socio-economic development have helped removed the natural obstacles to urban expansion and played a critical role in altering urban morphology. City-industry integration and administrative divisions strengthened the links between industrial and development zones with urban areas and promoted the expansion of urban built-up areas, thus facilitating formation of new spatial patterns. Acknowledgements This study was funded by the Key Projects in the National Science & Technology Pillar Program during the 12th Five-year Plan Period (2015BAD06B02) and Key Projects of China Land Surveying and Planning Institute. References [1] C.E. Bai, Y. Qian, Infrastructure development in China: The cases of electricity, highways, and railways, Journal of Comparative Economics.38 (2010) 34-51. [2] Y.J. Qi, Y. Yang, F.J. Jin, China’s economic development stage and its spatio-temporal evolution: A prefectural-level analysis, Acta Geographica Sinica. 68 (2013) 517-531 (in Chinese) [3] M. Chen, W. Liu, X. Tao, Evolution and assessment on China’s urbanization 1960-2010: Under-urbanization or over-urbanization? Habitat Int. 38 (2013) 25-33 [4] J.Q. Zhang, C.W. Lou, New ideas on Chinese urban sprawl governance by contrasting Chinese and American urban sprawl, Resources Science. 36 (2014) 2131-2139 (in Chinese)
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