Spatiotemporal dynamics of the urban sprawl in a typical urban agglomeration: a case study on Southern Jiangsu, China (1983–2007)

doi:10.1007/s11707-014-0423-1

Front. Earth Sci.

2014, Vol. 8

Issue (4) : 490-504 https://doi.org/10.1007/s11707-014-0423-1

RESEARCH ARTICLE

Spatiotemporal dynamics of the urban sprawl in a typical urban agglomeration: a case study on Southern Jiangsu, China (1983–2007)

Yongxue LIU¹(

), Jieli CHEN², Wangyu CHENG¹, Chao SUN¹, Saishuai ZHAO¹, Yingxia PU¹

¹. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China
². Changzhou Land and Resources Administration Wujin District Branch, Changzhou 213161, China

Download: PDF(3116 KB)
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

China has experienced urbanization at an unprecedented rate over the past decades. Against this background, this paper demonstrates the multi-level spatiotemporal urban sprawl process from 1983 to 2007 on the perspective of urban agglomeration with a case study in Southern Jiangsu. Based on a combination of eight rounds of satellite images from 1983 to 2007, the presented results suggest the following three main findings: (1) At the prefecture-city level, the urban sprawl in Southern Jiangsu has presented significantly divergent growth patterns, with more than half of this vast growth occurring in the Suzhou prefecture-level city. (2) At the county level, clear spatial differentiations exist in the direction of the urban sprawl. The centroids of all county seats in the Suzhou and Wuxi prefecture-level cities have an eastward tendency (Shanghai oriented), while those of the county seats in the Changzhou prefecture-level city tend to be westward (Nanjing oriented). (3) At the township level, two convergent groups have gradually formed over time; namely, the low density urban zone in the western hilly land and the high density urban zone around the three central downtown areas. The urban areas close to urban cores tend to merge, showing a high-density convergent growth pattern, as do the western and southwestern townships in Southern Jiangsu, showing a low-density convergent growth pattern. All of these findings may be valuable for researchers and local authorities in providing reference for regional coordinated growth, environmental management, and urban planning decision-making.

Keywords Southern Jiangsu urban sprawl spatiotemporal dynamics rapid urbanization areas

Corresponding Author(s): Yongxue LIU

Online First Date: 16 April 2014 Issue Date: 13 January 2015

Cite this article:

Yongxue LIU,Jieli CHEN,Wangyu CHENG, et al. Spatiotemporal dynamics of the urban sprawl in a typical urban agglomeration: a case study on Southern Jiangsu, China (1983–2007)[J]. Front. Earth Sci., 2014, 8(4): 490-504.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-014-0423-1
https://academic.hep.com.cn/fesci/EN/Y2014/V8/I4/490

1	G Anderson, Y Ge (2005). The size distribution of Chinese cities. Reg Sci Urban Econ, 35(6): 756–776 https://doi.org/10.1016/j.regsciurbeco.2005.01.003
2	L Anselin (1995). Local indicators of spatial association- LISA. Geogr Anal, 27(2): 93–115 https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
3	P Apparicio, M Polese, R Shearmur (2009). A history of residue: regarding general and local factors of regional growth in Canada, 1971–2001. Can Geogr, 53(4): 385–403
4	H Bagan, Y Yamagata (2012). Landsat analysis of urban growth: how Tokyo became the world’s largest megacity during the last 40 years. Remote Sens Environ, 127: 210–222 https://doi.org/10.1016/j.rse.2012.09.011
5	B Bhatta, S Saraswati, D Bandyopadhyay (2010a). Quantifying the degree-of-freedom, degree-of-sprawl, and degree-of-goodness of urban growth from remote sensing data. Appl Geogr, 30(1): 96– 111 https://doi.org/10.1016/j.apgeog.2009.08.001
6	B Bhatta, S Saraswati, D Bandyopadhyay (2010b). Urban sprawl measurement from remote sensing data. Appl Geogr, 30(4): 731–740 https://doi.org/10.1016/j.apgeog.2010.02.002
7	D Black, V Henderson (2003). Urban evolution in the USA. J Econ Geogr, 3(4): 343–372 https://doi.org/10.1093/jeg/lbg017
8	M G Boarnet, R B McLaughlin, J I Carruthers (2011). Does state growth management change the pattern of urban growth? Evidence from Florida. Reg Sci Urban Econ, 41(3): 236–252 https://doi.org/10.1016/j.regsciurbeco.2010.12.004
9	M Bosker, S Brakman, H Garretsen, M Schramm (2008). A century of shocks: the evolution of the German city size distribution 1925–1999. Reg Sci Urban Econ, 38(4): 330–347 https://doi.org/10.1016/j.regsciurbeco.2008.04.002
10	B Catalan, D Sauri, P Serra (2008). Urban sprawl in the Mediterranean? Patterns of growth and change in the Barcelona Metropolitan Region 1993–2000. Landsc Urban Plan, 85(3–4): 174–184 https://doi.org/10.1016/j.landurbplan.2007.11.004
11	J Chen (2007). Rapid urbanization in China: a real challenge to soil protection and food security. Catena, 69(1): 1–15 https://doi.org/10.1016/j.catena.2006.04.019
12	F L Fan, Y P Wang, M H Qiu, Z S Wang (2009). Evaluating the temporal and spatial urban expansion patterns of Guangzhou from 1979 to 2003 by remote sensing and GIS methods. Int J Geogr Inf Sci, 23(11): 1371–1388 https://doi.org/10.1080/13658810802443432
13	C F Gong, J Q Chen, S X Yu (2011). Spatiotemporal dynamics of urban forest conversion through model urbanization in Shenzhen, China. Int J Remote Sens, 32(24): 9071–9092 https://doi.org/10.1080/01431161.2010.549848
14	M Herold, N C Goldstein, K C Clarke (2003). The spatiotemporal form of urban growth: measurement, analysis and modeling. Remote Sens Environ, 86(3): 286–302 https://doi.org/10.1016/S0034-4257(03)00075-0
15	J G Huang, X X Lu, J M Sellers (2007). A global comparative analysis of urban form: applying spatial metrics and remote sensing. Landsc Urban Plan, 82(4): 184–197 https://doi.org/10.1016/j.landurbplan.2007.02.010
16	M K Jat, P K Garg, D Khare (2008). Monitoring and modelling of urban sprawl using remote sensing and GIS techniques. Int J Appl Earth Obs Geoinf, 10(1): 26–43 https://doi.org/10.1016/j.jag.2007.04.002
17	C Klaufus (2010). Watching the city grow: remittances and sprawl in intermediate Central American cities. Environ Urban, 22(1): 125–137 https://doi.org/10.1177/0956247809359646
18	F H Kong, H W Yin, N Nakagoshi, P James (2012). Simulating urban growth processes incorporating a potential model with spatial metrics. Ecol Indic, 20: 82–91 https://doi.org/10.1016/j.ecolind.2012.02.003
19	X H Li, T Lin, G Q Zhang, L S Xiao, Q J Zhao, S H Cui (2011). Dynamic analysis of urban spatial expansion and its determinants in Xiamen Island. J Geogr Sci, 21(3): 503–520 https://doi.org/10.1007/s11442-011-0860-7
20	E Lichtenberg, C G Ding (2008). Assessing farmland protection policy in China. Land Use Policy, 25(1): 59–68 https://doi.org/10.1016/j.landusepol.2006.01.005
21	G C S Lin (1999). State policy and spatial restructuring in post-reform China, 1978–95. Int J Urban Reg Res, 23(4): 670–696 https://doi.org/10.1111/1468-2427.00222
22	Y G Liu, G W Yin, L J C Ma (2012). Local state and administrative urbanization in post-reform China: a case study of Hebi City, Henan Province. Cities, 29(2): 107–117 https://doi.org/10.1016/j.cities.2011.08.003
23	J Luo, Y H D Wei (2009). Modeling spatial variations of urban growth patterns in Chinese cities: the case of Nanjing. Landsc Urban Plan, 91(2): 51–64 https://doi.org/10.1016/j.landurbplan.2008.11.010
24	R H Ma, C L Gu, Y X Pu, X D Ma (2008). Mining the urban sprawl pattern: a case study on Sunan, China. Sensors (Basel Switzerland), 8(10): 6371–6395 https://doi.org/10.3390/s8106371
25	J G Masek, F E Lindsay, S N Goward (2000). Dynamics of urban growth in the Washington DC metropolitan area, 1973–1996, from Landsat observations. Int J Remote Sens, 21(18): 3473–3486 https://doi.org/10.1080/014311600750037507
26	R B Miller, C Small (2003). Cities from space: potential applications of remote sensing in urban environmental research and policy. Environ Sci Policy, 6(2): 129–137 https://doi.org/10.1016/S1462-9011(03)00002-9
27	P A P Moran (1948). The interpretation of statistical maps. J R Stat Soc Series B Stat Methodol, 10(2): 243–251
28	T J Nechyba, R P Walsh (2004). Urban sprawl. J Econ Perspect, 18(4): 177–200 https://doi.org/10.1257/0895330042632681
29	H G Overman, Y M Ioannides (2001). Cross-sectional evolution of the US city size distribution. J Urban Econ, 49(3): 543–566 https://doi.org/10.1006/juec.2000.2204
30	X P Shen, L J C Ma (2005). Privatization of rural industry and de facto urbanization from below in Southern Jiangsu, China. Geoforum, 36(6): 761–777 https://doi.org/10.1016/j.geoforum.2005.01.005
31	Y Q Shi, X Sun, X D Zhu, Y F Li, L Y Mei (2012). Characterizing growth types and analyzing growth density distribution in response to urban growth patterns in peri-urban areas of Lianyungang City. Landsc Urban Plan, 105(4): 425–433 https://doi.org/10.1016/j.landurbplan.2012.01.017
32	V F S Sit, C Yang (1997). Foreign-investment-induced exo-urbanisation in the Pearl River Delta, China. Urban Stud, 34(4): 647–677 https://doi.org/10.1080/0042098975961
33	M H Tan, X B Li, C H Lu (2005). Urban land expansion and arable land loss of the major cities in China in the 1990s. Sci China Ser D, 48(9): 1492–1500 https://doi.org/10.1360/03yd0374
34	H Taubenböck, T Esch, A Felbier, M Wiesner, A Roth, S Dech (2012). Monitoring urbanization in mega cities from space. Remote Sens Environ, 117: 162–176 https://doi.org/10.1016/j.rse.2011.09.015
35	C H Teh, R T Chin (1988). Onimage-analysisby the methods of moments. IEEE Trans Pattern Anal Mach Intell, 10(4): 496–513 https://doi.org/10.1109/34.3913
36	K C Wang, J K Wang, P C Wang, M Sparrow, J Yang, H B Chen (2007). Influences of urbanization on surface characteristics as derived from the Moderate-Resolution Imaging Spectroradiometer: a case study for the Beijing metropolitan area. J Geophys Res, D, Atmospheres, 112(D22), doi: 10.1029/2006jd007997
37	Y H D Wei (2002). Beyond the Sunan model: trajectory and underlying factors of development in Kunshan, China. Environ Plan A, 34(10): 1725–1747 https://doi.org/10.1068/a3567
38	Y H D Wei (2010). Beyond new regionalism, beyond global production networks: remaking the Sunan model, China. Environ Plann C Gov Policy, 28(1): 72–96 https://doi.org/10.1068/c0934r
39	Q H Weng (2012). Remote sensing of impervious surfaces in the urban areas: requirements, methods, and trends. Remote Sens Environ, 117: 34–49 https://doi.org/10.1016/j.rse.2011.02.030
40	J P Wu (2008). The peri-urbanisation of Shanghai: planning, growth pattern and sustainable development. Asia Pac Viewp, 49(2): 244–253 https://doi.org/10.1111/j.1467-8373.2008.00373.x
41	X J Yu, C N Ng (2007). Spatial and temporal dynamics of urban sprawl along two urban-rural transects: a case study of Guangzhou, China. Landsc Urban Plan, 79(1): 96–109 https://doi.org/10.1016/j.landurbplan.2006.03.008
42	Y Zhou, Y H D Wei (2011). Globalization, innovation, and regional development in China. Environ Plan A, 43(4): 781–785 https://doi.org/10.1068/a4418

[1]	Erfu DAI, Zhuo WU, Xiaodian DU. A gradient analysis on urban sprawl and urban landscape pattern between 1985 and 2000 in the Pearl River Delta, China[J]. Front. Earth Sci., 2018, 12(4): 791-807.

Viewed

Full text

Abstract

Cited

Shared

Discussed