evaluating land-use change in rapidly urbanizing china: case study of shanghai
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Evaluating Land-Use Change in Rapidly Urbanizing China:Case Study of Shanghai
Ji Han1; Yoshitsugu Hayashi2; Xin Cao3; and Hidefumi Imura4
Abstract: Historical patterns and driving forces of land-use change were investigated in Shanghai under the background of drasticsocioeconomic transition in China. Differing from the previous researches, this paper highlights the investigation of not only the socio-economic factors driving urban area growth, but also the physical elements affecting urban land’s spatial distribution through remotesensing and multivariable regression methods. The results indicate that land-use changes have been occurring at an accelerating pace inShanghai over the past two decades, and are characterized by a massive increase of urban land and a loss of croplands. The growth inurban land use has primarily been driven by population, economy, and transportation, and its spatial distribution has mainly beeninfluenced by accessibility to the transport network and the city center, together with the constraints of existing land-use patterns. Theimplications for policy are that improvements are needed in the efficient use of resources and the layout of a more adequate transportnetwork; simple restrictions on the migration to cities are not a long-term solution. The conservation and exploitation of agricultural land,as well as the promotion of urban green spaces, are also crucial instruments for sustainable city development.
DOI: 10.1061/�ASCE�0733-9488�2009�135:4�166�
CE Database subject headings: Land usage; Social factors; Economic factors; Remote sensing; China; Urban development.
Introduction
Since the economic reforms of 1978, China has been experienc-ing a dramatic changeover from central planning to marketmechanism. Rapid socioeconomic development and urbanizationare leading to significant changes in land use, with associateddegradations in the environment and ecology. From 1978 to 2003,the number of cities increased from 190 to 660, and the propor-tion of urban population to China’s total grew from 18 to 39%�National Bureau of Statistics 2004�. As a negative result of this,large areas of high quality agricultural land have suffered en-croachment through urbanized land, which is likely to have animpact on the future food security of China and even to havecumulative effects on climate change. As China seems set to con-tinue its drastic course of socioeconomic transition, a thoroughstudy of the patterns and determinants of these changes in landuse is necessary, in order to be able to grasp the socioeconomic
1Japan Society for the Promotion of Science �JSPS� Research Fellow,Graduate School of Environmental Studies, Nagoya Univ., Furo-cho,Chikusa-ku, Nagoya 464-8603, Japan �corresponding author�. E-mail:[email protected]
2Professor, Graduate School of Environmental Studies, Nagoya Univ.,Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. E-mail: [email protected]
3Ph.D. Student, Graduate School of Engineering, Nagoya Univ.,Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. E-mail: [email protected]
4Professor, Graduate School of Environmental Studies, Nagoya Univ.,Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. E-mail: [email protected]
Note. This manuscript was submitted on January 30, 2008; approvedon June 2, 2009; published online on November 13, 2009. Discussionperiod open until May 1, 2010; separate discussions must be submittedfor individual papers. This paper is part of the Journal of Urban Plan-ning and Development, Vol. 135, No. 4, December 1, 2009. ©ASCE,
ISSN 0733-9488/2009/4-166–171/$25.00.166 / JOURNAL OF URBAN PLANNING AND DEVELOPMENT © ASCE / DE
J. Urban Plann. Dev. 20
influences at work and to offer policy makers useful informationas to the best directions for future sustainable development.
In connection with land-use change issue, many studies havebeen conducted in both developed and developing countries byapplying Geographical Information Systems �GIS� and remotesensing techniques to examine the relationships among spatialand temporal patterns, driving forces and environmental influ-ences, etc. Recent examples include Ryznar and Wagner �2001�,who used remotely sensed images to detect the net vegetationchange in Detroit’s metropolitan area. Li et al. �2003� examinedthe scale, intensity, and spatial heterogeneity of urban growth inthe Shanghai region by combining the urbanization index withGIS methods. Leao et al. �2004� used cellular automata �CA�-based model to simulate the urban growth in Brazil’s Porto Alegrecity, and tested the results of different development strategies.Wilson and Lindsey �2005� investigated the land-use dynamics ofthe central region of Indiana through classification and changedetection analysis of Landsat satellite imageries. They found asignificant correlation between land-use change and some socio-economic processes such as population change and financial in-vestment in the built environment. Xiao et al. �2006� analyzedurban expansion in Shijiazhuang City using GIS and a remotesensing method, and discussed the relationship between urbanland increase and several socioeconomic factors independentlythrough unitary linear regressions. Al Rawashdeh and Saleh�2006� adopted remote sensing and GIS techniques to monitor theurban spatial growth of Amman area of Jordan and discussed thepossible environmental impacts caused by the continuing fertileland loss. Shi and Li �2007� discussed the influences of land-usepolicy on urbanization such as the upsurge of real estate price,suburbanization, and multicenter urban development mode, etc.Xi and Cho �2007� integrated temporal remote sensing data witha gradient analysis to investigate the spatial and temporal dynam-ics of urban sprawl along the urban-rural transect of GuangzhouCity. These researches provide useful tools and insights for in-
creasing our understanding of land-use change issue. However,CEMBER 2009
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when touching the mechanism of urban land-use change, most ofthe works either rely on theoretical abstraction and qualitativediscussion �e.g., Shi and Li 2007�, or just use unitary linear re-gression to examine the correlation of urban land growth witheach driving factor separately �e.g., Wilson and Lindsey 2005;Xiao et al. 2006�. Those comprehensive and quantitative investi-gations of the socioeconomic factors driving urban area growthand the physical elements affecting urban land’s spatial distribu-tion are generally seldom reported.
Given this background, Shanghai has been selected for thiscase study because it is one of the most densely populated andeconomically fastest growing cities in the world, with a sustainedannual gross domestic product �GDP� growth rate of 10% in thelast decade and a population of 18 million in 2005 �NationalBureau of Statistics 2006�. Moreover, since the 1990s, and espe-cially after the opening-up of the Pudong district, Shanghai hasbeen one of the most intensively urbanized areas in China, whichmakes it a good place for studying land-use change in the processof rapid urbanization. As shown in Fig. 1, the area being studies islocated on the coast of the East Sea and at the estuary of theYangtze River between latitudes 30°40�–31°55�N and longi-tudes 120°50�–121°55�E, giving an area of around 6340 km2.
Data and Methodology
The key issues to be analyzed in this study and the correspondingresearch methods are illustrated by the flowchart in Fig. 2. First,the temporal and spatial characteristics of land-use change in thepast two decades are investigated. Second, the driving forces ofurban area growth and spatial distribution are examined.
Data
Table 1 presents all the analysis data used, including socioeco-
Fig. 1. Study area and location
nomic statistical data since 1985, three Landsat remote sensing
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J. Urban Plann. Dev. 20
images for 1979, 1989, and 2000, Digital Elevation Model�DEM� data and road network maps for around 1990 and 2000,etc., collected from various sources.
Methods
First, employing the widely used unsupervised classificationmethod and ERDAS IMAGINE software, we geometrically inter-match the three remote sensing images, and classify the land usesinto six types of water, crop, urban, forest, grass, and barren.Through a visual inspection method, we calculate the overall ac-curacy of this classification as 84.7% for 1979, 85.1% for 1989,and 87.2% for 2000, which is good enough to meet the minimumstandard of 85% proposed by the United States Geological Surveyfor the identification of land use from remote sensing data�Anderson et al. 1976�.
Second, we use two multivariable stepwise regression modelsto investigate the determinants of two aspects of urban land ex-pansion: �1� urban area growth driven by socioeconomic factors,and �2� spatial distribution of urban land affected by physicalelements.1. The urban area growth �UA� is closely correlated with eco-
nomic and infrastructure development, demographic pro-cesses and industry structure, etc. Derived from city-widestatistics and through a stepwise estimation which managesto avoid multicollinearity in selecting the most significantvariables, independent factors selected to explain UA arepopulation �P�, GDP, tertiary industry as a share in Shang-hai’s GDP �S�, urban infrastructure investment �INVT�, For-eign Direct Investment �FDI� and road freight traffic �RFT�.C is a constant
ln UAt = a1 ln Pt + a2 ln GDPt + a3 ln St + a4 ln INVTt
+ a5 ln FDIt + a6 ln RFTt + C �1�
2. The spatial distribution of urban land development is ex-pected to be driven by various physical elements such ashistorical land-use patterns, elevation, slope, and accessibil-ity to traffic routes, etc. Following the theory of cellular au-tomata models in urban growth simulation, the transitionprobability of a nonurban land cell passing into urban use�TP� depends on the land suitability and the neighborhoodeffect �White et al. 1997; Xian and Crane 2005�. By overlay-ing the land-use maps for 1979, 1989, and 2000, we use a
Urban area growth
Socio-economic driving forces� Population� GDP� Tertiary industry development� Infrastructure investment� Foreign Direct Investment� Transportation, etc.
Economic reform and socio-economic development
Rapid urbanization
Land use change pattern
Physical determinants� Historical land use patterns� Neighborhood effect� Elevation, slope� Accessibility to traffic routes, etc.
200019891979
Landsat data
Imageclassification
Land usechangedetection
Remote sensing and GIS methods
Multivariable stepwise regression method
Characteristics of urban area change (1985-2003)Economic and political background
Multivariable stepwise regression method
Fig. 2. Flowchart of this study
10�10 pixel gliding window to extract all the cells that
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have been converted from nonurban to urban land use duringthe periods 1978–1989 and 1989–2000, and take the propor-tion of converted cells within each gliding window as thevalue for TP. It is assumed to be affected by elevation�ELEV�, slope �SLOP�, distances from the converted cell tothe nearest roads, airports, harbors, city center, subcenters�Droad ,Dairport ,Dharbor ,Dcitycenter ,Dsubcenter�, and the neighbor-hood effect �N�
ln TP = b1 ln ELEV + b2 ln SLOP + b3 ln Droad
+ b4 ln Dairport + b5 ln Dharbor + b6 ln Dcitycenter
+ b7 ln Dsubcenter + b8 ln N + C �2�
In Eq. �2�, N is used to represent the urban agglomerativeeffect. The agglomeration of urban land reflects benefits of con-venience in exchanges of materials, information and money, andcost saving in the construction of infrastructure. Theoretically, alarger value of N indicates a denser clustering of the urban land�Sui and Zeng 2001�. N is defined by
N = �i=1
kAi
di�3�
where Ai=area of cell i for urban use within a 10�10 pixelgliding window; di=distance from cell i to city center of Shang-hai; and k=number of total urban land cells.
Table 1. Materials and Data Used in This Study
Data type Year
Landsat MSS image 1979/08/04
Landsat TM image 1989/08/11
Landsat ETM image 2000/06/14
DEM data /
Socioeconomic statistical data 1985–2003
Shanghai master plan 1999–2020 2001
Shanghai city layout records 1998
Road network map of Shanghai 1990, 2000
Fig. 3. Land-use maps of S
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J. Urban Plann. Dev. 20
Results
Land-Use Changes in 1979, 1989, and 2000
Fig. 3 shows the land-use maps of the Shanghai in 1979, 1989,and 2000 obtained by classified remote sensing images. In 1979,crops occupied the largest proportion of land �91.2%�, followedby water �3.4%� and urban �2.1%�. In 1989, these shares were90.2, 4.0, and 4.0%, respectively, and in 2000 they were 83.0, 3.0,and 12.9%. Spatially, the urban land mainly expanded along thesouth-north and east-west axes, and has gradually transformeditself from a “single-core” pattern �urban sprawl mainly aroundthe city center� into a “multicores” pattern �urban land expansionaround the outskirts of the city center, around subcenters andalong the major roads�.
Table 2 presents the quantified conversion relationships amongthe six types of land use in the Shanghai for 1979–1989 and1989–2000. It can be seen that there are significant changes inland use, with urban land greatly expanding while croplands de-creasing dramatically. Between 1979 and 1989, about 122 km2 ofcropland was converted to urban use, but between 1989 and 2000,this increased nearly five times to 566 km2. To correct the con-tradiction between urban sprawl and the need for cropland pro-tection, the conversion of water areas to reclaimed land foragricultural use has been a priority measure in Shanghai. Duringthe period 1979–1989, 101 km2 of water was converted to crop-land, and this rose to 135 km2 in 1989–2000. At the same time, inorder to mitigate the negative effects of city development on natu-
Description
tion 79�79 m
tion 28.5�28.5 m
tion 28.5�28.5 m
tion 90 m
ing urban land area, population, GDP, investment, freight volume etc.
ng for economy, urban and suburban areas, transportation, etc.
s of city layout from 1949 to the 1980s
road networks
i for 1979, 1989, and 2000
Resolu
Resolu
Resolu
Resolu
Includ
Planni
Record
Major
hangha
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ral resources, the environment and citizens’ quality of life, effortshave been made to increase the area of vegetation, by laying outwooded parks in suburban areas, planting trees along major roadsand increasing the green spaces in residential zones, etc. As aresult, the area of green space �including trees and grass� hasincreased significantly from 16 km2 in 1979 to 34 km2 in 1989,and 65 km2 in 2000.
Urban Area Growth and the SocioeconomicBackground in 1985–2003
In view of the insufficiency of remote sensing data for providingcontinuous information of land use and socioeconomic changeover a longer period, this discussion of the evolution of urbanarea growth and the socioeconomic background from 1985 to2003 will be based on statistical data �Fig. 4�. Overall, the in-crease of urban area in Shanghai went through a slow growth
Table 2. Land-Use Conversion Matrices in 1979–1989 and 1989–2000 �
Land type Water Crop Barren
19
Water 107.78 100.63 1.56
Crop 99.69 5,572.08 6.57
Barren 34.20 83.92 72.19
Urban 11.23 0.00 0.48
Forest 0.45 0.79 0.00
Grass 0.06 0.11 0.00
Total 253.40 5,757.52 80.80
19
Water 103.89 134.52 2.26
Crop 75.47 5,083.40 1.87
Barren 1.82 73.78 0.31
Urban 9.77 0.00 0.05
Forest 0.37 3.32 0.00
Grass 0.50 1.11 0.01
Total 191.82 5,296.12 4.49
Urban area
020040060080010001200
1985 1987 1989 1991 1993 1995 1997 1999 2001 200
Km2
0
2
4
6
8
1985 1988 1991 1994 1997 2000 2003
BillionUSD
Investment in urban infrastructureForeign direct investment
0
100
200
300
400
1985 1988 1
Milliontons
Ro
Fig. 4. Urban area growth and socioeconomic changes during 1985–2Bureau 2006�; Liang and Jin 2005; and Zhao et al. 2006.
JOURNAL OF URBAN
J. Urban Plann. Dev. 20
stage from 1985 to 1992, followed by medium growth in theperiod 1992–1997 and a rapid expansion stage after 1997.
In the slow stage �1985–1992�, city development just managedto recover from the influences of the political movements in theprereform era such as the Great Leap Forward, a movement ledby the central government from 1958 to implement communismthrough rapid production measures, and the Great Cultural Revo-lution, from 1966 to 1976, during which almost all economicactivities stopped. In this first stage, the urban land area grew atan annual rate of around 5%. There was stable socioeconomicprogress, with GDP growing at 7%, and population increasing at0.8%. The mean annual investment on urban infrastructure andFDI were $0.9 and $0.6 billion, respectively.
In the medium growth stage �1992–1997�, Pudong, an easterndistrict of Shanghai with a population of some 1.8 million and anarea of 522 km2 �Fig. 1�, was inaugurated as a New Economic
m2�
Urban Forest Grass Total
89
8.50 0.04 0.74 219.24
121.95 12.09 10.59 5,822.96
0.59 0.02 0.39 191.31
117.17 0.96 4.28 134.12
5.73 2.26 0.36 9.58
3.23 0.51 2.19 6.11
257.16 15.89 18.55 6,383.32
00
11.21 0.80 0.73 253.42
566.11 14.82 15.85 5,757.52
3.65 0.04 1.20 80.80
240.37 1.73 5.25 257.16
3.47 8.38 0.34 15.89
1.31 1.23 14.39 18.55
826.13 27.01 37.77 6,383.34
0369121518
1985 1988 1991 1994 1997 2000 2003
Millionpeople
Population
94 1997 2000 2003
ght traffic
0153045607590
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
0
20
40
60
80
100%
GDP Share of tertiary industry in urban economy
ource: Shanghai Statistical Yearbook �Shanghai Municipal Statistical
Unit: k
79–19
89–20
3
991 19
ad frei
BillionUSD
003. S
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Development Zone enjoying still more favorable developmentpolicies than those for special economic zones �e.g., Shenzhencity�. Within the Shanghai area, Pudong has been taking the leadin reforming its appraisal and approval procedures for foreign-investment projects by out cutting unnecessary formalities, allow-ing enterprises to be registered directly with the relevantauthorities and guaranteeing a low-cost investment environmentunder fair conditions. An abundance of capital, labor, and techni-cal know-how has been attracted to Pudong, accelerating theurban expansion. Over this period, the urban area increased 11%per annum. GDP and FDI rose rapidly to reach $41 and $6 billion,which are nearly two and three times the respective figures for1992. As one index for the development of infrastructure andtransport, road freight traffic increased significantly by 15.6% perannum, which can be expected to influence urban sprawl posi-tively.
Since the 1990s, the Chinese government has reformed thehousehold registration system by introducing such important newmeasures as the issue of temporary residence certificates for ruralimmigrants seeking jobs in cities, and the opening up of urbanhousehold registration without quota controls and the like in des-ignated municipalities. These reforms significantly facilitated themobility of migrants to cities. More recently, with the consolida-tion of the economic reforms and boosted by the success ofShanghai’s 2002 bid to host the 2010 World Exposition, the pros-perity of the urban economy and the great concentration of peoplein the city have propelled urban land expansion into a rapidgrowth stage. From 1997 to 2003, the population of Shanghaiincreased from 13 to 17 million. GDP nearly doubled in thisperiod, reaching $80 billion in 2003. Tertiary industry came tocontribute over 50% of the city’s production. With this upturn ingrowth, the urban land area also expanded fast at 18% per annum.
Determinants of Urban Land Expansion
1. The socioeconomic determinants of urban area growth.Table 3 shows that the dominating factors behind it are popu-
lation, GDP, and transportation. Further important factors are thedevelopment of tertiary industries, increases in urban infrastruc-ture investment and FDI.2. The contributions of physical elements to the spatial distri-
bution of urban land.The major driving factors, as shown in Table 4, are the dis-
tance to roads and to the city center and the neighborhood effect.In general, the closer a piece of land is to roads or to the citycenter, the more likely it is to be converted for urban use. Overthe past two decades, the influence of the distance to the citycenter has been decreasing, while the accessibility of roads hasbeen advancing to the primary factor, which suggests that therational layout of a transport network could be an important in-strument for the control of urban sprawl around subcenters whilealso helping to alleviate the crowding in of the city center. Theneighborhood effect is likely to represent the positive influence of
Table 3. Socioeconomic Determinants of Urban Area Growth in 1985–2
P GDP S INVT
Coefficient 4.02 0.24 0.12 0.10
t value 33.78b 5.82b 2.66a 6.87b
aSignificance: 5%.bSignificance: 1%.
the existing urban land-use patterns on the future changes in use
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J. Urban Plann. Dev. 20
of adjoining land areas. While other factors such as slope, eleva-tion, distance to airports, subcenters and harbors also have influ-ences on urban land distribution, they are less important thanDroad, Dcitycenter, and N.
Conclusion and Discussion
This paper has looked at land-use change in Shanghai during thepast two decades and highlighted a comprehensive analysis of thedriving forces behind urban land expansion, especially viewedagainst the current drastic socioeconomic transition in China. Incontrast with the previous literatures, the socioeconomic factorslike population, GDP, and transportation development that driveurban area growth, together with the physical determinants suchas the accessibility to transport network and city center that affecturban land spatial distribution were explicitly detected in thisstudy. Moreover, it is found that the very large population growthin Shanghai and the rapid development of the economy and oftransportation have led to accelerated changes in land use, mostobviously a large-scale expansion of urban land and an encroach-ment of urban land upon cropland. This acceleration does notappear to be coming to an end or even slowing down, which is byno means a situation special to Shanghai but a phenomenon ap-parent in the mega cities of other developing countries such asIndia and Thailand, etc. Consequently, it poses a threat to citi-zens’ quality of life, the local environment, the global climate andeven the whole country’s future prospects of sustainability. De-spite some successes in its attempts to control large-scale urbanexpansion and to conserve natural resources, China will soon finditself under much greater pressure to cut back the negative sideeffects of existing land-use change.
With further growth in the economy, more employment oppor-tunities are generally created, and these attract large inflows of
FDI RFT C R2 F value
0.08 0.18 �26.94 0.99 3,507.5b
3.62b 2.76a �35.55b
Table 4. Physical Elements Affecting Urban Land Distribution in 1979–1989 and 1989–2000
1979–1989 1989–2000
Coefficient t value Coefficient t value
ELEV �0.019 �2.10a
SLOP �0.167 �12.96b �0.049 �5.77b
Droad �0.284 �47.88b �0.287 �101.75b
Dairport �0.066 �6.76b �0.0191 �3.98b
Dharbor �0.159 �13.82b �0.024 �3.88b
Dcitycenter �0.363 �23.72b �0.177 �21.10b
Dsubcenter �0.177 �19.88b �0.016 �3.20b
N 0.292 85.18b 0.273 142.63b
C 4.725 64.10b 4.093 106.58b
R2 0.69 0.72
F value 3,586.73b 14,926.66b
aSignificance: 5%.b
003
Significance: 1%.
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migrants into cities from other provinces and from rural areas. Toslow down the consequent large-scale urban sprawl, appropriatepolicies should be applied not to the restriction of migration but toa greater efficiency in resource utilization and to the layout of atransport network that can guide urban land expansion in an or-dered and intensive way. Other implications for policy setting arethe needs to incorporate such measures as the conservation andexploitation of agricultural land, and the creation of green spacesetc. into urban planning. These measures will be crucial for thecompensation of cropland losses and also as a means of mitigat-ing the degradation of the environment and the ecology.
The United Nations estimates that in the decades ahead, mostof the global population growth and drastic urbanization will takeplace in cities of the developing countries �United Nations 2007�.However, the unprecedented pace of urbanization and unpreparedresponse to the generated social and environmental problemsmake them great challenges for the future sustainability. Applica-tion of various technologies and research methods to a largernumber of case studies in developing nations is required ratherthan a simple copy of the experience from developed countries.The case study of Shanghai for examining the patterns and driv-ing forces of urban land expansion has the potential of offeringpolicy makers useful information to plan their cities in a sustain-able way. The methods adopted and implications found in thisstudy can also be applied in other mega cities of developing re-gions.
Acknowledgments
This research was partially supported by a Grant-in-Aid for JSPSFellows �Grant No. 19·07397�. The writers express their greatappreciation to the anonymous referees for their valuable sugges-tions. We would also like to thank Professor David Dykes forrevision of the English.
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