Journal_Evolving Core-periphery Interactions in a Rapidly Expanding Urban Landscape

8/11/2019 Journal_Evolving Core-periphery Interactions in a Rapidly Expanding Urban Landscape

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Landscape Ecology 19: 375388, 2004.

2004Kluwer Academic Publishers. Printed in the Netherlands. 375

Evolving core-periphery interactions in a rapidly expanding urbanlandscape: The case of Beijing

Ye Qi1,

, Mark Henderson2

, Ming Xu3

, Jin Chen1

, Peijun Shi1

, Chunyang He1

& G. Wil-liam Skinner41College of Resources and Environment, Beijing Normal University, Beijing, 100875, China; 2Department of

Environmental Science, Policy and Management, University of California, Berkeley, CA 94720, USA;3Department

of Ecology, Evolution and Natural Resources Center for Remote Sensing and Spatial Analysis, Rutgers University,

New Brunswick, NJ 08901-8551; 4Department of Anthropology, University of California, Davis, CA 95616, USA;(Corresponding author: [email protected])

Received 16 April 2002; accepted in revised form 17 April 2003

Key words: Beijing, core-periphery, hierarchical regional space, landscape dynamics, urbanization, land use change

model

Abstract

We characterized and analyzed the dynamics of a rapidly expanding urban landscape of Beijing Municipality,

based on the Hierarchical Regional Space (HRS) model. We focused on ecological processes such as flows of

energy, materials and population between the urban core and its periphery, and how these processes co-evolved

with urbanization. We treated the HRS as an alternative to the cellular automata (CA) approach to characterizing

and modeling of landscape dynamics. With LANDSAT data, we showed that the urban area of Beijing expanded

from 269 km2 to 901 km2 in the period from 1975 to 1997, an increase of 2.35 times in 22 years. Meanwhile,

a number of secondary urban centers formed on areas that used to be sparsely populated around the city. These

secondary centers quickly expanded and ultimately merged with each other and with the urban core. The changes in

spatial pattern and organization were accompanied by evolution of urban functions and particularly the interactions

between the urban core and its periphery. We demonstrated a dramatic increase in dependence of the urban core onthe periphery as well as the cores influence on the periphery with a case analysis of the vegetable supply to Beijing.

The tightening link between the city and its periphery reinforces the urbanization process and further drives the

transformation of the regions landscape. We conclude that the HRS model is capable of characterizing the patterns

and processes of complex and dynamic landscapes such as the case of Beijing, and this model has great potential

for quantitative modeling of human dominated landscapes as well.

Introduction

Urbanization, a traditional research subject in geo-

graphy and regional economics, has received increas-

ing interest from ecologists who treat the process as

transformation of landscape patterns and functions or

as change in land use and land cover (Huang 1998;

Bessey 2002). Despite the long history of the study

of pattern and process of land use in geography, the

resurged interest in land use and land cover change in

the last decade was due primarily to its implications to

global and regional climate change (IPCC 2001). Land

use and land cover changes contribute, on average,

more than 20% to the buildup of CO2 concentration in

the atmosphere (Houghton 1999), and they affect the

regional energy and water balance through the change

of the albedo and land surface processes. As a major

component of the global and regional environmental

change, land use and land cover changes have a pro-

found effect on the regional and global biodiversity

(Chapin et al. 2000).

Two major types of landscape transformation can

be identified at regional level. The first is the con-

version of natural vegetation to agricultural land, e.g.,


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the agricultural development in the Amazon basin in

Brazil (Skole and Tucker 1994). The second is ex-

pansion of urban landscape, which can be found all

over the world, particularly along the coastlines of the

continents, and around the existing metropolitan areas.

Although urbanization is less extensive in area as com-

pared to agricultural development, it has intensiveimpacts on the environment and ecosystem functions.

It affects more human lives through its effects on the

economy and society.

Recent efforts in modeling land use and land cover

changes have been dominated by the cellular automata

(CA) approach (e.g., Qi 1994; Wegener 1994; Qi et al.

1996; Landis and Zhang 1999; Jenerette and Wu 2001,

Luck et al. 2001). In the CA approach, a landscape

is divided into a number of grid cells. Each grid cell

has a finite number of states, representing the types of

land use and land cover. The change of the landscape

is treated as the overall consequence of the conversion

of the individual cells. At any point of time, each cell

has a probability of being converted to another type

of land use or land cover. The probability is a func-

tion of a number of factors such as the topography,

proximity to urban centers, proximity to transporta-

tion network, and population density. Normally, the

probability of one cell is assumed to be independent

of the probability of the neighboring cells. The prob-

ability values can be derived either from a set of rules

or based on some statistical procedures. Examples of

the former are found in Turner (1993); Qi (1994); Qi

et al. (1996); Landis and Zhang (1999); Luck et al.

2001, and the latter, the statistics-based approach, wasused in Pontius and Hall (1993); Clark et al. (1998).

The CA approach is based on a reductionist view

which assumes the whole is the sum of all consist-

ing parts, and it focuses on dealing with individual

cells. This approach often neglects the links among

the cells and the overall patterns at greater spatial

scales. The CA approach has proven to be effective

when the spatial heterogeneity dominates the pattern,

thus each location can be characterized by a unique

vector of factors. Interactions among locations are

given little or no consideration in such an approach.

Despite many sussessful case in simulations in some

cases, e.g., for mountainous regions in Southeast Asia

(Qi et al. 1996), the CA approach is likely to fail in

areas with flat terrain as a dominating feature of the

topography such as Americas Midwest and Eastern

China. In our study of landscape transformation of the

Beijing and its surrounding area, we attempted to ex-

plore a holistic approach that focuses on the overall

patterns of the landscape and on the spatial relation-

ships among the landscape components of same or

different levels in spatial scale. We did so because the

flat terrain of the region makes hard to characterize

and explain the formation and change of the urban

landscape based on the differences among locations as

in the CA approach.We have observed in Beijing that more than 96%

of the urban expansion occurred on land with slope

less than 5 deg and elevation less than 100 m in the

study period from 1975 to 1997. In spite of the lack of

spatial heterogeneity in topography, the urbanization

is anisotropic: the northward urban expansion was sev-

eral times greater than the southward. This can hardly

be explained by the differences in the local properties

of the two directions. Thus, the CA approach which

focuses on the local differences is inadequate. It is

necessary to introduce alternative approaches that con-

sider the global properties and the interrelationships

and interactions among the localities.

We use the hierarchical regional space (HRS)

model developed by Skinner and associates (Skinner

1977, 1994; Skinner et al. 2000). HRS treats a region

as a whole in which interacting regional components

and elements are arranged in a hierarchical structure

with each component further divisible into lower level

in organization. Human settlement centers serves as

the nodes of the hierarchy. This model recognizes

first the macroscale connections among the spatial ele-

ments. It helps to characterize the large-scale patterns.

This model was developed in study of the geographical

structure of human settlement centers and economicactivities (see also Woldenberg 1971; Wilson 1977),

but it coincides with many of the recent development

in theoretical and landscape ecology (e.g., Wu and

Locks 1995; Ahl and Allen 1996; Wu and David

2002).

The expansion of Beijing has resulted in much

greater dependence and influence of the city on its

peripheral areas. Vegetable supply is a good example.

The city used to be self-sufficient in vegetable supply

prior to 1980s, but now more than half of the sup-

ply depends on the supply from Hebei, Shandong and

other nearby provinces.

In the HRS model, the intensively constructed

urban area is recognized as the urban core, and the

surrounding areas are treated as the cores periphery.

Thus urban core is much larger in space than the tradi-

tional central business district (CBD). The boundaries

of the periphery is broadly defined by the limit which

the core influences can reach. We realize that defin-


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ition is subject to debate, but it does not affect our

analysis in this study.

The rapid urbanization has occurred with, and as

a result of, the over-intensified interactions between

the urban core and its peripheral areas. On the one

hand, the city core acts like a socioeconomic mag-

net which absorbs the human and natural resourcesfrom the periphery, forming a constant and significant

fluxes of material, energy and population between the

core and its periphery; on the other hand, the urban

cores influences radiate onto the peripheral areas and

are agents for transformation in landscape patterns and

functions in those areas. These dynamic interactions

between the core and periphery are key to understand-

ing and predicting the changes of urban landscapes. In

this study, we characterize these changes of the urban

landscape of Beijing for the period of a quarter cen-

tury through applying the Hierarchical Regional Space

(HRS) model and landscape ecology theories, based

on the Landsat data and GIS. We will show that HRS is

a useful alternative to the CA model for characterizing

and modeling complex, dynamics landscapes and their

changes.

Data and method

The site of study

Beijing, the capital city of China, forms the core of

one of the largest metropolitan regions in the country

(Figure 1). The municipality is located at 39

56

N and11620 E, covers an area of 16,808 km2. Of which

two third are mountainous areas encircling the west-

ern, northern and eastern sides of the city. The center

is 43.71 m above sea level and the main rivers include

Yongding, Chaobai and north canal. Beijing lies in the

temperate zone. Within 50 km north and west of the

city, the Taihang and Jundu mountains, straddled by

the famed Great Wall, rise to heights of 2,300 m.

Beijings history as a capital city dates as far back

as Chinas Warring States period (484-221 B.C.); most

significantly, it was the center of the Mongols east

Asian empire at the time of Marco Polo (c. 1285)

and was the capital of the Ming and Qing dynasties(13681643 and 16441911). At the establishment

of the Peoples Republic of China in 1949, the city

was again made the national capital. Beijing has seen

more constant expansion over the past five decades

than any other Chinese city. By 1975, the city has

a population of 9 millions. Since then, the city has

experienced rapid economic boom and urbanization.

The Qing city walls were replaced with ring roads,

multistory housing blocks rose over the alleys of the

old city, and surrounding villages became suburbs in a

conurbation with some 6.5 million residents by 2000.

Beijing municipality, encompassing eight districts and

ten counties as well as the central city area, reportsa population of 14 million. Since the beginning of

economic reforms in 1978, development of the sur-

rounding countryside has been especially brisk. The

plains east and south of the city are now a check-

erboard of high-intensity agricultural lands and new

urban areas, while nearby mountainous areas, though

targets of reforestation since the 1960s, also show the

effects of economic expansion.

Data

We used Landsat data to detect the change in spatial

patterns of the land use and land cover from 1975 to1997. The coverage of our landsat data includes 11 of

a total of 18 districts or counties of which the Beijing

Municipality consists. The 11 districts or counties

contain the urban core of Beijing and part of peri-

pheral counties. The covered area (enclosed within

39355240220 N and 11550051165909

and about 4500 km2) has experienced the most dra-

matic urbanization in the period of study. Seven

counties that are left out of the study all distribute in

the outskirt of the municipality. The four periods of

Landsat data are all taken for path 123 and row 32.

Except the first period (May 6, 1975) for which MSS

data was used with a spatial resolution of 180180 m,

TM data are used for other periods (October 2, 1984,

May 6 1991 and May 16, 1997) and the spatial res-

olution is 30 30 m. The four scenes were selected

based on their data quality, cloud cover, and time of

the year. All data were processed at the Institute of

Resource Science of Beijing Normal University. Shi

et al. (2001) provided details on data processing.

Land use and land cover classification were based

on the system used by Anderson (1976). The seven

types that are distinguished on the images include:

intensive urban area, extensive urban area, water

(including fish ponds), farmland, orchards, shrubs,and forest. Kappa statistics for classification are 0.71

(1975), 0.76 (1984), 0.80 (1991) and 0.82 (1997).

The hierarchical regional space model

HRS draws on some of the fundamental elements of

modern geographical thought, including regional sys-


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Figure 1. The area of study, with surrounding urban centers. The urban core is indicated as central city and the surrounding districts. Different

levels of urban centers are also laid out.


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tems theory (in the tradition of von Thnen), central

place theory (following Christaller 1933), and dif-

fusion theory (as introduced by Hgerstrand 1965).

Foreshadowing regional systems theory, von Thnen

(1966 [1826]) described how zones of high- to low-

value economic activity fill the regions around cities.

Seen as core-periphery structures, von Thnens zonescan be characterized in terms of agricultural intens-

ity and transport efficiency. Regional systems theory

subsequently conceptualized these regions as local or

regional, social and economic systems, centered at

urban nodes and nested in a more or less integrated

hierarchy. This led in 1925 to E. W. Burgesss con-

centric growth model that modeled city expansion in

terms of concentric circles of high- to low-value urban

activities.

In the 1930s and1940s geographerWalter Christaller

and economist August Lsch put forth versions of

central place theory that became fundamental texts of

urban geography. For agrarian societies, Christallers

(1933) central place theory predicts the emergence

of a hierarchy of settlements, with each level of the

hierarchy providing distinctive services and attain-

ing corresponding levels of development. Individuals

on the landscape orient their economic activities to

specific central places at each hierarchical level in

accordance with the services provided there: to a

nearby market town for items of daily use, to central

towns for cooking utensils, to cities for fashionable

clothes, and to metropolises for specialized services

such as higher education. It follows that the hierarch-

ical levels providing less common services require acorrespondingly wider hinterland, and that for reas-

ons of transportation efficiency the hinterlands at each

level become nested. Economic activities in this hier-

archy develop hand in hand with a web of social

networks, making a central place analysis a useful

starting point for an investigation of social patterns.

Anthropologist G. William Skinner first applied

a central place analysis to understanding the spa-

tial structure of rural Chinese society at the local

level, finding evidence for the traffic and market

variants of Christallers central place theory (Skin-

ner 196465, Crissman 1976, p.204). In subsequent

work, Skinner traced Chinas central place hierarchy

up to its highest levels, proposing that the agrarian

portion of China (excluding the pastoral regions of

Tibet and Inner Asia) could best be analyzed in terms

of nine macroregions (Skinner 1976). Each of these

macroregions makes up a more or less integrated eco-

nomic system within Chinas national economy, much

as the comparably populous nations of France, Ger-

many, and others function as more or less integrated

economic systems within Europes continental eco-

nomy. Skinners regionalization of China has been

highly influential in studies of Chinese history and

society (Lavely 1989; Cartier 2002) but has not been

widely appreciated in fields such as economics orecology, which have tended to rely on much more

simplistic spatial characterizations (such as bifurcat-

ing China into north and south or coastal and in-

terior; see Batty 1994) or emphasizing physiographic

regions rather than social regions despite the dominant

role of human activity on the Chinese landscape.

After a decades-long lapse, in 1980s and 1990s the

Chinese government began compiling and releasing a

wide range of social, economic, and environmental

statistics. Skinner and associates made use of these

statistics and newly available GIS technologies to

construct a still more detailed spatial framework for

China dubbed the Hierarchical Regional Space model.

(Parallel efforts using historical data have led to the

construction of HRS models for Japan and France.)

The HRS model aims to make explicit the spatial

relations among regions defined around human settle-

ments at multiple levels in the central place hierarchy.

Phenomena at a given location in the social-economic

landscape must be understood in terms of that loc-

ations position amidst the core-periphery structures

operating at different spatial scales at each level in

the hierarchy. Implemented in a geographic inform-

ation system, the HRS model has been shown to be

highly predictive of socioeconomic phenomena suchas fertility, education, and occupational stratification

by gender (Skinner 1994; Henderson et al. 1999; Skin-

ner et al. 2000; Henderson and Ladenson 2000). In

this paper we return HRS to the intellectual roots of

Thnenesque regional systems theory by applying it

to questions of urbanization and land use/land cover

change.

As applied to China, HRS theory is operationalized

as a multilevel hierarchical framework for analyzing

data for regional systems. Below the top hierarch-

ical level, Chinas nine macroregions may be divided

into central metropolitan subsystems, each oriented

around one or two major metropolises. Four such sub-

systems Beijing-Tianjin, Shijiazhuang, Zhengzhou,

and Jinan-Qingdao are found in the North China

macroregion. (Figure 2 outlines the nine macrore-

gions of China and the four subsystems of North

China, including the region around Beijing that is

the focus of this paper.) At this hierarchical level


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Figure 2. Chinas macroregional systems in relation to provinces, showing metropolitan cities, 1990. Within the North China macroregion,

four subregions are delineated with heavy dashed lines (from Skinner et al. 2000).


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we can discern the broad core-periphery pattern of

socio-economic development through an analysis of

county-level statistics and household census returns.

For the Beijing region these are grouped into seven

core-periphery zones (see figure 3), representing the

structural distance from the core to settlements within

each zone, taking into account socioeconomic vari-ables and transportation costs. (Skinner et al. 2000,

provides a detailed description of the analysis rep-

resented by these zones. The core-periphery concept

itself is widely used in urban studies; see for example

Wallerstein 1991; Krugman 1991; or Chase-Dunn and

Hall 1991.)

In implementing the HRS model for China, Skin-

ner et al. (2000) has continued below the level of

regional cities to assign some 12,000 smaller cities and

towns to levels in the central place hierarchy. These

assignments are not simply a matter of classifying set-

tlements by population size; as countless applications

of the rank-size rule have shown, we can expect no

hierarchical discontinuities within an ordered list of

city populations below the level of the primate city,

and China is no exception (Zipf 1949; Skinner 1976;

Mann 1984; Marshall 1989; Reed 2002). Instead,

central places are classified by the urban functions

they perform for their surrounding hinterlands. In the

case of China, published statistics on urban functions

were used for cities in the upper levels of the hierarchy

to guide the analysis; population figures play a role in

the lower levels, but the breakpoints between levels

necessarily vary with each local urban system. Central

place analysis expects settlements at each level withinthe hierarchy to show a high degree of primacy with

respect to the lower-level central places in their hinter-

lands. Thus the delineation of regional systems and the

assignment of the central places therein to hierarchical

levels follows a top-down approach as advocated by

Marshall (1989), identifying the primate settlement at

each level and its dependent nodes at the next lower

level, ultimately revealing the urban hierarchy from

metropolis to market town.

Figure 3 depicts the urban hierarchy in the imme-

diate vicinity of our Beijing study area and outlines the

boundaries of regional city systems, a middle hierarch-

ical level in the HRS model. Each regional city (there

are some 272 in all of China; Skinner et al. 2000,

p.619) serves as the economic and social hub of these

systems. And, with patterns analogous to those seen at

the macroregional level, regional city systems are ex-

pected to exhibit their own core-periphery structures.

These assignments, along with administrative ranks

assigned by the Chinese government, have been used

to characterize every location in China along an urban-

rural continuum; this dimension of the HRS model

aims to approximate the core-periphery structures of

lower-order urban centers and their immediate hinter-

lands. Thus the HRS model allows us to contextualize

any settlement in agrarian China by its position withinboth high-level and meso-level core-periphery struc-

tures: by its core-periphery zone and by its urban-rural

continuum category.

For this study of urban expansion, the space

between settlements is modeled by interpolating the

core-peripheryzone assignments between mapped set-

tlements, and by extending the urban-rural continuum

categories outward along transportation routes using

the distance-decay function common to gravity mod-

els. The key model variables, then, account for the

structural distance from a given point to the urban

nodes at different levels in the urban hierarchy, as well

as the transportation distance to the nearest settlement

of any level.

Results and analyses

The results of classification of land use and land cover

of 1975, 1984, 1991, and 1997 are mapped in Figure 4.

Six types of land use/ land cover are identified in the

map, with intensive and extensive urban area lumped

together. Maps of changes in urbanization are shown

in Figure 5. In this section, we will discuss the changes

in land use and land cover, in spatial patterns, and inurban functions.

Changes in land use and land cover

Table 1 summarizes the change in land use and land

cover in the study area of a total of 4500 km2. The

values in each row represent the percentages of each of

the seven land use/cover types in the study area for one

point in time. The table shows that five types of land

increased in their areas while two types decreased.

Among the gaining side, urban expansion is the most

significant. Putting together both urban land types, we

see that 14% (or 630 km2) of the land in the study areawas converted to urban use in the 22-year period from

1975 to 1997. As a result, the urban area more than

doubled during the period. Water surface, orchards,

and forest cover also had significant growth. On the

losing side, farmland lost about one third of its area

in 1975. The lost land, about 945 km2, was mostly


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Figure 3. Core-periphery structure of the North China macroregion, showing high-order cities and major transportation network, 1990. The

level of shade (gray) indicate the gradient from core to periphery. See 2.3. for description how the gradient is defined and delineated.


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Figure 4. Land use and land cover classified from Landsat MSS and TM data, (a). 1975; (b) 1984; (c) 1991; and (d) 1997. Intensive and

extensive urban areas are combined.

used for urban expansion and aquaculture. Shrubs and

grassland had a significant loss to reforestation, mostly

in the mountainous areas where the natural vegetation

prior to timber harvest was temperate forest.

Changes in spatial patterns

Three major changes in spatial pattern have been ob-

served: (1) the expansion of the urban core, (2) the

formation of secondary urban centers, and (3) the

fragmentation of the landscape.

First, the expansion of the urban is obvious from

the maps from 1975 through 1997 in Figures 4 and 5.

Most of the expanded urban areas took place around

the edges of the existing urban area, mostly through

nibbling the farmland around the city. The core

expansion was accompanied by the mergence of sec-

ondary urban clusters. For example, on the map of

1975, a dumb bell-like band of urban area in the west

and southwest of the city was well recognizable. The

west cluster, labeled with circle and number 1 in Fig-

ure 4, was where a major state-owned steel plant, the

Capital Steel, was located; and the southwest cluster is

a suburban town called Fengtai which was a major hub

of freight trains. Over the years, these clusters grew

fast enough, and quickly merged with the main urban

core. By 1991, the farmland between the dumb-bell

band and the urban core was hardly recognizable and

continued to grow through 1997.

The second feature is the formation of second-

ary urban centers, or secondary central places in

Christallers (1933) terminology. There are largely two

types of secondary urban clusters around the core of

Beijing: the capital towns of the counties and the in-

dustrial buildups of large, and usually state-owned,

enterprises. In addition to the two clusters mentioned


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Table 1. The fraction of land use/cover types in four points in time.

Intensive Extensive Water Crops Orchards Shrubs/ Forest

Urban Urban Grass

1975 1.29 4.68 1.19 66.66 6.03 16.04 4.10

1984 1.53 10.86 2.28 60.29 7.09 12.31 5.64

1991 2.19 12.45 4.44 54.41 7.56 12.06 6.90

1997 6.44 13.54 7.39 45.66 8.68 10.13 8.16

in the last paragraph, we marked eight other second-

ary urban clusters which could be barely recognized

in the 1975 map. These clusters were seeds to grow.

By 1984, all marked clusters had significant growth

in area, and clusters 1 and 2 merged with each other.

By 1991, clusters 1, 2 and 3 were essentially in-

tegrated with the urban core due to their respective

expansion. Other marked clusters grew to become sig-

nificant urban centers. The formation and growth ofthe secondary urban centers markedly changed the

pattern of the landscape.

The third feature of the landscape change is char-

acterized by the increased fragmentation. Shi et al.

(2001) calculated both landscape diversity index and

fragmentation index. The diversity index increased

from 0.49 in 1975 to 0.70 in 1997 for the study area.

Meanwhile, the fragmentation index increased from

0.71 to 0.81. Important differences in fragmentation

exist between the flat areas (about 80% of the total

area of study) and the mountainous area (20%). For

the plains, the diversity index increased from 0.38 to0.56, while the fragmentation index from 0.73 to 0.90.

For the mountainous area, the diversity index varied

in the range from 0.52 to 0.56, but the fragmentation

index decreased from 0.93 to 0.56.

The change in fragmentation indicates the effect

of land use and land cover change on the overall

pattern of the landscape. The plains were severely

impacted by urban expansion which resulted in in-

crease in fragmentation, while the mountains were

reforested with young trees, leading to decrease in

fragmentation of the landscape. This agrees to gen-

eral observation that urban expansion and intensified

transportation network tend to increase the landscape

heterogeneity, while the reforestation homogenizes the

vegetation cover of the mountains. In fact, 99% of the

urban expansion took place on areas with slope less

than 5 deg, and more 96% of the urbanization on areas

with elevation less than 100 m (Shi et al. 2001). The

fact that most urbanization took place on relatively

homogeneous areas makes it difficult for the CA ap-

proach using topography as a major driver the change

in land use / land cover.

Increased core-periphery interactions: The example

of vegetable supply

The changes of urban functions are closely related

to the transformation of the landscape patterns as aconsequence of urbanization. The urbanization of the

Beijing area showed that the patterns and functions

co-evolve with each other. These changes together res-

ulted in functional integration of the core and the sur-

rounding areas. More profoundly, the changes helped

to convert the areas surrounding the municipality to

functionally integral parts of the urban hierarchy. As

a result, the urban core of Beijing has increased its

influence over the expanded periphery. The surround-

ing areas which otherwise used to be little impacted

by the municipality have now become integrated in

economic, social and ecological functions with themunicipality. On the other hand, the dependence of

the urban core on the newly expanded periphery has

increased. This dynamics of evolving core-periphery

interactions is important in understanding and mod-

eling the change of landscape patterns. We use the

vegetable supply as an example to demonstrate this

important feature in urban function dynamics.

Fresh vegetable has become perhaps the largest

foodstuff consumed by the urban population. This has

to do with the diet structure of the Chinese people

who, in general, consume much less meat as com-

pared to the people in the Western countries. Cities

themselves do not produce vegetables, and vegetablesupply to the cities depends largely on the nearby rural

areas. However, municipalities which include rural

areas surrounding the urban cores had great capacity

for vegetable supply (Skinner 1978). In 1975, Beijing

achieved self-sufficiency in vegetable supply, with

about 90% of its consumption of vegetables produced


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in the rural landscape in these regions was plastic

covered greenhouses surrounding the rural villages.

The rapid urban expansion in Beijing area was closely

coupled with the widespread reallocation of land from

grain production to vegetable and fruit production in

the neighboring Hebei and Shandong Provinces.

The regional expansion of vegetable supply de-veloped with formation and growth of specialized

vegetable production zones. In Shandong Province

alone, several counties developed their specialized

zones for vegetable production. Counties in Liaocheng

Prefecture, 250 km from Beijing, became special-

ized in vegetable production by late 1980s. Similarly,

Shouguang County has become the largest vegetable

production base in China. This county alone sup-

plied 20% of all vegetable consumption of the city of

Beijing in 1990s.

Lowered cost of transportation has been an im-

portant factor. For example, Suning county of Hebei

Province is 220 km south of Beijing. It used to take

6 h to travel to Beijing by bus ten years ago. Now the

travel time is cut by half due to the improvement of

roads and means of transportation. In this relatively

small county where vegetable production used to be

for households self-consumption, 25% of the arable

land is now allocated for vegetable production, mainly

to be transported Beijing (Suning Statistics Summary

2000). In effect, at least part of each of the provinces

surrounding Beijing has become well integrated in

function with the Beijing metropolis.

Discussion

Land classification and measures of landscape

measures

We were able to identify seven types of land use and

land cover. It is possible to make more detailed clas-

sification, particularly using LANDSAT TM data, but

the seven types are adequate for our purpose in this

study. Rather than accurately quantifying each land

type, we focused on characterizing the change of the

spatial patterns and functions of the urban landscape

of Beijing and on uncovering the evolving interac-tions between the urban core and its periphery that

accompanied the changes of landscape patterns.

Due to the lack of TM data for 1975, we used MSS

data instead. The difference in spatial resolution (30 m

for TM vs.180 m for MSS) would inevitably introduce

errors in both land classification and in calculation of

measures of landscape structure (Qi and Wu 1996; Wu

et al. 2002). It is likely that the resulted errors do not

obscure the overall trend in landscape structures from

1975 to 1984. This was a period when great changes

in landscape patterns took place.

The diversity index is generally not a good choice

to indicate the fragmentation of landscapes. We usedit in combination with fragmentation index calculated

in Shi et al. 2001.

The core-periphery interactions and transformation

of urban landscape

More than two decades of urban development not only

has transformed the landscape of the municipality of

Beijing, but also changed the overall landscape in

the peripheral regions. The extent of the periphery

has expanded and the functional links between the

urban core and its periphery have been tightened. The

perspective of viewing the dynamics of the urbaniz-ing landscape as an evolving process of interactions

between the urban core and periphery has import-

ant implications for modeling the landscape changes.

The urbanization process in Beijing region can be

viewed largely as process of core-periphery interac-

tions, while the characteristics of specific locations has

played minor role in affecting land use and land cover

change. The changes of spatial patterns at large scale

are closely linked to the spatial interactions between

the different levels in the urban-rural continuum in

the core-periphery zone. For this particular case of

Beijing, topography, which is usually an importantdriver for land use and land cover change, has doubt-

lessly played a minor role, because of its lack of

heterogeneity in the region. No other single or mul-

tiple factors, physical or socio-economic variables,

seemed to have major influence on the landscape trans-

formation in the region during the period under study.

Therefore, as an alternative, the HRS approach serves

as a complement to the CA approach.

The use of the HRS model

We noted that both HRS model and its predecessor,

the central place theory, were developed for under-standing the regional structure of agrarian societies.

In our case, the Beijing municipality and the sur-

rounding region are one of the most industrialized

regions in China. Yet HRS still works as a qualitat-

ive theory, as demonstrated in Skinner et al. (2000),

in explaining the social-economic structures of the


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387

lower Yangtze River basin. This has potential to be-

come a quantitative model of landscape dynamics of

the region. However, this model will have to include

Tianjin, another major metropolitan entity of the same

macroregion (see Figure 2). An interesting observation

is that the rate of urban expansion of Tianjin has been

much slower than that of Beijing. Some even arguethat it is the development of Beijing that has drained

the resources and market that are otherwise shared by

Tianjin. If this is the case, it provides an example of

core-periphery interactions of different type. But this

much more complicated case is beyond the scope of

this study.

The urban expansion in Beijing is a result of

reallocation of energy, material, information, capital,

labor and market. These elements distribute, flow and

dissipate with the spatial structure and make the struc-

ture itself to evolve (Costanza 1977). HRS model

provides a macroscopic view of the overall system,

and a theoretical framework, supplementing the CA

model, for building the model of landscape dynamics.

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