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fuzzy-pattern-matching method to measure agreement between
the model output and the real-world data was proposed by
Power, Simms and White (2001) and White (2006). Kocabas
and Dragicevic (2009) developed a validation method for agent
models based on Bayesian network and vector spatial data.
another 30% by tertiary (service) activities, though agriculture
still accounts for most employment of the rural labor force (Xie,
Yu and Bai, 2006).
There is a remarkable link between rapid urban growth and
rural industrialization and subsequent investments in non-farm
enterprises (Kirkby, 2000). New towns and urban development
have been observed across the entire study area, which has been
called ''desakota.'' The desakota emergence issue surrounding
rural urbanization stems fromcomplex factors (Lin, 2001; Xie and
Batty, 2005). This process to a large degree is local, spontaneous
and unplanned (McGee, 1989, 1991, 1998; Marton, 2000; Kirkby,
2000). The phenomenon of desakota conforms with the notion
that a structure emerges froma bottom-up process throughwhich
local actions and interactions produce global patterns. The nature
of desakota fits well with the capabilities of complexity system
based modeling approach, like agent-based modeling. Thus,
Suzhou Municipality is a good site for applying an agent-based
model to study the dynamics of urban growth.
The data for this model was derived from diverse sources.
Population, household and related socio-economic data were
collected from the statistical yearbooks (Suzhou City Statistical
Bureau, 1991, 1996, 2001). Data on urban and rural construc-
tion (which we assume proportional to household change) was
generated from remote sensed imagery using Landsat Thematic
Mapper (TM) images for 1990, 1995 and 2000. The pixel reso-
lution of Landsat TM images is 30m. This resolution suffices to
differentiate urban construction patches since they are large and
contiguous. Patches of rural construction have a non-contiguous
impervious surface and are small in size. Rural construction is
24.3
Case study
-
desakota
development in Suzhou,
China
Suzhou, the cradle of Wu Culture, is a city well-known for
its history (tracing back to the later Shang Dynasty more than
2500 years ago) and its classical gardens, called ''Paradise on the
Earth'' or the ''East Venice of the World.'' Suzhou is one of 13
prefecture cities of Jiangsu Province and the study area covers the
entire prefecture city, which includes Suzhou and six county-level
cities under its jurisdiction: Changshu, Zhangjiagang, Kunshan,
Taicang, Wujiang and Wuxian, with the urban district (Shiqu)
of Suzhou located within the administrative territory of Wuxian
(Fig. 24.1). The municipality of Suzhou has a population of
6.244 million (Suzhou Municipality Statistical Bureau, 2008).
Suzhou has served as a model for the development of rural
industries based on diversified collective enterprises run by the
local municipality model (Tan, 1986), and its network of pre-
existing towns and cities (Chen, 1988; Marton, 2000). Today
over 50% of GDP is provided by secondary industries with
Jiangsu
Province
China
Jiangsu
Towns in Suzhou
Suzhou Downtown
N
Suzhou City
0
30
60
Kilometers
FIGURE 24.1
The study area: Suzhou Prefecture City.
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