Geography Reference
In-Depth Information
development priority, priority
min
is the minimum of all-region's urban land
development priority, v
max
and v
min
are all-region's maximum and minimum of
cellular transformation speed.
Since cellular automaton model does not have the concept of transform speed
but only evolution interval, so we need to convert evolutionary speed to evolution
interval here.
1
Interval
ij
pri
ΒΌ
v
ij
pri
The above formula is the corresponding evolution interval of evolving speed.
Accordingly, we can estimate asynchronous evolution interval of urban land
expansion for Wuhan Metropolitan.
6.3.3 Results
6.3.3.1 Urbanization Pattern Scenarios for Wuhan Metropolitan
Urbanization patterns are divided into two categories: centralized and decentral-
ized urbanization. Centralized urbanization has three main features: First, urban
scale structure is centralized. It is mainly performed that large cities, metropolitan,
and medium-sized cities lead in development. Second, cluster is the main feature
of city metropolitan. It is mainly showed that formation and development of
various levels and influential metropolitan intensive areas. Third, urban land use
become more intensified spatially. In our research, centralized urbanization mainly
refers to the first characteristic, namely, cities, metropolitan, and medium-sized
cities lead in development. Corresponding decentralized urbanization, the main
characteristics is that small towns lead in development.
According to urbanization patterns, three scenarios of urban land expansion are
designed. They are baseline scenario, centralized urban land expansion scenario,
and decentralized urban land expansion scenario in this research. Under baseline
scenario, urban land expansion in Wuhan Metropolitan follows its historical law.
Under centralized urban land expansion scenario, large cities lead in development,
while small towns' urban land use expansion speed is controlled. Under decen-
tralized urban land expansion scenario, priority in the development is achieved by
small towns, metropolitan urban land expansion are controlled. Accordingly, by
setting the asynchronous evolution interval of Partitioned and Asynchronous
Cellular Automata Model, urban land expansion patterns in Wuhan Metropolitan
under different scenarios can be simulated. Taking centralized urbanization sce-
nario for example, large cities will receive the prior development. At the same
time, cities have higher evolving speed, and the corresponding evolution should be
given a smaller interval. Accordingly, we could set three asynchronous evolution
intervals of urban land expansion under different scenarios in Wuhan Metropolitan
