Geoscience Reference
In-Depth Information
12.4
Methodology
A cellular automata model was developed to investigate the scenarios of future
urban land transformations in Houston. This model started on a 30-m grid and the
transition rules were applied to all cells at the same time, and the entire grid was
updated at the annual iteration. The transition rules were defined as the difference
between the center cell and eight neighbors within 3
3 Moore's neighborhood. To
determine the state of a cell in a certain time period, the simulation function was
written as:
S
t C1
i;j
D
a
N
N
i;j
C
a
M
M
i;j
C
a
SE
SE
i;j
(12.1)
where N
i
,
j
denotes the diffusion factor regarding its neighborhoods, M
i
,
j
denotes
the Markov transition probabilities, SE
i
,
j
denotes the socioeconomic status of each
single cell and its neighborhoods;
a
represents the coefficients for these variables.
For a self-organizing CA model, the diffusion factor, Markov transition rules,
and socioeconomic status were defined as:
n
i;j
X
n
i;j
N
i;j
D
(12.2)
N .i; j /
,
m
X
m
k
X
i D1
M
i;j
D
(12.3)
k
m
k
kD1
d
i;j
min
d
i;j
max
d
i;j
0
@
1
A
X
n
min
d
i;j
nD1
SE
i;j
D
(12.4)
n
where
n
i
,
j
is the total number of class
i
surrounding the observed class
j
,N(
i
,
j
)is
the observed landscape amount changing from class
i
to class
j
during total
m
years
at
k
internal steps, and
d
i
,
j
is the different value in the selected four socioeconomic
variables between the observed center cell and its
n
neighbors (Fig.
12.3
).
Although the socioeconomic data were collected at the last year of simulation, the
difference of socioeconomic values between the observed cell and the neighbors was
used to determine the socioeconomic factors. Obviously, different socioeconomic
variables have different impact weights to the urban land use/land cover change.
In order to find the weightiness of each socioeconomic variable, 20 experts in the
field of socioeconomic and land use change were invited to assign weights to each
variable using the index ranging from 0 to 10 to represent the weight from the
highest impact to the lowest impact. The average value of these ratings was shown
in Table
12.3
.
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