Geography Reference
In-Depth Information
Afterwards, the impact on built-up area of population, GDP and urbanization
ratio, as socio-economic indicators, are estimated by econometric
model as
follows:
Y
t
¼ a
0
þ
a
1
X
1t
þ
a
2
X
2t
þ
a
3
X
3t
þ
e
t
ð
3
:
12
Þ
where Y
t
stands for the area of built-up area, X
1t
represents population, X
2t
is GDP,
X
3t
is urbanization ratio, a
0
is intercept. e
t
is random error term, which is a random
variable independent with other explaining variables, and assumed it satisfied
normal distribution with zero expectation and homoscedasticity.
DLS model presumes that the change of land use pattern is affected by both the
historic land use pattern and the driving factors within the pixel and adjacent pixels
(Yin et al.
2010
). DLS model includes three modules: driving force analysis
module, scenario analysis module and spatial allocation module.
DLS model analyzes balance between supply and demand of land resources at
the grid scale through spatial allocation module, which can be used to realize the
spatial allocation of structural data of land use so as to simulate LUCC under
different scenarios (Yin et al.
2010
; Deng et al.
2008
). DLS model provides
response function about land system structural changes. In addition, based on
evaluation of the suitability of land use type distribution, DLS will express spatial
dominant of possible scenarios on regional change of land system structure by
estimating the response function. DLS expresses the difficulty level of conversion
from one land type to other land types through defining transformation rule.
Spatial allocation module calculates the number of grids to allocate. As for the
grids needing distribution, the model would calculate the distribution probability
of the different land use/cover types and allocate those.
3.2.2 Simulation of the Pattern of LUCC in China
3.2.2.1 Simulation Scheme
The simulation scheme is as follows. The structural data of LUCC were simulated
on the basis of GCAM combined with the econometric model. Based on the
correspondence table of USGS classification and GCAM classification (Table
3.6
),
we allocated the land area in the structural data of LUCC with the original area
percentage of each land use/cover type in last year as the weight. So the data of
demand for each land use/cover type of USGS classification in each year during
2010-2100 are obtained.
ld
k
;
j
;
t
P
ld
k
;
j
;
t
ld
i
;
t
þ
1
¼
ldg
j
;
t
ð
3
:
13
Þ
