Geography Reference
In-Depth Information
cover conversions and projection of possible future land use changes, both of
which heavily rely on the land use simulation models. Besides, the land use
simulation model also provides an essential approach for stakeholder to project
and evaluate the potential consequences of policy decisions and other actions. As
more scholars realized the importance of LUCC, the land use simulation model has
become an important tool for the analysis of both the mechanism and the spatial
distribution of LUCC in the past and future (Deng et al.
2012
; Hu et al.
2004
).
The land use simulation models include Markov model, logistic function model,
regression model, econometric model, dynamic systems model, spatial simulation
model, linear planning model, nonlinear mathematical planning model, mechanistic
GIS model, CA model, and so on (Flamenco-Sandoval et al.
2007
). All of these
models may help to explore the combined effects of social policies, individual
behavior, and other drivers of the land use change, however, most of them have
some drawbacks. For example, the Markov model has been widely used to simulate
the land use change, but it involves no spatial factors, so the land use change cannot
be spatially explicitly reflected. The CLUE-S model can comprehensively analyze
the regional LUCC process and driving force, but it can only be used in the spatial
allocation so far, while the nonspatial changes must be estimated with other methods
(Deng et al.
2008
). Therefore, although some models can be used to simulate land
use change, there are still some serious drawbacks (Liu and Deng
2010
; Cai et al.
2004
). Moreover, there were few global models to simulate the LUCC, especially in
the study of the interaction mechanism among the social economy, climate change,
and LUCC. In some sense, the GTAP-AEZ model and the Global Change Assess-
ment Model (GCAM) are more useful in the land use simulation, which can simulate
the land use change of each agricultural ecological zone (AEZ), combined with the
influences of social economy and climate change at global scale (Sands and
Leimbach
2003
; Lee
2004
; Burniaux and Lee
2003
). However, the parameters of
these models are rough and the simulation accuracy needs to be improved.
In the preparation for the fifth Assessment Report of the Intergovernmental
Panel on Climate Change (IPCC AR5), the international community is developing
new advanced Earth System Models (ESMs) to address the combined effects of
human activities (e.g., land use and greenhouse gas emissions) on the carbon-
climate system. Besides, the four Representative Concentration Pathways (RCPs)
scenarios of the future (2005-2100) have been provided by the four Integrated
Assessment Model (IAM) teams, which are used as input to the ESMs for the
future carbon-climate projection (Moss et al.
2008
; Moss et al.
2010
). This study
aims to compare the simulation results of land use change obtained from the
GCAM and GTAP-AEZ model and improve the simulation accuracy through
optimizing the input parameters of the models, and the calibrated GCAM can be
used to provide more scientific reference information of land use change for the
land use planning and policy formulation to mitigate the climate change in China.
