Geography Reference
In-Depth Information
and DLS model. The DLS model is capable of simulating the spatial dynamics of
LUCC, and case studies indicate that it is an effective tool to simulate the process of
land use change (Yin et al.
2010
; Deng et al.
2008
).
One of major issues is to settle temporal data of current research on driving
force of LUCC which is only from simple perspectives. Therefore, it is significant
to obtain the long-term temporal data of LUCC parameters. For that purpose, this
study simulates structural changes of land use in China with the GCAM through an
econometric model with socioeconomic factors as the driving forces. Thereby an
econometric model is set up to forecast the built-up area change, and the changing
trend of land use is simulated based on different scenarios of socioeconomic
development. Thereafter the DLS model is used to forecast the future spatial
pattern of LUCC in China.
3.2.1 Scenario Design and Downscaling Simulation Method
3.2.1.1 Scenario Design
In this study, three scenarios were designed according to characters of historical
socioeconomic development of China, including the BAU scenario, REG scenario
and CES scenario. The BAU scenario mainly reflects future changing trends of
population and economy, which provides the baseline trend of land use change.
Based on the BAU scenario, the REG scenario and CES scenario were designed
according to main risks and adjusted direction of China's medium and long-term
development plan. It is assumed that under the BAU scenario urbanization and
industrialization will continue, the TFP that is on behalf of scientific and tech-
nological progress will develop by following the historical development trend, and
China's population will peak in 2030s, but the population growth rate will grad-
ually reduce. The REG scenario assumes that the industrial structure adjustment
would be smoothly carried out, resource allocation and industrial structure would
be more reasonable, while the speed of economic growth will keep steady. Under
the CES scenario, the population growth rate is lower than it is under the BAU
scenarios, the urbanization rate is relatively lower and GDP would increase with a
lower rate (Table
3.5
).
3.2.1.2 Data
Input data used in this study include the baseline structure land use/cover data and
historical socio-economic data for both GCAM model and econometric model, and
the baseline land use/cover data and some driving factors data for DLS model.
The baseline data of land use/cover change are derived from the dataset of
National Basic Research Program of China. With these spatial distribution data,
the initial land use allocation data in 2000 used by GCAM model could also be
