Geography Reference
In-Depth Information
scenario, were designed based on the historical changing trends of land cover and
the historical and future trends of socio-economic development. This study selected
the population, total factors productivity (TFP), gross domestic product, (GDP) and
national policy as the variables of socio-economic development, the changing trends
of which are different under different scenarios. The BAU scenario mainly reflects
historical development trend of the population and economy, which provides the
reference to compare with other scenarios. It is assumed that the urbanization and
industrialization will continue under the BAU scenario; TFP, which is on behalf of
the scientific and technological progress, will develop following the historical
development trend, and China's population is expected to peak in 2030, but the
population growth rate will gradually reduce. The REG scenario and CES scenario
were designed according to the main risks and adjustment directions of the medium
and long-term development of China. The REG scenario assumes that the structural
reform of industries would be smoothly carried out, the resource allocation and
distribution of the industrial structure will be more reasonable, and the economy will
develop more and more quickly. Under the CES scenario, the population growth rate
is lower than that of BAU scenario, the urbanization rate is relatively lower, and
population and GDP would increase with a lower rate. Finally, with the socioeco-
nomic factors as the driving force, the structural change of land use under each
scenario is simulated with the module of Agriculture and Land Use in GCAM.
4.2.1.2 Simulation with the DLS Model
This study simulated the spatial pattern of land cover change in the study area with
the DLS model, which is a collection of programs that simulates pattern changes in
land uses by conducting scenario analysis of the area of land use change (Deng et al.
2008
). The DLS model can export a macroscopic map of land use by estimating the
effects of driving factors of spatial pattern changes, formulating land use conversion
rules and scenarios of land use change, and simulating dynamic spatiotemporal
processes of land use changes (Deng et al.
2008
). The simulation with the DLS model
includes four steps. First, the statistical relationship between the spatial distribution
of land use types and the driving factors is analyzed at the regional and grid scales,
and the key driving factors were extracted according to the effects of the natural
environment and socio-economic factors on the spatial patterns of regional land use.
Then the changing trend of the selected key driving factors is predicted based on their
historical characteristics and current status at the regional level. Thereafter, a proper
scenario is identified and used to foresee the balances between the supply and
demand of land resources. Finally, the spatial allocation of land cover is implemented
at 1 9 1 km grid pixel level, and the spatial pattern map of land cover is generated.
