Geography Reference
In-Depth Information
3.4 Summary
In this chapter, specific simulations of land use changes were introduced. In the
first section, we assess the possible trends of land use change that drove by social
and economic development in order to better mitigate climatic change, especially
CO
2
emissions. We use AGLU module of GCAM model to assess corresponding
land use structural changes, and then use land use change to obtain the CO
2
emissions under each scenario. By setting three different socio-economic devel-
opment scenarios,, we can choose the optimized scenario of reducing CO
2
emis-
sions, which provides a theoretical basis of land use planning to climate change
mitigation.
In the second section, we predict the future structure of land use/cover with the
aid of GCAM and an econometric model. Spatial allocation of future land use/
cover in China is simulated with the DLS under three scenarios, i.e., BAU sce-
nario, REG scenario and CES. The simulation results show that land use/cover in
China will change continually due to human activities and climate change, and the
spatial pattern of land use/cover will also change as time goes by. Besides, the
spatial pattern of land cover in China under these three scenarios is consistent on
the whole, but with some regional variance. Built-up area will increase rapidly
under all three scenarios, however, most of the other land cover types will show a
decreasing trend to different degrees under different scenarios.
To date, high-precision land cover data to support climatic modeling in China is
absent. To this end, in the third section of this chapter, we first overlay the land
cover maps of the IGBPDIS, GLC, UMD and WESTDC, and select the grids with
agreement of classification as the sample grids. We then combine the land cover
data from CAS with the land use data to generate land cover data of high accuracy
for climate simulation. The produced temporal land cover data using this method
can meet the accuracy requirement of climate simulation and can be applied as the
parameters of dynamical downscaling in regional climate simulation.
References
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Bartholomé E, Belward A (2005) GLC2000: a new approach to global land cover mapping from
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Berg A, Papageorgiou C, Pattillo CA, Spatafora N (2010) The end of an era? the medium-and
long-term effects of the global crisis on growth in low-income countries. IMF Working
Papers, pp 1-29
Brenkert AL, Smith A, Kim SH, Pitcher HM (2003) Model documentation for the MiniCAM.
Pacific Northwest National Laboratory, Richland, WA
