Geography Reference
In-Depth Information
where, L v,p = 1 denotes that the vth type of vegetation is the dominant vegetation
in the pixel p and L v,p = 0 denotes that the vth type of vegetation is not the
dominant vegetation in the pixel p. This criterion defines that for any other veg-
etation type u, when P v,p,t+1 is positive and S v,u,p,t+1 is larger than 1 or no larger
than 0, or P v,p,t+1 is not positive and S v,u,p,t+1 is smaller than 0 or no larger than 1,
the vth type of vegetation is dominant vegetation in the pixel p in the (t + 1)th
year; when P v,p,t+1 is positive and S v,u,p,t+1 is larger than 0 or no larger than 1, or
P v,p,t+1 is not positive and S v,u,p,t+1 is larger than 1 or no larger than 0, the vth type
of vegetation is not the dominant vegetation in the pixel p in the (t + 1)th year.
For a specific pixel, vegetation change will happen as long as the productivity
of the new dominant vegetation exceeds that of the original dominant vegetation.
LV p ; t þ 1 ¼ v ;
if for 8 u 6 ¼ v ; RY v ; p ; t þ 1 [ RY u ; p ; t þ 1
ð 2 : 12 Þ
RY v ; p ; t þ 1 ¼ RY v ; p ; t þ RY v ; p ; t
RY p ; t
Y v ; p ; t þ 1
ð 2 : 13 Þ
RY p ; 0 ¼ X v
A v ; p ; 0
A p
Y v ; p ; 0
ð 2 : 14 Þ
where, LV p,t+1 denotes the new vegetation type that characterized the pixel p in the
(t + 1)th year. RY v,p,t+1 is the productivity of the vth type of vegetation in the pixel
p in the (t + 1)th year. RY p,t is the total productivity of all the vegetation in the
pixel p in the tth year; RY p,0 is the total productivity of all the vegetation in the
pixel p in the base year. A p is area of pixel; A v,p,0 is area the vth type of vegetation
in the pixel p in the base year; and Y v,p,0 is the productivity of the vth type of
vegetation in the pixel p in the base year.
2.1.2 Concluding Remarks on LUCD Model
In this part, we introduced the LUCD model which is compatible with RCMs to
provide endogenous underlying surface for climate modeling. This model is
constituted by economic module, vegetation change module, and agent-based
module. The economic module calculates the land use change demand driven by
economic activities aiming at maximizing economic utility. The vegetation change
module evaluates the probability of vegetation change driven by climate change.
These two modules depict the land surface process under the condition of rational
decision making and ideal circumstances. To couple the economic module and
vegetation change module, the AEZ is introduced in the LUCD model. The agent-
based module identifies if the land use change demand and vegetation change can
be realized under the condition of irrational decision making and multiple vege-
tation competition. By introducing the simulation results of the LUCD model in
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