Geography Reference
In-Depth Information
Table 3.6 Mapping table of land use/cover types of USGS and GCAM classification systems
ID USGS_Code USGS_Name GCAM_Code
1 100 Urban and built-up land 50
2 211 Dryland cropland and pasture 10
3 212 Irrigated cropland and pasture 10
4 213 Mixed dryland/irrigated cropland and pasture 10
5 280 Cropland/grassland mosaic 10
6 290 Cropland/woodland mosaic 10
7 311 Grassland 30
8 321 Shrubland 20
9 330 Mixed shrubland/grassland 30
10 332 Savanna 30
11 411 Deciduous broadleaf forest 20
12 412 Deciduous needleleaf forest 20
13 421 Evergreen broadleaf forest 20
14 422 Evergreen needleleaf forest 20
15 430 Mixed forest 20
16 500 Water bodies 40
17 620 Herbaceous wetland 40
18 610 Wooded wetland 40
19 770 Barren or sparsely vegetated 30
20 820 Herbaceous tundra 30
21 810 Wooded tundra 30
22 850 Mixed tundra 30
23 830 Bare ground tundra 30
24 900 Snow or ice 40
Note in the column ''GCAM_Code'', 10 represents Cropland; 20 represents Forestry area rep-
resents 30, Grassland represents 40 represents Water area; 50 represents Built-up area
where ld
i,t+1
is the predicted area of the ith land use/cover type of USGS classi-
fication in year t + 1. ldg
j,t
is the predicted area of the ith land use/cover type of
USGS classification in year t. ld
k,j,t
is the predicted area of the kth land use/cover
type of USGS classification, which corresponds to the jth land use/cover type of
GCAM classification in year t.
3.2.2.2 Simulation Results
In the future, the land use/cover in China will be continually changed by human
activities and climate changes, and their spatial pattern will change dynamically as
well.
(i)
The simulated changes of LUCC. In the study, we simulated the changes of
LUCC in China in the future using GCAM model combined with the econo-
metric model under the three scenarios (Fig.
3.7
). The simulated results show
the changing trends of different land use/cover in three different scenarios.
