Geography Reference
In-Depth Information
Table 4.2
Land use/cover types of the USGS classification system
Code
Description
Code
Description
1
Urban and built-up land
14
Evergreen needle leaf forest
2
Dryland cropland and pasture
15
Mixed forest
3
Irrigated cropland and pasture
16
Water bodies
4
Mixed dryland/irrigated cropland and
pasture
17
Herbaceous Wetland
5
Cropland/Grassland Mosaic
18
Wooded Wetland
6
Cropland/woodland Mosaic
19
Barren or sparsely vegetated
7
Grassland
20
Herbaceous Tundra
8
Shrubland
21
Wooded Tundra
9
Mixed shrubland/Grassland
22
Mixed Tundra
10
Savanna
23
Bare ground Tundra
11
Deciduous broadleaf forest
24
Snow or Ice
12
Deciduous needle leaf forest
99
Interrupted areas (goodes homolosine
projection)
13
Evergreen broadleaf forest
100
Missing data
Due to the land use/cover data classification mechanism in WRF model is the
USGS classification system (Table
4.2
), and the simulated land use/cover data in
2040 with DLS model were classified by the land cover classification of IGBP. The
simulated data were reclassified into USGS classification system with classifier we
developed before. In addition, the scale of these data is 1:100000 and the inter-
pretation accuracy exceeds 92 % (Liu et al.
2010
).
The climate forcing data used in this study were the geographically segmented
(GEOG) data obtained from NCEP FNL (Final) Operational Global Analysis data,
which is updated every 6 h. This dataset has been constructed and updated since July
of 1999 with the data assimilation of almost all kinds of observation data (e.g., the
remote sensing data and ground-based observation data), it has the spatial resolution
of 1 9 1 and the vertical height of 27 layers. And the time period of the data were
truncated from the January of 2000 to December of 2010. Then the climate forcing
data were prepared on the basis of these data. The NCEP/FNL dataset has higher
accuracy and spatial resolution and includes more kinds of environmental variables
than the datasets of NCEP I, NCEP II and EAR40. This study has used the Noah land
surface parameterization scheme, with which the simulation result is more stable and
reasonable. The data of the temperature field and precipitation field in this scheme
were interpolated with the large scale information.
4.1.2 Results
The change of cultivated land in Northeast China is directly caused by the human
activities in the context of the special regional geographical conditions, such as the
plenty
of
the
complex
mountains
in
this
region.
The
population
growth
is
the fundamental reason for the expansion of cultivated land in Northeast China, the
