Full text: Technical Commission VIII (B8)

      
   
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
   
  
  
  
  
  
  
  
   
  
   
     
   
  
  
  
  
   
  
  
  
  
  
   
   
    
   
    
   
  
     
     
  
   
  
   
  
  
  
  
    
IX-B8, 2012 
'ounties from the 
0 periods from the 
sidering the whole 
in the first period, 
ond period. On the 
14.6 % in the first 
cond period. The 
y 45% and then 
decreased all over 
or each period. The 
nuch in total. For 
se for paddy land 
2000. On the other 
decreased in these 
dryland increased 
e time, grassland 
slightly increased. 
ddy fields show a 
ied by a more than 
of grassland. 
010 
rm area in the SJP 
. Overall, the TSA 
950, the TSA was 
ever, until 2010 it 
ird of the counties. 
wed an increase. In 
ore than 20 000 ha. 
by more than 3.5 
, the increase was 
iobei, Suibin and 
Although it is not 
sification, the TSA 
{, the TSA in each 
han 150 000 ha in 
rom 2004 to 2010, 
w, in more than a 
000 ha. 
  
Others 
980s to 1995 
1995 to 2000 
site -3.8 
0.3 -3.1 
3.5 -6.6 
10.7 -1.4 
78 -2.2 
-0.6 -1.0 
-16.1 -4.5 
-9.8 9.2 
1.3 0.7 
5.8 -0.5 
1.8 -3.7 
tive counties 
  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
  
  
  
  
+ Muling f 
Legend 
  
  
  
    
Nodata Wa» 70000-110000ha 4. Jiamusi 
»20000-70000ha i^ 150000-365000ha  3:Qitaihe 
Data Source: 
NGCC, Beijing, China, 2010 
s20000ha Wii» 110000-150000ha 2:Shuangyashan o 50 100 200  CBSED, Harbin, China, 2011 
MN kr Map author: Q. Zhao, 2012 
  
  
Figure 3. Total sown area of the non-farm area in the SJP for the last 60 years 
4. DISCUSSION AND CONCLUSIONS 
Land use change of paddy rice shown in Fig. 2 reveals similar 
results compared with the study by Chen et al. (2012). Due to 
climate warming in Heilongjiang starting in the 1980s, the sown 
area of rice increased strongly (Guo, 2003; Yun, 2005). 
However, a severe problem for rice growth in the region is cold 
damage which happens frequently (Zhang et al. 1991). In 
general, rice produces higher yields than e.g. soy bean but is 
more temperature sensitive. Consequently, farmers changed the 
crop type from year to year. 
In Muling County, the most southern one of the SJP (Fig. 1), 
farmers first cultivated a large area of paddy fields in the early 
years of the 1980s because of the increasing temperature. After 
several colder years, they changed some of the paddy land into 
dryland, then again changed back to paddy fields (from 
2 198 ha in the 1980s to 17 025 ha in 1995 and back to 2 198 ha 
In 2000). From Tab. 2, it can be easily derived that the paddy 
land was mainly converted from dryland and wetland, since the 
other land use classes did not change significantly. The increase 
of dryland is mainly due to conversion from grassland in the 
period of the 1980s to 2000. 
The change of the TSA during the last 60 year in Fig. 3 shows a 
Special trend. The TSA increased very much in the first 15 
years. After the establishment of the new China in 1949, people 
focused on the agricultural production: New farming fields were 
reclaimed in a short time. From 1965 to 1980, the TSA did not 
increase very much. In the 1980s, the focus was on increasing 
yield, not on reclaiming more agricultural land. From 1994 to 
2004, the reclamation of arable land occurred under pressure of 
increasing population and food demand. With the availability of 
new technologies, it was possible to manage larger areas. The 
TSA increased rapidly in the six years from 2004 to 2010. 
The AEIS for the SJP will be used to investigate the long-term 
change of the agro-ecosystems, to provide data sets for 
ecosystem modeling and to derive sustainable management 
strategies. It was possible to integrate first basic datasets in the 
AEIS for the SJP. The main difficulty in establishing an AEIS is 
the acquisition of available detailed soil data which is 
demanded for spatially distributed agro-ecosystem modeling, of 
detailed management data, as well as of detailed land use maps 
which differentiate between the different crops within arable 
land. 
5. REFERENCES 
Bareth, G., 2009. GIS- and RS-based spatial decision support: 
structure of a spatial environmental information system (SEIS). 
International Journal of Digital Earth, 2(2), pp. 134-154. 
   
	        
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