Wheat area assessment by remote 
sensing in 6 counties 
(from the 1991-96 period) 
  
  
  
  
  
  
Maize area assessment by remote sensing in 
6 counties 
(from the 1991-96 period) 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
165000 
150000 
* | z 145000 + 
£ " $ 
m 129000 | | % 125000 | 
5 | 
V 100000 1 | Z 105000 + 
SS ~~ 
Ë 75000 " | £201 
£ 50000 | | $ 45000 + 
= } rj 
$ 250001 R2=0,97 | £ 25000 + A 
= ! | 5000 ' + 
: / 5000 55000 105000 155000 
0 50000 100000 150000 4 
Area assessment by remote sensing Area assessment by remote sensing 
FOMI RSC (ha) FOMI RSC (ha) 
Fig.1.a. Fig.1.b. ; 
The satellite data coverage was incomplete for these The figures compare similarly to those of wheat. The 
years and counties reason for somewhat weaker relationship is the 
(missing year: 1994). The area estimation for winter practice and statistics of maize for silage. Only a part 
wheat shows a strong relationship between the of maize is sown originally for ensilage. Many times 
traditional (questionnaire) method and the remote decisions are made if needed for maize ensilage along 
sensing one. The data appear remarkably earlier from the season. New methods suggest compensation to this 
the remote sensing system. effect. The missing data are the same as in Fig. | .a. 
Wheat yield estimation by remote sensing in Maize yield estimation by remote sensing in 
6 counties 6 counties 
(from the 1991-96 period) (from the 1991-96 period) 
8000 
= = 7000 + 
o o 
Ü G 6000 + 
2 E uM 5000 sg 8 
= sg 
3 2 § 4000 + 
8 x 
Ë B 7 3001 
- = |J E 
3 = 2X0 R? = 0,96 
2 2  1000—+ 
2° 200} 5 $ HANOOD 
2000 i ; 0 + | 
2000 3000 4000 5000 6000 0 2000 4000 6000 8000 
Yield assessment by remote sensing Yield assessment by remote sensing 
FÓMI RSC (kg/ha) FOMI RSC (kg/ha) 
Fig.2.a. Fig.2.b. 
The satellite data coverage was incomplete The maize yields can be predicted early prior to 
for these years and counties (missing year: the harvest. The sample comprises diverse 
1994). The wheat yields can be predicted by years. The missing data are the same as in 
remote sensing prior to the harvest. These Fig.1.a. 
years comprise good and extreme bad ones 
as well. The missing data are the same as in 
Fig. 1.a. 
110 International Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 7, Budapest, 1998