Full text: Application of remote sensing and GIS for sustainable development

64 
national level wheat forecasting is described by Supit 
(1997). 
(f) Linking of SOYGRO model to RS inputs and 
ARC/INFO for Orangeburg County, South Carolina, 
USA: In this study, the multidate SPOT data was used to 
prepare an agricultural mask, meteorological data was 
spatially organised in form of Thiessen polygons, soil 
survey map (46 soil types reduced to 8 dominant soil 
types) linked to attribute table for depth and soil water 
storage characteristics. The large area simulation was 
carried out by 40 model runs representing 8 dominant 
soil types in each of 5 Thiessen polygons (Carbone et 
al., 1996). 
Table 3. Summary of results ofNational Level wheat forecasts using multi-date WiFS data. 
1995-96 
1996-97 
1997-98 
Sample Approach $ 
20x20 km, ST 
20x20 km, ST 
15x15 km, ST2 
Mha 
CV% 
Mha 
CV% 
Mha 
CV% 
Bihar 
2.2744 
20.46 
1.9333 
19.42 
2.1876 
10.57 
Haryana 
1.9675 
10.56 
1.8735 
13.00 
2.1944 
5.49 
MP 
3.9665 
11.58 
4.3005 
11.17 
4.4670 
8.23 
Punjab 
3.2392 
5.56 
3.5301 
6.03 
3.2865 
5.03 
Rajasthan 
2.3542 
16.62 
3.0768 
20.11 
4.4761 
10.14 
UP 
10.5942 
4.91 
8.0572 
7.03 
8.7402 
4.11 
Other# 
2.7750 
5.35 
2.8850 
13.52 
2.8651 
10.01 
INDIA 
27.171 
3.68 
25.6569 
4.22 
27.2169 
3.26 
$ : Segment size, Stratification, (ST; Stratified Design, ST2 = Two stage stratified approach) 
Table 4. Crop simulation models for regional yield modelling and prediction. 
Crop 
Model 
Study Area 
GIS 
RS 
Application 
Reference 
Millet 
CERES-Millet 
Burkina Faso 
IDRISI 
(0.25 x 0.25 deg) 
Meteosat-Rainfall 
Famine Early 
Warning 
Thornton etal., 1997 
Sorghum 
QSORG 
South Australia 
Arc/Info 
Rainfall-polys# 
- 
Yield Forecasting 
Rosenthal et al., 1998 
Soybean 
SOYGRO 
S. Carolina, USA 
Arc/Info 
Rainfall, Soil, LC 
Land cover (LC) 
Spatial Yield 
variability 
Carbone et ai, 1996 
Wheat 
WOFOST 
Europe 
Arc/Info 
50 x 50 km grid 
- 
Yield Forecasting 
Supit, 1997 
Multiple 
crops 
CROPCAST 
Global 
48 x 48 km grid 
VI for validation 
Global yield 
forecasting 
- 
# polys : Polygon coverage
	        
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