districts. In these districts the other dominating crop is 
sugarcane during the season and due to the 188 m ground 
resolution of WiFS, the NDVI profile contained the combined 
response of wheat and sugarcane crops. These two districts 
were dropped from further analysis which resulted in an 
increase in correlation coefficient from 0.81 to 0.93 (Figure 3). 
The difference between TO and computed DOS ranged from 4 
to 16 days with a mean value of 11 days. 
  
KARNAL DISTRICT 
  
0.6 
0:5 
+04 
SIMULATED LAI 
o 
w 
NDVI (PROFILE FIT) 
  
  
  
  
  
+ 0.1 
— — -NDVIPROFILE 
0.5 ; + r 0 
15 25 35 45 55 65 
DAY OF YEAR (2001) 
  
  
Figure 2. An illustration for obtaining date of sowing (DOS) for 
Karnal district by matching date of simulated LAI 
peak with date of fitted NDVI profile peak (Tmax). 
Different simulated LAI curves correspond to 
various dates of sowing (320 to 350) in year 2000. 
  
365 7 
y = 0.5823x + 134.76 
360 | 20.93 
355 - 25: fine 
350 4 
345 - 
340 4 
335 - 
330 4 
Computed Date of Sowing (Julian day) 
  
  
325 
  
325 335 345 355 365 
  
  
Spectral Emergence Date TO (Julian day) 
  
Figure 3. Comparison of RS-derived spectral emergence date 
TO and CGMS derived date of sowing for 14 
districts in Haryana for 2000-01 crop season. 
The CGMS was run under three different scenarios of crop 
management input specification as described in methodology 
section. Under all the scenarios, CGMS generated grid-wise 
daily outputs of crop growth and development parameters 
which were visualized in GIS as maps. The spatial variability of 
these parameters captured by CGMS is summarized in Table 4. 
IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India,2002 
     
For all the parameters, variability captured under scenario-3 
was highest followed by that under scenario-2. Under scenario- 
1 the spatial variability captured is the result of variations in 
weather and soil characteristics only, whereas, under scenario-2 
and scenario-3, the spatial variability captured is due to the 
variations in management practices besides variations in 
weather and soil. The variability captured by CGMS in grain 
yield across the State under scenario-3 is shown in Figure 5. 
  
  
  
  
SCENARIO PARAMETERS RANGE MEAN 
SCENARIO-1 ANTHD (days) 85 —97 90.50 
GFD (days) 27-33 29.84 
LAI ANT 3.58 — 4.46 3.89 
TDM (t/ha) 779-1056. 939 
YLD (t/ha) 3.29 — 4.86 4.06 
SCENARIO-2 ANTHD (days) 81-97 87.75 
GFD (days) 25-33 28.42 
LAI ANT 3.73 — 4.53 3.95 
TDM (t/ha) 6.89 — 10.12 849 
YLD (t/ha) 2.80 — 4.67 3.72 
SCENARIO-3 ANTHD (days) 80 — 99 87.43 
GFD (days) 25 — 33 28.39 
LAL ANT 2.78 — 5.05 3.88 
TDM (t/ha) 633-1183 . 842 
YLD (t/ha) 2.80 — 5.48 3.69 
  
ANTHD: Pre-anthesis duration; GFD: Post-anthesis duration; 
LAI_ANT: LAI at anthesis; TDM: Above ground total dry 
matter; YLD: Grain yield 
Table 4: Range and mean of grid-wise simulated crop growth 
and development parameters under three scenarios 
of input specification for Haryana (2000-01 season). 
  
74°30E 75°E 75°30'E 76°E 76°30'E 77°E 77°30E 78°E 
| 1 1 ] 1 L 1 | 
  
  
N,0£,272 No8Z  N,O£,82  Ne6Z  N,0O£,62  NoO€  N,O£,0€ 
Haryana (2000-61) 
R$-DOS, N Fortilizor 
27*30'N 28?N .228"30'N 299?N  29*30'N 309N "30°30'N  319N 
  
  
  
T | I I | | I 
74*30E 7S5'E 75*3UE 76°E 76°30E 77°E 77*30'E 
Wheat Yield (t/ha) 
  
+ 
28 35 42 48 55 
  
  
  
Figure 5. The wheat yield map generated by CGMS framework 
for 14 districts of Haryana when RS-derived DOS 
and N fertilizer at district level were used as inputs.