Table 3 Comparison of different estimators of area under wheat 
for district Rohtak during Rabi season, 1995-96 ('000 ha) 
6. CONCLUSIONS 
The aim of this study was to explore the advantage of using 
GIS and remote sensing technologies in sampling of spatial 
data. The results of the study points out that more efficient, 
stable and reliable area estimates could be obtained and thus 
spatial surveys could be substantially improved by employing 
computer-intensive techniques of GIS. These estimates could 
be further improved by integrating remote sensing parameter 
along with GIS. 
7. REFERENCES 
Arbia, G. 1993. The use of GIS in spatial statistical surveys. 
Int. Stat. Rev., 61(2), pp, 339-359. 
Brunsdon, C., Fotheringham, S. and Martin, C. 1998. 
Geographically weighted regression-modeling spatial non- 
stationarity. Statistician, 47 (3), pp. 431-443. 
Moran,P.A.P. 1950. Notes on continuous stochastic 
phenomena. Biometrika, 37, pp, 17. 
Raj, D. 1956. Some estimators in sampling with varying 
probabilities without replacement. J. Amer. Stat. Assoc., 51, 
pp. 269-284. 
IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring", Hyderabad, India, 2002 
    
  
  
  
  
  
Ester Area under wheat Relative 
(‘000ha) Bias (%) 
Remote Sensing 137.01 2.97 
Technique 
Stratified 139.76 1.02 
CUBBS 
True value 141.20 =