2. The GIS has the capability of converting, LANDSAT data and other physical data rendered in 
vector or polygon modes into similar forms that could be very quickly and accurately compared. 
This is what developing countries need to overcome their development planning problems. 
3. The computer has the capacity to classify the terrain much faster than man throu- 
gh conventional means but can only do that on the basis of reflectance of surface cover or charac- 
teristics of the exposed surface. This introduces the problems of misinterpretation by the compu- 
ter in the case of soils which for the most part is covered by often unrelated vegetation types. 
4. The spatial resolution of the MSS data determines its ability to detect terrain features. Nar- 
row features are masked and are apparently poorly classified. The computer, in case of overwhel- 
ming surface cover such as in the savanna, best discriminates between well drained soils and poor- 
ly drained soils. All the soils in these two broad categories therefore tend to be grouped together 
as one unit, no matter their other intrinsic property differences. 
REFERENCES 
Condit, H. R. 1970, The spectral reflectance of American soils. Photogramm. Engineering 36: 
955 — 966. 
Elbersen, G.W.W. 1973. Interpretation of ERTS—MSS Images of a savanna area in eastern Colom- 
bia. 2nd Symposium on Significant Results obtained from ERTS—1 Vol. 1: 105 — 119. March 
5—9, 1973. Goddard space Flight Centre, Washington, D. C. 
ERDAS (Earth Resources Data Analysis Systems) 1982. User software package. 
Fagbami, A. A. 1978. The use of random stone count for the evaluation of physiographic analy- 
sis. ITC.Journ. 1978 — 3: 465 — 486. 
Fagbami, A. A. 1980. Interpretation of LANDSAT MSS imagery of the Nigerian Federal Capital 
Territory for soil survey purposes. Geoforum, Il: 71 — 84. 
Hinzel, E. J., R. À. Weismiller and D. P. Franzmeier, 1980. Correlation of spectral classes deriv ed 
from LANDSAT MSS data to Soil Series and soil conditions for Jasper County, Indiana. 
Kirschner, F. R., S. A. Kaminsky, R. A. Weismiller, H. R. Sinclair and E. J. Hinzel 1978. Map 
unit composition assessment using drainage classes defined by LANDSAT data. Sofi Sci. Soc. 
Amer, Proc. 42: 768 — 771. 
Kristof, S. J., M. F. Baumgarduer, A. E. Zachary and E. R. Stoner, Comparing soil boundaries 
delincated by digital analysis of multi-spectral scanner data from high and low spatial resolution 
systems, LARS publication No. 082477. Purdue University, West Lafayette, Indiana. 
Kristof, S. J., M. E. Baumgarduer, R. A. Weismiller and S. M. Davis. Application of Multispectral 
reflectance studies of soils Pre-LANDSAT LARS Technical Report No. 060280. Purdue Univer- 
sity, West Lafayette, Indiana. 
Lillesand, T. M. and R. W. Kieffer 1979. Remote sensing and image interpretation. John Wiley 
& Sons, N. Y. 
      
    
  
  
    
    
    
   
   
   
    
   
    
    
     
    
  
    
    
     
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