Full text: Proceedings of the international symposium on remote sensing for observation and inventory of earth resources and the endangered environment (Volume 1)

   
    
  
    
   
  
   
  
   
  
  
  
  
   
  
  
  
   
   
   
   
  
  
  
     
   
  
  
  
  
  
  
  
  
  
  
   
  
   
  
    
of tonal and textural. variables at the three scales were further 
analysed. Linear discriminant analysis was again carried out on 
the data by combining the two sets of corn (cut corn and uncut 
corn) as one group. Pairwise linear discriminant scores were also 
obtained for the more significant variables (as determined earlier) 
and their suitable combinations. 
Summary of Results and Discussions 
  
The above analysis enabled testing of the effectiveness of each 
variable and their combinations to further evaluate the relative 
contribution of each variable marginally under different combi- 
nation of crop types. Utility of texture as a supplement to tone 
under these varied conditions could thus be evaluated. 
The discriminant scores as a result of the discriminant analyses 
carried out (for all 5 crop types) are summarised in Table 3. 
Table 3 
Summary of Percentage of Successful Scores Using Tone/Texture 
at Three Scales 
  
  
Scale Tone Texture Tone+Tex. Tone+Tex. Tone+Texture 
only only (Linear) (Quad. ) (All three scales) 
(Linear) (Quad.) 
Small 42$ 43$ 2% $ 
Medium 45$ 45$ $ 2 80$ 66$ 
Large 49$ % 69% $ 
  
The table clearly illustrates that by combining tone and texture 
at any of the three scales, success of discrimination improves 
very significantly. It also shows that by using all the three 
scales, still better success is obtained. An optimum scale for 
best discrimination is noticeable. As these optimums for tone 
and texture are not the same, the improvement in success by use 
of more than one scale is further explained. 
Summary of results for various combinations of the six variables 
is given in Table 4 for both cases i.e. with all five crops and 
with four crop types (the two corn states merged into one crop 
type). 
Table 4 illustrates that: 
a) there is a marked improvement in overall success by aggregating 
the corn category into a single category; 
b) use of texture in addition to tone and use of more than one 
scale of photographs should contribute to significantly better 
success of classification; 
c) the combined use of the four variables of tone and texture at 
medium and large scale provide the best results. 
Lastly , the role of texture and tone for pairwise discrimination 
is summarised in Table 5. This supportive role of texture in the
	        
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