1. Classification techniques used 
Unsupervised classification and classification with human assistance 
are used in this study. The LANDSAT multispectral data are first analysed by 
an unsupervised classification. Then several test zones are delineated in the 
image and the multispectral data in these zones are used as prior information 
for the classification with human assistance, the goal of which is to improve 
the classification result. 
a) Unsupervised classification 
The method used (DOTU and INSTALLE) (1) combines the histogram me thod 
and the ISODATA method and may be described by the following three steps. 
1) Each pixel is represented by a 4-dimensional vector the component 
of which is the measure in each spectral band. Since the measured values in 
these spectral bands are largely correlated, a Karhunen-Loeve transformation 
is first used in order to reduce the dimension from 4 to 2 (principal component 
analysis and the first two components the most important being retained). 
2) The 2-dimensional histogram of the transformed image is computed. 
This histogram visualizes the location of pixels in this new and reduced space 
(2 dimensions) and informs the number of pixels which have same spectral values 
in this space. A class appears as a grouping close to the maxima of the histo- 
gram. The unsupervised classification consists in realizing an optimal grouping 
in this histogram, each group corresponding to a class. 
3) An unsupervised classification (clustering) method based on the 
modification of the ISODATA method is used where each "pattern" is a point in 
the histogram, and the value of which represents a weighting factor. The following 
four points describe the detail of the algerithm : i) find the maxima of the 
histogram which are used as initial centers, ii) move the centers by use of the 
ISODATA method, modified by the weighting factors ; the distance used is the 
Euclidian distance, iii) then compute the intra-class distance. If it is large 
for a specific class, this class will be split in two; if it is small, this 
(1) H. DOTU and M. INSTALLE : A fast clustering procedure based on ISODATA 
algorithm with application to remote-sensing, Tech.Rep.,Feb. 78 (also 
appeared in a condensed form in the proceedings of the 4th Int. Joint 
Conf. on Pattern Rec., Kyoto, Nov. 7-10, 78). 
  
    
  
  
   
   
  
  
   
   
  
   
   
    
  
   
  
  
   
   
   
  
  
  
  
  
  
  
  
    
   
  
     
clas 
clas 
they 
ciou 
orde 
of c 
thes 
cent 
new 
the 
the 
this 
as w 
assi 
a li 
is v 
tanc 
dist 
dist