b) Training area evaluation 
The multi-spectral information of each training area vill be 
displayed as shown on Fig.7. Trainees can check the 
separability of each items at each spectral band. If the 
separability of each items are not clear, trainees have to 
select better training area again. 
  
E 5; 
  
  
  
  
se THRESHOLD ++ 3 127 
- 
>> CATEGORIES << BAND4 - 
BI Forest 
u 127 
B Plant = 
Wl suburban BANDS À -— 
M Urban 
9 127 
M water =" 
Bl Reclaimed BANDS | = -— 
SEMI 127 
whe 
um 
  
  
  
S T 
Fig.7 Spectral Characteristics of Training Area 
c) Classification 
Based on the training data selected by the trainee, the multi 
spectral classification(minimum distance classification) will 
be performed. The trainee can compare his classification 
result with the optimal classification result already prepared 
by ENDIPS-T, and can repeat classification procedure. Through 
this try and error process, the trainee can understand the 
technique of classification. 
4) Geometric Correction 
Trainees are required to select GCP by comparing the ground 
pattern of the two remotely sensed data taken at different time. 
Geometric correction is automatically applied to the data by 
using the GCP data. Trainees can compare and check the 
registration accuracy of original image and geometric corrected 
image by flickering the both image on the display. 
5. Conclusion 
As described above, ENDIPS-T allow beginners to understand basic 
ideas of digital image processing and smoothly forward them to 
the training of real remotely sensed data analysis. The 
characteristics of ENDIPS-T can be summarized as follows. 
50