Full text: Remote sensing for resources development and environmental management (Volume 1)

5 CONCLUSION 
This paper has described how the processing of 
Landsat MSS data using the VAX computer and the 
Tektronix Ink Jet Plotter, and subsequent comparison 
of the results in hard copy format with ground 
truths, can achieve a considerable improvement over 
conventional image processing methods in terms of 
delineation. Small subscenes (40x40 pixels) were 
manually processed and plotted in single bands or 
combinations of different bands. The technique 
demonstrated that even Landsat MSS data can be used 
to classify small scale geological features. 
Overall, the study showed that the vegetation index 
is not a suitable tool for use over an extensive 
area of relief for the delineation of vegetation. 
The main reason is that the index tends to classify 
shadows as vegetation, leading to errors in the 
final result. However, the lower values in the 
vegetation index histogram proved useful for the 
identification of landslides and screes which are 
hazardous to the Haraz Road. Table 1 shows a 
quantitative analysis of the capability of different 
combinations of the bands for an unsupervised 
vegetation classification. 
Supervised classification was carried out by 
selecting certain training areas and using their 
pixel values to classify the subscenes (Table 2). 
The separation of different features is shown in 
Figure 6 which enables the investigator to carry out 
a supervised classification of the area. As can be 
seen in Table 3 each combination is most suitable 
for the classification of one specific feature. As 
result the subscene was classified employing three 
combinations as shown in Figure 5. By this method 
only a small portion of the subscene was 
misclassified or was not classified. Ground cell 
resolution and topographic effects were two major 
difficulties in obtaining optimum results. 
The method devised can be used for classification of 
a bigger area, even an entire scene of a Landsat 
image. Vegetation which appears on Landsat MSS 
imagery can be classified more accurately than by 
conventional classification techniques. Some 
geological features were located very precisely, for 
example landslides and screes which generally cannot 
be observed on a false colour composite were also 
delineated ( see Figure 5).
	        
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