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Remote sensing for resources development and environmental management
Damen, M. C. J.

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).