International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
hydrogeological unit and the polje, with a mean annual
discharge of 5m?/sec. The water is coming out from a large and
imposing cave with a tube like shape (karstic conduit). This
conduit connects the shallow holes and the spring. There are
two other springs (Fig.2,7, S2, S3) at the elevation between
600-800m with mean annual discharge «llit/sec (Dimadi,
1988).
4. DEM GENERATION AND ORTHO-RECTIFICATION
OF THE IMAGE
For the creation of DTM, two topographic maps, at scale
1:50,000 and in UTM projection, were used (Tsakiri, et al.,
2003). The image was orthorectified by using the generated
DTM and 25 control points. The accuracy of the
orthorectification was RMS=0,66 pixels.
5. SPECTRAL CONTENT INFORMATION
The six Landsats TM bands cover the visible region of
spectrum, VIS (TMI, TM2 and TM3) the near infrared, NIR
(TM4) and the middle infrared, MIR (TM5, TM7). In these
regions of spectrum the rocks have different spectral
characteristics. The MIR is characterized with high reflectance
values for most of the rocks at the spectral range covered by
TMS and by strong absorption features for clays and micas at
the TM7. Even if the TM bands do not allow precise
discrimination of the mineral content in soils or rocks, it may be
possible to detect some groups of minerals. The differences in
the reflection can be duc to the different lithological
composition of bared soils that is created for example from the
surface humidification of granite or micas chist slate. It is
obvious that the soil on micas chist contains more micas and
clays than soils on the granite with consequently the intense
absorption (Yésou, et al. 1993; Tsakiri et al., 2003).
The comparison of the NIR and VIS provides the bare soils and
vegetation discrimination. In the study area, the rocks are
marbles, which are constituted from calcite that approaches the
90%, dolomitic limestone with calcite in 8% and dolomite in
92% and granodiorites mainly with feldspars (intense
kaolinited) and quartz. As a result they have different spectral
signatures. It is known that the spectral signatures allow the
discrimination of the objects. The comparison of the bands in
the near infrared and in the visible region provides the
discrimination between the bare soil and the vegetation, as it is
well known.
6. VISUALIZATION OF BAND COMBINATION
The six TM bands provide 20 possible combinations per three,
for color display. To get an optimal color composite, the three
bands used, must have the minimum redundancy that is to have
the minimum correlation coefficient. Different ways exist to
determinate of most optimal combination, which can be or
empirical or statistical.
6.1 Empirical procedure
Three bands are selected based on their spectral characteristics.
It is the most commonly used technique. This technique
decreases the volume of possible combinations of bands. An
optical study based on the spectral parameters and on the
radiometric contrast of different color composition allows the
determination of best combinations in respect of information.
The combination TM5-4-2 allows the better perception of
geological structures and the TM7-4-3 provides good
discrimination between bare soil and vegetation. According to
the international bibliography, the combinations TM7-5-1,
TM7-5-4, TM4-3-1 and TM4-3-2 have poor contrast and do not
facilitate the discrimination of rocks (Yésou, et al., 1993).
These combinations for the imagery that was used in the present
work, gave images suitable for interpretation that proves that
the combinations arc not submitted in rules but they depend on
local characteristics (geology, geomorphology, vegetation). In
this study were used combinations from empiric methodology
depending on the area. For example, for the localization of the
granodiorite was used the combination TM7-5-1. More
frequency was used for the combination TM4-5-2 (Fig. 3).
Figure 3. 3D Visualization of Landsat TM image, over the
DEM, where: R=band4, G=band5 and B=band2.
gr: granodiorite, S1: spring Aggitis, S: shallowholes area,
WI: well
6.2 Statistical Procedure
The factor of most optimal index (Optimum Index Factor, OIF)
is computed which is based on the variance and the correlation
of bands. The Factor OIF is computed for each possible
combination of three bands. The band combination, that has the
bigger value in factor disposes, has the more information, and it
is calculated according to the function (1). In Table 2 the OIF is
presented for all the combinations of bands. In the third column
is presented the degree where smallest corresponds in the bigger
OIF and biggest in smallest.
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