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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
regarding the alteration of rocks. These conventional well-known
methods include color composite method, band rationing method,
principal component analysis and least squares fitting method.
ALTERATION MAPPING FLOWCHART
Remote sensing of the alteration products in volcanic rocks
of Hasandag - Melendiz volcanic complex
Use of conventional
alteration mapping
Use of spectral library data
Calculation of the descriptive statistics
of the reflectance data
Band Regression Y
r1 Rationing Defining the maximum and minimum values
for the band intervals
Color PCA
Composites [^ Analysis d
Band
Rationing
Calculation of the upper and lower limits
of the band ratios
Analysis of Landsat
I'M bands
Filtering the Landsat TM band ratios
according to the predefined limits
Image
Processing
Generalized
Alteration
Map
Detailed
Mineral Maps
Visual
Interpretation
Final
Alteration
Map
Figure 3. Flow chart of the study.
2.1.1 Color Compositing: Color composite method is simply the
decision of the order of bands to be displayed in red, green and
blue channels. The concept surely forms the basis of the other
methods. Methods are summarized in Table 1.
No image correction has been made prior to the processes. Images
that are selected to be displayed as a composite are normalize type
contrast stretched. Visually, normalized contrast enhancement
gives better results than linear contrast stretching. That is because
the stretching transformation is performed varyingly according to
the histogram density in normalizing contrast enhancement.
As it is clearly observed, the color composite method is a fast but
not that detailed enough to map the certain borders for alteration
types. Only general information is mapped. The procedure of
assigning the bands to the display channels is the same in the other
methods, changing the input bands to be displayed.
112 Band Rationing: Band rationing is the selection of the
bands, rationing to get the desired information and the meaningful
order of display of these ratios. Spectral characteristics of the
387
RGB display :
: : 1 Green ^
of resp Red corresp d Blue correspondent Extra
or
TM bands :
Structural lineament Hydrothermal
4:7:6 MT : à l'emperature contrast
> differentiation alteration
Hydrothermal alteration :
7:8:4 ” decis Gabbro Vegetation
and intrusives =
. ; Radiometric
Clay minerals are ; ; ;
7:4:2 ae, Vegetation correction is
brighter than the others ;
important
Clay mineral Clay minerals ar Radiometrie
. a erais i crais are
4:7:5 Vegetation e E
correction is
are brighter brighter
m important
Sedimentary
and volcanic
bluish-grey units are
Granites, FeO, MnO
7:4:2 displayed as reddish
brown areas
Monzogranite in | Sedimentary units in
grayish-green
separated
. ci > -
4:7:2 Background is pink Fel is yellow
green
4:7:3 Background is orange- | FeO is yellow-
red green
Table 1. Properties of some color composites.
minerals are used for deciding the pairs of bands to be rationed.
Prior to the process no correction has been made to the images
unless stated. Results are summarized in Table 2.
Band ratio technique is based on highlighting the spectral
differences that are unique to the materials being mapped. As the
resulting image will have ratios instead of grey levels, the image is
normalize contrast stretched to be able to display 256 grey levels.
RGB display of
; R
respective TM ed 1 Green Blue x Extra
band Ratióx corresp corresp corresp
Yellow, orange
5/7: 3/2 : M/S Clav-rich areas FeO rich areas areas both clay and
FeO rich
OH/ H»0-.
Minerals oH :
iius ; SO,- or CO-
7/4 : 4/3 : 8/7 containing iron | Vegetated zones
en P e bearing
tons
minerals
FcO as apricot
34:5:57 yellow and the
UE background as sky-
blue
t
5/7: 5/4 : 31 Clay minerals Iron minerals Ferric oxides |
| Highly altered zones
3/1:57 :4/5 dark-blue to violet-
blue
Table 2. Summary of band ratio composites.
2.1.3 Principal Component Analysis: The Principal Components
process uses the principal components transformation technique
for reducing dimensionality of correlated multispectral data. The
technique is used widely with a few to many correlated rasters to
create a lesser number of objects.
Information from six bands of thematic mapper (TM) imagery is
transformed to three processed images that contain virtually all of
the variance from the set of input objects in this method. The three
output bands can be displayed simultaneously as components of
an RGB display, which is easier to interpret than the raw data.
Also, transformation sometimes enables you to see details that
were obscured in the raw data.
Reducing the number of spectral bands input for principal
component analysis ensures that certain materials will not be
mapped and increases the likelihood that others will be
unequivocally mapped into only one of the principal component
images. The methodology is called Crosta Technique. The method
does not require detailed knowledge of the spectral properties of
target materials; also no atmospheric or radiometric correction is
needed. PCA on raw, unstretched data is found to be effective in
all cases. Resulting images produced by PCA were judged and
found to be accurate in delineating alteration zones (Fig. 4).
