The image of the Bosphorus(Fig.5) has been formed by
the Thermal Band. This image clearly displays the
temperature differences. As seen in the image, the cold
water coming down from the Black Sea mixes with the
warmer water of the Marmara Sea causing turbulence.
When the image is zoomed, the light blue zones
representing the increasing temperature of the waste
water discharge locations of the Bosphorus and the
Golden Horn are visible. It can also be observed that
Black Sea water is dominant in Bosphorus and that it
flows into the Marmara Sea. Fig 6A and Fig 6B show
the increased turbidity distribution in the Bosphorus and
the Golden Horn depending to the years.
4.CONCLUSION REMARKS
This study demonstrates that the hydrodynamic-
condition water pollution in the Bosphorus is quite
complex in nature. It may be appropriate to investigate
this pollution by processing the digital images taken from
data in conjunction with the help of the conceptional
methods of remote sensing. The very important
environmental problem of water pollution can be
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158
examined by processing and classifying the satellite
data. As the remote sensing method permits large
regions of the environment to be studied, the pollution
problems can be determined both
quickly and correctly. When conceptions of the final
images taken from Landsat-5 TM and Spot data are
compared with the water quality reference data, it can
be observed that both residential and industrial
discharges are correctly displayed on Stellite imagery.
These observed reflectance shows a strong relationship
with the suspended solids, chemical oxygen demand,
and with humic materials and polyaromatic
hydrocarbons. Satellite data provide a useful index of
TSS, HM and PAH. As the reflectance (in the turbidity
area) in the longer red and near IR wavelength increases
faster than the reflectance in shorter blue and green
wave lengths, it can be seen that turbidity levels are
positively related to reflectance.
The relationship between the water quality parameters
and the individual band reflectance are supported by
simple linear regression analysis.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B7. Vienna 1996
