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Figure 2. Test site 
3 METHOD 
In this study, Landsat TM images dated 12™ June 1984 and 18" July 1997 were used. First of all , boundaries of the 
area of study were determined by applying geometric correction to the satellite images. Then, correction analyses were 
made to the classification results by applying controlled and uncontrolled classification algorithms to the images and 
temporal changes were examined. 
3.1 Geometric Correction 
Geometric errors that can be corrected using sensor characteristics and ephemeris data include scan skew, mirror-scan 
velocity variance, panoramic distortion, platform velocity, and perspective geometry. Errors that can only be accounted 
for by the use of ground control points (GCP) include the roll, pitch, and yaw of the platform and/or the altitude 
variance (Bernstein, 1983). 
In the first stage of the study, satellite images were transformed into Universal Transverse Mercator (UTM) co-ordinate 
system by using 1/25000-scale standard topographic maps (Fig.3). In selecting the GCP’s to be used for 
transformation, care was shown in homogeneous distribution of the sharp points and net differentiation on the map and 
satellite image (roads, shores, etc.) and transformation equations were selected as a first-degree polynom. For the 
geometric transformation, cubic convolution method was used. Co-ordinate transformation was done with + 0.5 pixel 
root mean square (RMS). 
    
  
  
(a) (b) 
Figure 3: Satellite images of study area a) 1984 Landsat TM b) 1997 Landsat TM 
  
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000. 941