Ebrahim, Mostafa Abdel-Bary 
  
  
  
  
  
  
  
  
  
Image date 1992 1993 1998 
Band Bl B2 B3 Bl B2 B3 Bl B2 B3 
Min. value 55 60 40 65 60 50 40 30 30 
Max. value 135 130 100 140 150 130 85 105 80 
  
  
  
  
  
  
  
  
Table 1. The minimum and maximum values used for stretching image bands 
3.3 Vegetation Indices 
The ratio of near infrared and the red band of space imagery is sometimes referred to as the Simple 
Vegetation Index (SVI). The Normalized Difference Vegetation Indices (NDVI) is given by: 
NDVI=(IR-R)/(IR+R) 
In which: 
IR is the brightness of pixels in the near-infrared band (band 3 of SPOT XS, 7 of Lansat MSS and 4 of 
TM). 
R is the brightness of pixels in the near band (band 2 of SPOT XS, 5 of Lansat MSS and 3 of TM). 
Vegetated areas will generally yield high values for either index, because of their relatively high near- 
infrared reflectance and low visible reflectance. Rock and bare soil areas have larger visible reflectance than 
the near-infrared reflectance and result in vegetation indices less than zero or near zero. The NDVI is 
preferred to the SVI for global vegetation monitoring because it helps compensate for changing illumination 
conditions, surface slop, aspects and other extraneous factors [Lillesan& Kiefer (1994)]. In this study the 
NDVI is constructed and the resulting pixels with values greater than zero were considered as vegetated 
areas. The obtained images of NDVI are given for the test area in Plates 4, 5, and 6 for the images of 92, 95, and 98 
respectively. 
3.4 Image Classification 
In this step major emphasis was made on the identification and delineation of the new reclaimed areas using 
the information contents of the composite images. For visual interpretation, composite images were constructed 
and displayed in pseudo natural color, where band 2 was assigned to red, band 3 was assigned to green and band 1 was 
assigned to blue. Visual interpretation was carried out to give an indication of number of classes that can be 
discriminated on the image and possibility of distinguishing the reclaimed areas. Several tests were carried out in order 
to choose the optimum number of classes in the classified image. It found that 10 classes give reasonable results. The 
unsupervised classification was carried out to test the possibility of automatic discrimination of the new 
reclaimed areas. The obtained unsupervised classified images are given for the test area in Plates 7, 8, and 9 for 
the images of 92, 95, and 98 respectively. 
  
384 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000.