Manzul Kumar Hazarika 
  
3 METHODOLOGY 
3.1 Data Processing 
Satellite data are corrected geometrically, using Ground Control Points (GCP) taken form topographic maps (Scale 
1:50,000). A first order polynomial transformation equation has been used to rectify the data set. 
32 Identification of Road Characteristics in Different Backgrounds 
Road sections with various backgrounds have been considered in study. False Colour Composite of the multispectral 
data and intensity image panchromatic data are used for investigating the road characteristics. 
3.3 Estimation of Road Width 
Road width is estimated using analog and digital methods. In analog method, each of the geometrically corrected 
images from different sensors is printed in a hardcopy and widths of roads are estimated from the actual measurements 
made on the hardcopies. SPIN-2 is printed at a scale 1:8,000 whereas ADEOS Panchromatic, SPOT Panchromatic, 
ADEOS Multispectral and LANDSAT TM data are printed at a scale of 1:20,000. These scales are found to be most 
appropriate, because pixels of the roads are not shown individually in the hard copy. A road can be measured up to an 
accuracy of 0.25 mm on a hardcopy image, using a ruler. Field survey was conducted to find out the actual width of the 
road sections for verification of results. The measured width includes both the pavements and shoulders of the road and 
median strip, in case of roads having more than one lane. 
In digital method, numbers of pixels are counted in the perpendicular direction of a road and width of the road is 
estimated by multiplying pixel numbers with the pixel size. However, there are certain difficulties in counting numbers 
of pixels perpendicular to a road. Mixed pixels exist on the edge of a road and, in such cases, it is not an easy task to 
find out an accurate width of the road. This is more critical in low-resolution data. 
4 RESULTS AND DISCUSSIONS 
4.1 Road Passing Through a Water Body 
Clarity of a road depends on its background. Figure 1 shows a road (35m in width), passing through a water body, 
contaminated with molasses, in different sensors. 
ADEOS Panchromatic SPOT Panchromatic ADEOS Multispectral LANDSAT TM 
À 
  
  
      
  
  
  
  
  
  
  
  
  
  
Figure 1 A section of road passing through a water body 
In ADEOS AVNIR Panchromatic data, the background is very bright in the portion of the tank where water is dried out 
and, however, road can be seen distinctly. On the other hand, the portion of the tank, where contaminated water is 
available, appeared very dark and the road can also be seen clearly. In this case, molasses absorbs most of the energy 
whereas reflectance from the road is very high and thereby provides a very good contrast. In SPOT Panchromatic data, 
rainy season was just started and probably, therefore, dried out portion of the tank is not as bright as in the case of 
ADEOS data. This could not be confirmed due to unavailability of ground truth data at that instant of time. In ADEOS 
Multispectral data, the tank was full of water, therefore, the road appeared very bright against its background of dark 
contaminated water. LANDSAT TM data shows similar behaviour with ADEOS AVNIR Panchromatic data as both the 
images were acquired nearly in the same time of two different years. SPIN-2 data is not available for this area. 
  
368 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000.