IAPRS & SIS, Vol.34, Part 7, 
y? nl) — 
R49 
  
Fig. 1. InSAR viewing geometry 
For repeat pass interferometry, baseline and temporal 
decorrelation play an important role. Baseline decorrelation 
results from viewing the surface at two slightly different look 
angles and increases with increasing differential angle (baseline). 
For optimal system performance, the baseline must be large 
enough to give sufficient phase sensitivity to height yet small 
enough as to not introduce too much decorrelation noise. The 
second decorrelation i.e. temporal decorrelation occurs due to 
changes in the surface between different radar observations. This 
decorrelation increases with time on the scale of days. 
3. STUDY AREA 
The study area lies in the north of Alwar district of Rajasthan 
state in Western India located between 26° 35 to 26° 45 N 
latitude and 76° 35 to 76° 45 E longitude. It is characterized by 
plain to moderate relief with an elevation range of 200 m to 600 
m. The prominent cultural features include Shymak Reserved 
forest (RF), Kalakhora RF, Siliseri lake, Bahadurpur, Chikani, 
Alwar cities etc. 
4. DATA USED 
Single look complex (SLC) images obtained from ERS 1/2 
tandem mission was used to generate Interferometric outputs such 
as interferogram, coherence image, DEM and slope images. The 
date of acquisitions of these images were 03-05-96 and 04-05-96 
respectively for ERS 1 & 2. Differential GPS measurements were 
carried out for validating the DEM. IRS-1D Merged product, 
georefrenced with GCP’s established from GPS measurements, 
was used for geo referencing detected image (10 *2 averaged) and 
other interferometric products. 
“Resource and Environmental Monitoring”, Hyderabad, India, 2002 
5. METHODOLOGY 
5.1 Estimation of topographic height (DEM) and slope 
Topographic height, slope and other interferometric products such 
as amplitude image, interferogram, coherence image were 
generated using a fortran package named InSAR developed by a 
team in Signal and Image Processing Group (SIPG/RESA) at 
SAC (Padia et al 1998, 2000). It is a menu-based package 
involving following steps. 
5.2 Registration of Slave image with Master image 
Registration of Slave image with Master image involves two 
steps. One is the manual registration of two images by taking 
GCP's manually from the detected image with a pixel accuracy. 
For this a few points are identified on both the images and its 
average scan and pixel are taken. Next step is the sub pixel 
registration. In this step one image is fixed and other is 
interpolated to a 1/10 of a pixel. The Average Fluctuation 
Function (AFF) of the phase difference image is computed. The 
exact registration parameter is the one, which gives the minimum 
average fluctuation function. 
  
Fig. 2. ERS Amplitude Image 
5.3 Intereferogram generation 
After resampling using the estimated coarse and fractional 
registration parameters, the phase difference at each pixel is 
estimated using maximum likelihood estimator given by 
following equation 
® - tan! (Im (Z, A1 A2) / Re (En Ar A2)) (5 
     
  
    
   
  
  
  
   
    
   
  
  
   
    
     
   
    
  
  
  
  
   
  
   
   
   
  
  
   
  
    
   
    
     
  
     
    
  
    
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