JAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India, 2002 
  
  
of sampling location in terms of soil moisture, size and surface 
roughness. . 
5.2 Ground truth collection 
A ground truth data collection was done in synchronous with 
the RADARSAT pass. The information gathered during ground 
truth data collection consists of soil samples with the help 
of 
  
Figure 2. Instruments used for collecting soil samples. 
auger and core sampler for the measurement of gravimetric soil 
moisture, bulk density of the soil, field capacity of the soil and 
wilting point of soil samples. Figure 2 shows the various 
instruments used to collect soil samples. Along with soil 
samples other associated field conditions have also been 
recorded. Fresh weight of soil samples were noted and they 
were oven dried for 24 hours at 105? C temperature. Figure 3 
shows the soil samples in side the oven equipped with 
thermostat. 
  
Figure 3. Fresh soil samples inside the Oven. 
The dried samples were weighed once again for dry weight. 
With the help of fresh weight and dry weight for each of the 
fields, gravimetric soil moisture has been calculated. 
Gravimetric soil moisture was then converted to volumetric soil 
moisture by multiplying the gravimetric soil moisture of a 
sample with the bulk density of that sample. Bulk density was 
calculated using a 100 cc of undisturbed soil sample taken with 
the help of a core sampler. 
5.3 Calculation of available water of soil samples 
In this study available water refers to the difference of soil 
moisture at field capacity and at wilting point. For this reason 
field capacity and wilting point of all the soil samples have 
been estimated with the help of pressure plate instrument 
(Figure 4). This instrument was used to calculate the soil 
moisture of all the samples at 1/3 bar pressure for field capacity 
and at 15-bar pressure for wilting point 
  
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Figure 4. Pressure plate instrument used for the calculation of 
available water in soil samples. 
Conversion of soil moisture values into percentage of field 
capacity was done using the following equation: 
SM g ı/3bar = (SM oss * 100) / SM i555. (2) 
where SM jy, — Soil moisture in percentage of field 
capacity 
SM ops = Observed soil moisture from field 
SM 1/3bar = Soil moisture at field capacity 
Soil moisture in percentage of available water has been 
calculated by representing soil moisture in terms of (SM /3par — 
SM 15bar), the difference of soil moisture at field capacity and at 
wilting point. Following equation has been used for this 
purpose. 
5.4 Radiometric calibration of RADARSAT-1 SAR 
RADARSAT-1 SAR data supplied from CCRS includes the 
scaling in terms of gain and offset, to ensure optimum 
utilization of the available dynamic range. The scaling used can 
vary for each scene, making it difficult to directly relate 
information between scenes. Hence for any quantitative 
analysis, it is necessary to convert the image data to calibrated 
radar backscatter (Sigma naught). Due to this reason 
RADARSAT-1 EL1 SAR data was radio metrically calibrated 
using the Equation 3. 
oo 10*log((DN? + offset)/gain)+10*log(sin (a) (3) 
where | DN - Digital number of SAR image 
À = local incidence angle 
The header information was used for calculation of o, the local 
incidence angle at each pixel. These conversions yielded a 32- 
bit real image, which is radio metrically, calibrated. These 
operations have been done using EASI/PACE image processing 
software. 
5.5 Speckle suppression and data compression 
After conversion of DN to 0°, Speckle suppression was carried 
out using Enhanced Lee-filtering algorithm (Lee, 1986). Owing