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38
CHAPTER 4
4.1 THE RADAR BACKSCATTERING COEFFICIENT
Radiometric calibration of the microwave data is essential to convert the processed
SAR data or images into measurements of radar back scatter of targets. The equation
used for computing the radar backscattering or return scattering coefficient (sigma
naught or σo) of sensor is generally associated to the SAR image brightness (beta
naught or βo) as follows:
σo = βo .sin (4.1)
where is the local incidence angle.
The return scattering coefficient 'σo' in decibels is given as
σo (dB) = 10log10 (σo) (4.2)
The radiometric calibration of the particular microwave image is mandatory in
measuring of backscattering values. The digital numbers (DN) of the pixels are used
to convert the SAR image into either betao image or sigmao image. Betao image
formation needs the DN values of image pixels and it does not require incident angles
of the pixels. Whereas the sigmao image formation is required the incident angles of
each image pixel and centre pixel. The digital number of a pixel can be calculated
from square root of squares of real and imaginary values of SLC (Single Look
Complex) data, if SLC data has been considered. The digital number of a pixel is
directly given if the level-2 data is considered. Calculation of backscattering
coefficient [119-121] is a primary and compulsory step in any microwave data
processing to analyze the target surface. This value depends on calibration constant,
which is available in metadata.
The RISAT-1 radar return scattering coefficient values of MRS data is evaluated
as follows
σo (dB) = βo (dB) + 10log10 [ sin(ip) / sin (ic)] (4.3)
where βo (dB) = 20log10(DN) - K (dB) (4.4)
'ip' is angle of incidence for a particular pixel
'ic ' is angle of incidence for center of the image
'K' is calibration constant of SAR image
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4.2.Data used
The central pixel of image is geographically situated in Andhrapradesh state, India.
This area is located in middle of the south India and the image center point is having a
latitude of 14.42 North and longitude of 77.72 East. The area under this SAR image
covers all the features like water, manmade structures, barren lands and agriculture
lands.
Table 4.1: Characteristics of RISAT-1 image data for measuring sigmao values
Operating Frequency 5.35 Giga Hertz
Band C - band
Angle of Incidence 36.616 o
Transmitting polarization H
Mode of the data MRS
Receiving polarization H and V
Height of receiver 541 kilometers
Repetition period 25 days
Pixel size (Spatialresolution) 18 m
Mode of travelling Descending
Look type Left
Mean Local Time 6 AM
4.3 BACKSCATTERING COEFFICIENTS OF RISAT-1
Table 4.2: Comparison of backscattering coefficient values
AREA
HH HV
BETA SIGMA GAMMA BETA SIGMA GAMMA
1
Water
-26.688 -26.528 -23.327 -30.711 -30.551 -29.144
-25.845 -25.682 -22.627 -23.242 -23.08 -25.461
-28.05 -27.887 -23.898 -24.005 -23.842 -27.489
-25.752 -25.591 -20.792 -30.108 -29.947 -28.679
-27.584 -27.594 -22.31 -21.596 -21.606 -25.656
Average -26.7838 -26.6564 -22.5908 -25.9324 -25.8052 -27.2858
40
2
Settlement
6.523 6.434 5.122 -21.239 -21.327 -19.217
7.744 7.657 3.889 -22.777 -22.863 -18.892
1.007 0.9222 0.922 -19.291 -19.376 -20.302
-2.043 -2.132 -3.464 -19.758 -19.847 -19.426
-1.776 -1.774 0.585 -17.964 -17.962 -20.163
Average 2.291 2.22144 1.4108 -20.2058 -20.275 -19.6
3
Agriculture
-9.988 -9.812 -10.92 -20.032 -19.857 -18.359
-6.698 -6.523 -8.863 -22.289 -22.114 -16.374
-12.797 -12.619 -11.947 -25.91 -25.732 -23.474
-11.478 -11.235 -13.153 -24.492 -24.249 -24.566
-13.858 -13.617 -12.46 -23.936 -23.696 -22.571
Average -10.9638 -10.7612 -11.4686 -23.3318 -23.1296 -21.0688
4
Barren land
-17.843 -17.59 -13.193 -22.386 -22.133 -23.173
-17.248 -16.998 -14.732 -26.304 -26.054 -26.285
-18.791 -18.533 -14.512 -19.14 -18.88 -17.761
-15.811 -15.842 -16.278 -24.032 -23.763 -23.573
-15.32 -15.058 -12.244 -18.342 -18.071 -21.038
Average -17.0026 -16.8042 -14.1918 -22.0408 -21.7802 -22.366
Fig.4.1: Comparison of betao, sigmao & gamma filtered values for HH polarization.
WATER
SETTELEMENT
AGRICULTURE
BARREN
-30 -20 -10 0 10
GAMMA
SIGMA
BETA
41
Fig.4.2: Comparison of betao, sigmao & gamma filtered values for HV polarization.
The back scattering values for man buildings (settlements) are high. It is due the
double bounce of the electromagnetic signals. Generally plain surfaces like water
bodies will give low back scattering values, it is because of no reflections from them.
It is shown in figure 4.1 and 4.2. HH linear polarization is more sensitive to surface
and double bounce and it is clearly differentiated in the figures.
Fig. 4.3: Comparison of incidence angle image, betao image, sigmao image & gamma
filtered image for HH polarization.
-30
-25
-20
-15
-10
-5
0WATER SETTELEMENT AGRICULTURE BARREN
BETA SIGMA GAMMA
42
Fig.4.4: Comparison of incidence angle image, betao image, sigmao image & gamma
filtered image for HV polarization.
Fig.4.5: Comparison of betao image, sigmao image & gamma filtered image for HH
polarization.
Fig.4.6: Comparison of betao image, sigmao image & gamma filtered image for HV polarization.
43
The medium resolution scan SAR mode data has been taken to generate and
analyze the back scattering phenomenon. In table 4.1, it is described about the data
that have been taken. The final incidence angle image which is calculated after all
arithmetic operations, betao image, sigmao image & gamma filtered image for HH
polarization are given in figure 4.3. The final incidence angle image which is
calculated after all arithmetic operations, betao image, sigmao image & gamma filtered
image for HV polarization are given in figure 4.4. The betao image, sigmao image &
gamma filtered image of HH polarization are given in figure 4.5. The betao image,
sigmao image & gamma filtered image of HV polarization are given in figure 4.6.
In table 4.2, the back scatter coefficient values for various textures like water,
settlement, agriculture and barren fields are listed.
Fig.4.7: Comparison of backscattering values for RISAT-1 polarizations.
Fig.4.8: Comparison of backscattering values for various land covers.
-30
-20
-10
0
10
WATER SETTLEMENTS AGRICULTURE BARREN
Sigm
a ova
lues
in d
B
HH(Blue) and HV (Red) polarizations
WATER SETTLEMENTS AGRICULTURE BARRENHH BETA -27.0109 1.6177 -12.8942 -17.52109091HH SIGMA -27.001 2.70252 -12.7952 -17.25790909HV BETA -28.0449 -20.2896 -21.5453 -20.31045455HV SIGMA -28.035 -20.2665 -21.4471 -20.019
-30-25-20-15-10
-505
σ oin
dB
Sigmao values for various features
44
Fig.4.9: Comparison of betao image, sigmao image & gamma filtered image for HH
polarization (Chitravathi Dam, Andhrapradesh, India)
Fig.4.10: Comparison of betao image, sigmao image & gamma filtered image for HV
polarization (Chitravathi Dam, Andhrapradesh, India)
The comparison of back scattering values for HH and HV polarizations are given
in figure 4.7 and 4.8 respectively. The betao image, sigmao image & gamma filtered
image of HH polarization are shown in figure 4.9. The betao image, sigmao image &
gamma filtered image of HV polarization are presented in figure 4.10. The betao
image and sigmao images are giving almost same response in both the polarizations.
That is the reason why in many of the cases both are treated as same, except in
sensitive applications like defense.
45
4.4 SUMMARY
The original picture of the scene is obtained by converting the GEOTIF of SAR
image in to either betao or sigmao image. The betao and sigmao values for various
SAR images are analyzed. The back scattering coefficient values of various futures
like water, manmade structures, agriculture lands and barren lands are verified. The
betao and sigmao values are compared. Both the values are very nearby. Because of
this reason, the betao images are considered in this research work for analyzing the
despeckling methods. Generally, the values of both the betao and sigmao images are
almost same except at particular incident angles. This process has been done with
(Environment for Visualizing Images) ENVI software. The Gamma Map filter is also
checked on speckled images. It has been considered to differentiate the betao and
sigmao images to despeckled images.
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