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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

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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.

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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

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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.

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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.