Apr 12, 2023

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Polarimetric SAR Data Processing Software: PolSDP

Shaunak DeCentre of Studies In Resources Engineering – IIT Bombay

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PolSDP Main Interface

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Export RISAT-1 Data

• Supports export of Level 1 and Level 2 CEOS data

• Covariance Matrix

• Radar Backstatter• Decibel (0 db )• Linear scale (0 linear )

• C2 and 0 Calibrated

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Export RISAT-1 Data (cont)

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Export RISAT-1 Data (cont)

• Input Product Directory• Sub-Directories and Files will be detected

Automatically• Output Directory• Exported products will be placed here

Multilook Factor and other information displayed hereLeader files, Scenes, Data Files, Grid

Files, Meta Files are listed here

• Enter the desired Range multilook• Azimuth multilook is automatically

calculated

Choose the desired outputs and click “Run”

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Export to C2 Matrix

𝐶 2=[ ⟨𝐸𝐻𝐶𝐸𝐻𝐶∗ ⟩ ⟨𝐸𝐻𝐶𝐸𝑉𝐶

∗ ⟩⟨𝐸𝑉𝐶𝐸𝐻𝐶

∗ ⟩ ⟨𝐸𝑉𝐶𝐸𝑉𝐶∗ ⟩ ]

• Two channel data – i.e. RH and RV

• Supplied as I,Q (complex) 16 bit integer values

• After conversion to float C2 is calculated:

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Export to C2 Matrix (cont)

RGB Color Composition 2Blue = C22 Green = C11 +2 Re(C12) + C22 Red = C11

RGB Color Composition 1 Blue = C11 Green = C11 +2 Re(C12) + C22 Red= C22

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Backscatter ( 0 ) Calculation• The “I” and “Q” values for each pixel are

supplied as 16 bit integers• Converted to complex floating point• Radiometric correction of data• The calibration constant (KdB) is supplied

Here:

RH 0 (db) - Mumbai

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RISAT-1 Calibration

Decibel Scale

Linear Scale

This must then be normalized around the center incidence angle:

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Speckle Filtering

3

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3

Speckle Filtering (cont)

• Select filter type to be applied:• Boxcar Filter• Refined Lee Filter

Select Filter Size

Set the input and output directories

Click Run to apply filter

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Speckle Filtering Comparison

Unfiltered 5x5 Refined Lee Filtered

Crop of cFRS-1 mode acquired over Mumbai by RISAT - 1

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Hybrid Polarimetric Decomposition

m-delta () Decomposition:

)1(

2

sin1

2

sin1

0

0

0

mSfG

mSfR

mSfB

diffused

even

odd

m-chi () Decomposition:

)1(

2

2sin1

2

2sin1

0

0

0

mSfG

mSfR

mSfB

diffused

even

odd

m-alpha () Decomposition:

)1(

2

2cos1

2

2cos1

0

0

0

mSfG

mSfR

mSfB

volume

dihedral

surface

Cloude, et al., IEEE GRS Letters, 9(1), Jan 2012Raney et al., JGR, Vol. 117, E00H21, 2012

Stokes Parameters: (RH-RV Case, BSA Convention)

0

23

22

2

1

S

SSSm

2

31tan(deg)S

S

0

32sinmS

S

Degree of Polarization: Relative RH-RV Phase:

Degree of Circularity:

3

22

211tan

2

1(deg)

S

SSScattering mechanism:

Stokes Vector: (RH-RV Case) - BSA

22

1

22

0

RVRHS

RVRHS

*

3

*2

2

2

RVRHS

RVRHS

Indicator of polarized and diffused scattering; Related to Entropy

δ Sensitive indicator of Double Bounce

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Hybrid Polarimetric Decomposition (cont)

Decomposition techniques applied to cFRS-1 Image acquired over Mumbai by RISAT-1

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Conversion To Pseudo Quad Pol

• Ratio of the Same Sense toOpposite Sense echo powers

• Indicator of the degreeof wavelength scale surface and/or near subsurface roughness

CPR =

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Conversion To Pseudo Quad Pol

11 11 22 12

13 11 22 12

22 11 22 12

31 11 22 12

33 11 22 12

7 2 Im

6

2Im

6

7 2Im

C J J J

C J J j J

C J J J

C J J j J

C J J J

CP

CP

CC

C

CC

C

3331

22

1311

0

00

0

Where :

Reflection and Rotation symmetry assumptions

2221

1211*)2/()2/(2/ 2

1*

JJ

JJkkJ

T

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Conversion To Pseudo Quad Pol (cont)

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Conversion To Pseudo Quad Pol (cont)

Set Input DirectorySet Output Directory

Run the process

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Geocoding• Correspondence between:

– position of points on the final image – location in a given cartographic projection

• Affine transformation

• Intensity Interpolation• Bilinear

Reference: Gunter Schreier(Ed.) SAR Geocoding Data and Systems (Publisher: Wichman)

𝑃𝑣=

∑ ( 𝑍𝑘

𝐷𝑘❑2 )

∑ ( 1𝐷𝑘❑

2 )• Nearest Neighbor

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Geocoding (cont)

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Geocoding (cont)

Select the file to be geocodedAny floating point bin file is supportedProvide the “infoRH.txt” file

This is in the directory where the product was extracted

Choose the resampling method Run the process

Output will be automatically opened in OpenEV

S-Curve Stretching gives good visualization

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Geocoding (cont)Geocoded C11 image of Mumbai, India

Acquired by RISAT-1 in cFRS-1 mode

15-NOV-2012

Scene CenterLongitude:72.930005Latitude :19.220882

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Comparison of Decomposition TechniquesALOS L Band – Fully Polarimetric Image is used for this comparison

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Comparison of Decomposition Techniques

Pauli RGB Freeman 3 component

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Comparison of Decomposition Techniques

VanZyl 3 component Yamaguchi 3 component

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Comparison of Decomposition Techniques

Arii ANNED 3 component Arii NNED 3 component

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Comparison of Decomposition Techniques

Y4O Y4R

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Comparison of Decomposition Techniques

G4U1 G4U2

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Comparison of Decomposition Techniques

S4R Y4R

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RISAT – 1 Data AnalysisClassified image of cFRS-1 scene acquired over Mumbai, India.

Urban Forest Mangroves Water Wetland

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Comparison of Classification

Sensors Band Polarization PixelSize (m)

RISAT-1 C Hybrid Pol 2.5

RADARSAT-2 C Full Pol 8.0

ALOS-PALSAR L Full Pol 24.0

TerraSAR-X X HH and HV 3.0

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Comparison of Classification (cont)Classifier Wishart Classifier

Classes TerraSAR-X band Dual Pol.

RISAT-1-C band Compact Pol

RADARSAT-C band simulated

Compact PolRADARSAT-C band Full Pol.

ALOS-PALSAR-L band Full Pol.

Water 99.66 81.03 100 100 87.94

Mangroves 74.93 88.06 77.49 89.86 91.78

Urban 98.17 91.53 97.03 98.63 100

Forest 60.26 81.00 77.42 82.19 93.49

Saltpan 63.77 68.6 95.89 96.38 85.99

Wetland 89.96 89.96 97.77 97.54 73.44

Grassland 83.78 90.54 85.59 92.34 90.54

Accuracy % 81.84 83.40 89.96 93.40 89.38

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Comparison of Classification (cont)

ALOS-PALSAR RADARSAT-2 TerraSAR-X RADARSAT-2 RISAT-1 Full pol Full Pol Dual Pol Simulated Hyb. Hyb.pol

Water Mangroves Urban Forest Saltpans Wetland Grassland

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Classification – Simulated v/s Actual Hybrid

Sensors Band Polarization PixelSize (m)

RISAT-1 C Hybrid Pol 2.5

RADARSAT-2 C Full Pol 8.0

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Classification – Simulated v/s Actual Hybrid

Class

RISAT-I RADARSAT-2

Wishart m-δ,CPR,SPAN (SVM)

m-χ, CPR,SPAN

(SVM)Wishart m-δ,CPR-

SPAN (SVM)

m-χ, CPR,SPAN

(SVM)

Water 78.59 84.32 84.00 99.95 98.91 99.05

Mangroves 60.60 88.92 88.99 75.25 71.85 70.72

Urban 56.74 60.99 63.43 91.73 92.06 92.25

Forest 56.15 81.54 81.54 52.87 54.94 56.88

Wetland 60.22 84.22 84.78 97.09 97.75 98.26

Overall Acc.% 64.17 81.53 81.86 81.35 80.68 80.91

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Classified Image

Classified RISAT-1 image acquired over Mumbai in cFRS-1 mode.

SVM classifier used on m- decomposed image along with SPAN and CPR

Urban Forest Mangroves Water Wetland

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Classification – Hybrid v/s Full Pol

Sensors Band Polarization PixelSize (m)

RISAT-1 C Hybrid Pol 2.5

RADARSAT-2 C Full Pol 8.0

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Linear and Hybrid pol σ0 (Mumbai)Variation of H/AlphaMean and Standard Deviation of σ0

• Urban features: hybrid σ0 shows higher value with more standard deviation• Urban features can be clearly discriminated • The other features are not discriminable – low dynamic range (within 3dB) • Channel Imbalance observed

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Hybrid Pol v/s Full Pol – Mumbai Data

Linear PolFCC RGB

Hybrid PolFCC RGB

Lin

ear

Com

plex

L

inea

r In

tens

ity

Hyb

rid

Com

plex

H

ybri

d In

tens

ity

UrbanWaterForestMangrovesWetland

Field Work

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Hybrid Pol v/s Full Pol – Mumbai Data

Polarization/Class

Linear(HH,HV)Intensity

Circular(RH,RV)Intensity

Linear(HH, HV)Complex

Circular(RH,RV)Complex

Urban 70.77 85.27 70.68 82.50

Forest 73.50 52.95 78.85 87.41

Water 95.19 99.45 94.99 99.83

Mangroves 80.09 59.78 82.88 91.74

Wetland 62.57 91.55 73.11 98.24

Accuracy(%)

83.48 79.60 86.38 91.79

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Signature Analysis – Urban TargetRADARSAT-2 RISAT-1

Urban_Copol

Urban_Crospol

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Signature Analysis - WaterRADARSAT-2 RISAT-1

Water_Copol

Water_crosspol

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RISAT-1 Soil Moisture Analysis

Saoner Test Site

• Scene center:• 21°23′09″N Latitude• 78°55′12″E Longitude

• Major Crops:• Paddy• Sugarcane• Wheat• Gram

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RISAT-1 Soil Moisture Analysis (cont)

0%

57.5%

0%

41.4%

m-delta m-chi m-alpha

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Thank You!