PolSDP - 29May13
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Apr 12, 2023
1
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!