第520回 URSI-F会合資料
開催日：2007年12月14日(金)場所：情報通信研究機構

POLSAR画像解析を基とした
新潟県中越地震の被災住宅の検出
佐藤亮一* 山口芳雄 山田寛喜
新潟大学

Introduction
The Mid Niigata Prefecture Earthquake- October 23, 2004
M6.8
- Large scale landslides at several stricken area
- Unexpected secondary disasters due to the landslides
Higashi-Takezawa, Yamakoshi (山古志村・東竹沢)

Copyright©1998-2006 NTT DATA CORPOLATION

Copyright©1998-2006 NTT DATA CORPOLATION*We express our sincere appreciations to Prof. Makino and NTT data for providing these high resolution photos.

1

Introduction
Yamakoshi village(山古志村)
Tanesuhara
種苧原Terano
寺野

POLSAR image analysis
Airborne POLSAR (Pi-SAR**)

Scattered power

Informationof polarization

Observation of stricken area
in mountainous region“Yamakoshi village”**We would like to thank NiCT and JAXA for providing valuable Pi-SAR data sets.

2

Hybrid classification method
I. Power decomposition
Total power=+Surface scattering+Double-bounce scattering Volume scattering+

Helix scattering

II. Correlation coefficient*
S XY S AB

γ XY − AB = Cor ( XY , AB) =*S XY S XY*S AB S AB- ⋅ : ensemble average- X,Y,A,B are basis elements

Classification method IPower decomposition[C ] = f s ⋅ [C ]surface + f d ⋅ [C ]double + f v ⋅ [C ] volume + f c ⋅ [C ] helix

Total power=+Surface scattering⎡β⎢[C ]surface = ⎢ 02

⎢ β*
⎣0 β⎤
⎥0 0⎥
0 1⎥
⎦

Based on “physical mechanism”++ Helix scattering

Double-bounce scattering Volume scattering⎡1[C ]double = ⎢⎢ 0⎢α⎣α* ⎤⎥
0 0 ⎥20 α ⎥⎦0⎡3 0 1 ⎤[C ] volume = 1 ⎢⎢0 2 0⎥⎥8⎣⎢1 0 3⎦⎥⎡

1

[C ] helix = ⎢⎢m j 2⎢ −1⎣±j 22mj 2−1 ⎤⎥± j 2⎥
1 ⎥⎦P (θ ) = 1 / 2π

Useful marker for man-made targets

Right angle dihedral structure:
Vertical wall and the ground surface.

Ground3

Classification method IPower decomposition
Problem of ``Classification method I’’

Normal illumination
Strong Co-pol . scattering

Not normal illumination
X-pol. scattering

POLSARPOLSAR

Classification method II
Correlation coefficient
Assumption:- Residences = Man-made targets(There exist lots of ``Edges’’ on man-made targets)- “Edge” may be a source generating“Circular polarized scattering components”
a − b + j 2cj ( a + b) ⎤2 ⎣ j (a + b) b − a + j 2c ⎥⎦[S ( LR)] = 1 ⎡⎢[S ( HV )] = ⎡⎢ HHS⎣ SVHS HV ⎤ ⎡a c ⎤=SVV ⎥⎦ ⎢⎣ c b ⎥⎦S HV = SVH = c for back scattering- Particular polarimetric indices including X-component “c”
for accurate identification of man-made targets.

4

Classification method IICorrelation coefficient
Polarimetric correlation coefficient*S XY S AB

γ XY − AB = Cor ( XY , AB) =*S XY S XY*S AB S AB

- X,Y,A,B are basis elements- ⋅ : ensemble average

Co-pol. coefficients for three types of bases- HV basis (Linear polarization)- LR basis (Circular polarization)- XY basis with “45o rotation to HV basis”(Linear polarization)

Classification method IICorrelation coefficient
Co-pol. correlation coefficient for HV basis
γ HH −VV = Cor ( HH , VV ) =*S HH SVVS HH2SVV2ab*=a2b2

No X-polarized component
Unsuitable for man-made target classification?

Scattering matrix for HV basis

S[S ( HV )] = ⎡⎢ HH⎣ SVHS HV ⎤ ⎡a c ⎤=SVV ⎥⎦ ⎢⎣ c b ⎥⎦POLSAR acquires scattering matrix over target region( SHV=SVH=c for back scattering )⎡ a2⎢[C ] = ⎢⎢ 2 ca*⎢ ba*⎣

2 ac *2c

22 bc*⎤⎥
2 cb* ⎥
⎥
2⎥b
⎦
ab*

The second order statistics of scattering nature⋅ : ensemble average

5Classification method IICorrelation coefficient
Co-pol. correlation coefficient for LR circular basis
γ LL − RR = Cor ( LL, RR) =2*S LL S RRS LL

2S RR

2=4c − a −b

2a − b + j 2c− j 4 Re c* (a − b)a − b − j 2c22Phase

ϕ LL − RR = tan −1

4 Re c* (a − b)a −b −4c22Relationship between RL basis and HV basis[S ( LR )] = ⎡⎢ LLS⎣ S RLS LR ⎤ 1 ⎡1 j ⎤ ⎡a c ⎤ ⎡1 j ⎤ 1 ⎡a − b + j 2cj ( a + b) ⎤= ⎢= ⎢⎥⎥⎢⎥⎢⎥S RR ⎦ 2 ⎣ j 1 ⎦ ⎣ c b ⎦ ⎣ j 1 ⎦ 2 ⎣ j (a + b) b − a + j 2c ⎥⎦Classification method IICorrelation coefficient
Co-pol. correlation coefficient for XY basis(45o rotation)

γ XX −YY = Cor ( XX , YY ) =S XX

2SYYa +b −4c2

*S XX SYY
2=

2a + b + j 2c+ j 4 Im c * (a + b)
2

a + b − j 2c

2

Phase

ϕ XX −YY = tan −1

4 Im c * (a − b)a −b −4c22Relationship between XY basis and HV basis[S ( XY )] = ⎡⎢ XXS⎣ SYXS XY ⎤ ⎡ cos θ=SYY ⎥⎦ ⎢⎣− sin θsin θ ⎤ ⎡a c ⎤ ⎡cos θcos θ ⎥⎦ ⎢⎣ c b ⎥⎦ ⎢⎣ sin θ− sin θ ⎤ 1 ⎡a + b + 2cb−a ⎤= ⎢⎥a + b − 2c ⎥⎦cos θ ⎦ 2 ⎣ b − a(θ=45o)

6Observation based on
POLSAR image analysis
Yamakoshi villageRange

X-band, Nov. 4, 2004

RGB composite (Red: Pd, Green: Pv, Blue: Ps)

Pi-SAR data description
Fully polarimetric data take function
Mode: Quad.Pol. HH+HV+VH+VV

Dual frequency band
L-bandX-bandFrequency (Wavelength)1.27GHz (0.236m)

9.55GHz (0.0314m)

Pixel size

2.5m by 2.5m

1.25m by 1.25m

Total pixel number(entire region)

6,000 by 4,000

12,000 by 8,000

Averaging size

5 by 5 pixels

10 by 10 pixels

Incident angle

10/26: 26.91-52.77 [deg.]
11/04: 27.25-53.29 [deg.]

11/04: 27.25-53.29 [deg.]

Measured date
Date: 10/26/2004
11/04/2004

L-bandL-band and X-band

7

Natural dam detection
Tanesuhara area
Higashi-Takezawa area

Copyright©1998-2006 NTT DATA CORPOLATION

Natural dam detection I
Tanesuhara area
Oct. 26, 2004
Composite image obtained by``Power decomposition’’Pd (Double-bounce scattering)L-bandPv (Volume scattering)Ps (Surface scattering)Nov. 4, 2004

L-band8Natural dam detection I
Tanesuhara area
Oct. 26, 2004
Composite image obtained by``Power decomposition’’Pd (Double-bounce scattering)L-bandPv (Volume scattering)Ps (Surface scattering)Nov. 4, 2004

X-bandNatural dam detection II
Higashi-Takezawa area
Oct. 26, 2004
Composite image obtained by``Power decomposition’’Pd (Double-bounce scattering)L-bandPv (Volume scattering)Ps (Surface scattering)Nov. 4, 2004

L-bandCopyright©1998-2006 NTT DATA CORPOLATION

9Natural dam detection II
Higashi-Takezawa area
Oct. 26, 2004
Composite image obtained by``Power decomposition’’Pd (Double-bounce scattering)L-bandPv (Volume scattering)Ps (Surface scattering)Nov. 4, 2004

X-bandCopyright©1998-2006 NTT DATA CORPOLATION

Man-made target detection I-a
Higashi-Takezawa area
L-band (1.27GHz)
Oct. 26, 2004
Before flood

RGB composite image
1.0

1.0

1.0

0.0

0.0

0.0

|Cor(HH,VV)||Cor(LL,RR)||Cor(XX,YY)|(45o rotation)

10

Power decomposition-- 4 scattering components decomposition -[C ] = f s ⋅ [C ]surface + f d ⋅ [C ]double + f v ⋅ [C ] volume + f c ⋅ [C ] helix

Total power =+Surface scattering⎡β 2⎢[C ]surface = f s ⎢ 0⎢ β*⎣Based on “physical mechanism”++ Helix scattering

Double-bounce scattering⎡10 β⎤
⎥
0 0⎥
0 1⎥
⎦

[C ]double = ⎢⎢ 0
⎢α
⎣

α* ⎤
⎥
0 0 ⎥
20 α ⎥⎦0Volume scattering⎡⎡3 0 1 ⎤81[C ] helix = ⎢⎢m j 2[C ] volume = 1 ⎢⎢0 2 0⎥⎥⎢ −1⎣⎢⎣1 0 3⎥⎦±j 22
mj 2−1 ⎤⎥± j 2⎥
1 ⎥⎦P (θ ) = 1 / 2π

Right angle dihedral structure:
Vertical wall and the ground surface.

GroundMan-made target detection I-b
Higashi-Takezawa area
L-band (1.27GHz)
Nov. 4, 2004
After flood

RGB composite image
1.0

1.0

1.0

0.0

0.0

0.0

|Cor(HH,VV)||Cor(LL,RR)||Cor(XX,YY)|(45o rotation)

11

Man-made target detection I-c
Higashi-Takezawa area
X-band (9.55GHz)
Nov. 4, 2004
After flood

RGB composite image
1.0

1.0

1.00.00.0

0.0|Cor(HH,VV)||Cor(LL,RR)||Cor(XX,YY)|(45o rotation)

What is back-scattered?
Double-bounce scattering

Before flood

Double-bounce scattering

Oct. 26, 2004

Surface scattering

GroundRiver12What is back-scattered?
Double-bounce scattering

After flood
Nov. 04, 2004

Flooded river

GroundDouble-bounce scattering is enhanced.

Reflection symmetry or not?
Reflection symmetry**
S HH S HV≈ SVV S HV
≈ 0 i.e. ac * ≈ bc * ≈ 0

No residence,
Many trees (Forest)

This condition is derived from experimental results.

Co-pol. correlation coefficient for LR basis
4c − a −b24c + a −b22( 0)( 0)( LL, RR) =γ LL− RR = Cor2Phase

Real0 or π

Many residences or man-made targets

Non-reflection symmetry

Co-pol. correlation coefficient for LR basis
4c − a −b2

γ LL − RR = Cor ( LL, RR) =2a − b + j 2c− j 4 Re c* (a − b)2a − b − j 2cComplex

2Phaseϕ LL − RR = tan −1

4 Re c* (a − b)a −b −4c2213

Man-made target detection IIHigashi-Takezawa area

L-band image (1.27GHz)

Oct. 26, 2004

Nov. 04, 2004

Before flood

After floodPdPvPsPdPvPs

Composite image|Cor(LL,RR)|

Composite image+j-1|Cor(LL,RR)|+j+1-j-1+1-j

ϕLL-RR

ϕLL-RR

Man-made target detection II
Higashi-Takezawa area

L-band image (1.27GHz)
Nov. 04, 2004

After flood|Cor(LL,RR)| >0.8
ϕLL-RR is not 0 or π+j-1+1-j

ϕLL-RR

Extract the data
under |Cor(LL,RR)|>0.8

White: |Cor(LL,RR)| >0.8
Black: |Cor(LL,RR)| <0.814

Summary of the man-madetarget classification schemePdPvPs

Step 1. Power decomposition- Extract double-bounce scattering
for wide area image

Composite image|Cor(LL,RR)| >0.8

Step 2. Further extraction under the conditions as+j

ϕLL-RR is not 0 or π

- |Cor(LL,RR)|>0.8- ϕLL-RR is not 0 or π-1+1(Correlation coefficient for LR basis)-jfor the extracted small area image

Ang{Cor(LL,RR)}|Cor(LL,RR)|

ϕLL-RR

Modified correlation
coefficient[1][2]Co-pol. correlation coefficient for LR basis
4c − a −b2

γ LL − RR = Cor ( LL, RR ) =2− j 4 Re c* (a − b)a − b + j 2c

24c − a −b2

4c + a −b2

a − b − j 2c

2Reflection symmetry2( 0)(0)γ LL( LL, RR) =− RR = Cor

2**S HH S HV
≈ SVV S HV
≈0ac * ≈ bc* ≈ 0

Modified co-pol. correlation coefficient for LR basis [1],[2]4c − a −b2

γ LL − RR = Cor ( LL, RR) / Cor ( 0) ( LL, RR) =2a − b + j 2c− j 4 Re c* (a − b)2a − b − j 2c24c + a −b24c − a −b22⋅

2[1] D. Shuler, J.-S. Lee, et al., ``Characteristics of polarimetric SAR scattering in urban and natural areas,’’Proc. of EUSAR 2006, CD-ROM, May 2006.
[2] D. Shuler, J.-S. Lee, et al., ``Polarimetric SAR detection of man-made structures using normalized
circular-pol correlation coefficient,’’ Proc. of IGARSS 2006, pp.485-488(CD-ROM), Aug. 2006.

15

Man-made target detection IIIHigashi-Takezawa area

L-band image (1.27GHz)
Nov. 04, 2004

After flood- |Cor(LL,RR)|>0.8- |Ang{Cor(LL,RR)}|<170 o
YESPdPv
Ps

Extracted result+jComposite image |Cor(LL,RR)|
Without phase information|Cor(LL,RR)|/|Cor(0)(LL,RR)|

Man-made target detection III
Higashi-Takezawa area

X-band image (9.55GHz)
Nov. 04, 2004

After flood- |Cor(LL,RR)|>0.8- |Ang{Cor(LL,RR)}|<170 o
YESPdPv
Ps

Extracted result+jComposite image |Cor(LL,RR)|
Without phase information|Cor(LL,RR)|/|Cor(0)(LL,RR)|

16FDTD polarimetric analysis
Polarimetric scattering analysis fora simple man-made target modelby using the FDTD methodzf=1.27GHz (L-band)

Plane wave
incidence
H-pol
V-polθyφ
PEC plate(Water)x

Parameters of the FDTD analysiszf=1.27GHz (L-band)

Permittivity& conductivity

W=L=1.2m (5.08λ)
H=1.6m (6.78λ)Wmain part:εr=4 σ=0.0070

H-pol
V-pol

(εr=4-j0.2 at 1.27GHz )D=0.3m (1.27λ)θbase part:
εr=7 σ=0.0141

LR(εr=7-j0.1 at 1.27GHz )φx

PEC plate(Water)H

R=1.4m (5.93λ)Dy

θ=45 [deg.]
φ= 0 to 40 [deg.]

φ:variable

Other parameters in FDTD simulation
Analytical region
350 X 350 X 350 cells
Cubic cell size Δ0.01m
Time step Δt
1.925 X 10-11 sIncident pulse
Lowpass Gaussian pulse
Absorbing boundary condition Mur 2nd17

Statistical evaluation
Evaluation of statistical polarimetric scattering feature
as actual POLSAR image analysis,
Plain view

yyx

yx

yx

0-10deg.

10-20deg.

x20-30deg.

30-40deg.

Ensemble average processing is carried out foreach squint angle range (Average of 10 angles).

Double-bounce squint
angular range[3]z1

WH-polV-polθLR

PEC plate(Water)

W = 5.08λ , θ =θ i= 45o
X =πDyφx

H

X = kW cos θ sin φφc = sin −1 (λ / 2W cos θ )Function (sin X / X )2

f=1.27GHz (L-band)

0.8
0.6
0.4

First minima
φc = 8.001o

0.2
05

10 15 20 25

Squint angle φ [deg.][3] K. Hayashi , R. Sato, Y. Yamaguchi and H. Yamada, ``Polarimetric scattering analysis for a finite dihedral
corner reflector,’’ IEICE Trans. on Commun., Vol.E89, No.1, Jan. 2006.

18

Statistical result of
the FDTD analysis
Power decomposition

Correlation coefficient (LR basis)

Pt=Pd+Ps+Pv+Pc
Dielectric model

PEC model

Statistical result of
the FDTD analysis
Power decomposition

Modified correlation coefficient (LR basis)

Pt=Pd+Ps+Pv+Pc
Dielectric model

PEC model

19

Conclusions
Detection of the studded stricken areas
in mountainous region
based on POLSAR image analysis
Hybrid classification procedure
Step 1. Power decomposition
Step 2. Correlation coefficient- Achievement of accurate classification of the stricken areas- Validity has also been confirmed by
FDTD analysis for simple man-made target model

Acknowledgments- The authors express their sincere appreciation to NiCT andJAXA, Japan, for providing valuable Pi-SAR image data andto Prof. Makino, Niigata University, and NTT data corp. forproviding their high resolution photos around the stricken
areas.
- This research was partially supported by a Scientific
Research Grant-In-Aid (19510183, 2007) from JSPS (JapanSociety for the Promotion of Science), Japan.

20