ADAPTIVE LOCAL KRIGING (ALK) TO RETRIEVE THE SLANT RANGE SU - PowerPoint Presentation

Slide1

ADAPTIVE LOCAL KRIGING (ALK) TO RETRIEVE THE SLANT RANGE SURFACE MOTION MAPS OF WENCHUAN EARTHQUAKE

Department of Earth Science and Engineering

Imperial College London

Meng-Che

Wu

meng-che.wu08@imperial.ac.uk

Jian

Guo

Liu

j.g.liu@imperial.ac.ukSlide2

Outline

Background & Purpose

Method Development

Experimental Results

ConclusionsFuture worksSlide3

Background & PurposeSlide4

Background & Purpose

Path 471

Path 472

Path 473

Path 474

Path 475

Path 476

Azimuth

Range

2

π

0Slide5

Background & Purpose

≈

1 m

≈ -

1 m

Azimuth

Range

Path 471

Path 472

Path 473

Path 474

Path 475

Path 476Slide6

Ordinary

kriging:

Γ *

λ = g Γ is a matrix of the semivariance between each sampled point. λ

is a vector of the

kriging

weights.

g is a vector of the

semivariance

between a unknown point and each sampled point.

Semivariance

= FSM(D)

FSM is the fitted

semivariogram

model.

D is the distance

bewteen

each sampled point or the distance between a unknown point and each sampled point.

Ordinary kriging concept

S = (x, y) is a locationSlide7

Example of semivariogram model

≈

1 m

≈ -

1 m

Gaussian modelSlide8

Method: Adaptive Local

Kriging

≈

1 m

≈ -

1 m

Azimuth

Range

Hang wall

Foot wall

Window

based

kriging

scan to calculate the linear fitting of local

semivariance

.

2. Window

size is

locally adaptive to ensure adequate data points and high processing efficiency.Slide9

Semivariance

Distance

Averaged

semivariance

Fitted semivariance

x

= 1024, y =

230

Local gradient

:

1.258×10

-5

ALK local

semivariogram

model: Towards the seismic fault (

Hang wall side

)Slide10

Semivariance

Distance

Averaged

semivariance

Fitted semivariance

ALK local

semivariogram

model: Towards the seismic fault (

Hang wall side

)

x

= 1024, y =

460

Local gradient

:

5.812×10

-5Slide11

Semivariance

Distance

Averaged

semivariance

Fitted semivariance

ALK local

semivariogram

model: Towards the seismic fault (

Hang wall side

)

x

= 1024, y =

580

Local gradient

:

7.313×10

-5Slide12

Semivariance

Distance

Averaged

semivariance

Fitted semivariance

ALK local

semivariogram

model: Towards the seismic fault (

Foot wall side

)

x

=

745,

y =

1200

Local gradient

:

1.624×10

-5Slide13

Semivariance

Distance

Averaged

semivariance

Fitted semivariance

ALK local

semivariogram

model: Towards the seismic fault (

Foot wall side

)

x

=

745,

y =

1000

Local gradient

:

3.613×10

-5Slide14

Semivariance

Distance

Averaged

semivariance

Fitted semivariance

ALK local

semivariogram

model: Towards the seismic fault (

Foot wall side

)

x

=

745,

y =

870

Local gradient

:

7.652×10

-5Slide15

ALK

(

Decoherence

zone)

ALK multi-step processing flow chart

Input data

Hang wall & foot wall separation

Final ALK result

Ordinary

kriging

ALK

Give some sampled points in the large

decoherence

gaps

Artificial discontinuity elimination

H

F

H

F

Coherence

thresholding

Coherence

thresholdingSlide16

ALK data

≈

1 m

≈ -

1 m

Azimuth

RangeSlide17

2

π

0

ALK rewrapped

interferogram

Azimuth

RangeSlide18

Original

interferogram

2

π

0

Azimuth

RangeSlide19

ALK results assessment

Azimuth

Range

Original unwrapped image profile

ALK

data profile

A

A’

A

A’

Path 471 profiles

RMSE:

0.0053591572

meters

Correlation

coefficient:

0.99999985

≈

1 m

≈ -

1 mSlide20

ALK results assessment

Original unwrapped image profile

ALK data

profile

A

A’

Azimuth

Range

A’

A

Path

472

profiles

RMSE:

0.00909682429

meters

Correlation

coefficient:

0.99939712

≈

1 m

≈ -

1 mSlide21

ALK results assessment

Original unwrapped image profile

ALK

data profile

Traced

fault line

Initial fault

A

A’

Azimuth

Range

A’

A

Path

473

profiles

RMSE:

0.0083477924

meters

Correlation

coefficient:

0.99973365

≈

1 m

≈ -

1 mSlide22

ALK results assessment

Original unwrapped image profile

ALK

data profile

Traced

fault line

Initial fault

A

A’

Azimuth

Range

A’

A

Path

474

profiles

RMSE:

0.017175553

meters

Correlation

coefficient:

0.99792644

≈

1 m

≈ -

1 mSlide23

ALK results assessment

Original unwrapped image profile

ALK

data profile

Traced

fault line

Initial fault

A

A’

Azimuth

Range

A’

A

Path

475

profiles

RMSE:

0.0059325138

meters

Correlation

coefficient:

0.99969193

≈

1 m

≈ -

1 mSlide24

ALK results assessment

Original unwrapped image profile

ALK

data profile

A

A’

Azimuth

Range

A’

≈

1 m

≈ -

1 m

A

Path

476

profiles

RMSE:

0.0071013203

meters

Correlation

coefficient:

0.99929831Slide25

3D visualization of ALK data

≈

1 m

≈ -

1 mSlide26

Refined ALK data

≈

1 m

≈ -

1 m

Azimuth

RangeSlide27

2

π

0

Azimuth

Range

Refined ALK rewrapped dataSlide28

3D view of refined ALK unwrapped data

≈

1 m

≈ -

1 mSlide29

Local

semivariogram

is more

representive to the local variation  of spatial pattern of the interferogram than a global semivariogram model.Dynamical local linear model represents a nonlinear global model for the whole interferogram.ALK multi-step processing procedure avoids the error increases in large decoherence gaps.

ConclusionsSlide30

Conclusions

The ALK interpolation data revealed dense fringe patterns in

the

decoherence

zone and show high fidelity to the original data without obvious smoothing effects.The initial fault line separating the data does not affect the final interpolation result of ALK processing.The seismic fault line that can be denoted in the ALK is different from that in publications. The discrepancy needs further investigation.Slide31

Geological structural numerical

modeling to explain the discrepancy of trend of seismic fault line.

Three dimensional surface deformation maps development.

Future worksSlide32

Thank you

Any questions ?Slide33
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