soil moisture retrieval under vegetation using dual polarized palsar data

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Christian N. Koyama University of Cologne IGARSS 2011 Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data Christian Koyama & Karl Schneider Department of Geosciences University of Cologne IGARSS 2011 Vancouver July 26, 2011

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Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data. Christian Koyama & Karl Schneider Department of Geosciences University of Cologne IGARSS 2011 Vancouver July 26, 2011. Outline Test Site & Field Measurements ALOS PALSAR Data & Processing - PowerPoint PPT Presentation

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Page 1: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian Koyama & Karl SchneiderDepartment of Geosciences

University of CologneIGARSS 2011 Vancouver

July 26, 2011

Page 2: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Outline

• Test Site & Field Measurements

• ALOS PALSAR Data & Processing

• Grassland Soil Moisture Retrieval Model

• High Resolution Surface Soil Moisture Patterns

• Conclusions

- 02 -TABLE OF CONTENTS

Page 3: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Grass layerLayer depth: 5 – 175 cmDielectric constant: 15 – 25 Blade density: 1000 – 3000/m²Grass biomass: 0.2 – 3.1 kg/m²Thatch layer

Layer depth: 2 – 4 cmDielectric constant: 6 – 70Soil half spaceDielectric constant: 9.7 – 33.8Texture: clay/silt loam

GROUND TRUTH DATA(test site and field measurements)

- 03 -

Page 4: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

PALSAR Fine Mode Dual Polarization DataRegion: Track 647+648 / Frame 1000+1010Ground Range Resolution: 15 mCenter Frequency: L-band @ 1,270 MHzChirp Bandwidth: 14 MHzPolarization: HH + HVOff-Nadir Angle: 34.3 deg.

2007 2008 2009

Track 647Track 648

10/2

1/20

09

5/4/

2008

6/2/

2008

6/19

/200

8

7/18

/200

8

6/22

/200

9

7/21

/200

9

9/5/

2009

9/22

/200

9

9/17

/200

7

8/2/

2007

Soil moistureSurface roughnessBiomass

ALOS PALSAR FBD343 DATA(product description & acquisition overview)

- 04 -

Jan.

Feb. Mar. Apr. May

June July

Aug.

Sep.

Oct. Nov.

Dec.

Aug.

Sep.

Oct. Nov.

Dec.

Jan.

Feb. Mar. Apr.

May

June July

Aug.

Sep.

Oct. Nov.

Dec.

Jan.

Feb. Mar. Apr.

May

June

5/10

/201

0

6/25

/201

0

2010

Page 5: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

ALOS PALSAR FBD343 Level 1.1

Multi-looking

Coregistration + Generic Filtering

Terrain Geocoding

Radiometric Calibration

HH Power Image HV Power Image

[C2] Matrix Elements Processing

Multi-Looking

H/A/Alpha Decomposition

Covariance [C2] Matrix Elements

H A alpha span

Geocoding

σ0HH σ0

HV

SIMPLIFIED PROCESSING CHAIN(basic processing and polarimetric decomposition of FBD343)

- 05 -

Page 6: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

2008-06-02 2008-07-18 2009-07-21

0 200 400100Meters

0 200 400Meters

Dual-pol α/H/span-HSV(H = alpha / S = entropy / V = span)

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Page 7: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Thatch

Matrix soil

Grass canopy

- 7 -THATCH LAYER EFFECT

Page 8: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

10

20

30

40

50

60

70

80

90

entropy

alph

aangl

e[deg

.]

?

2009-07-21

mv = 37.9 / SD = 4.4

2009-07-21

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

10

20

30

40

50

60

70

80

90

entropy

alph

aangl

e[deg

.]

?

2008-06-02

mv = 34.5 / SD = 3.4

2008-06-02

Alp

ha [d

eg.]

Entropy

Alp

ha [d

eg.]

Entropy

mv = 37.9 SD = 4.4

mv = 34.5 SD = 3.4

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

10

20

30

40

50

60

70

80

90

entropy

alph

aangl

e[deg

.]

?

2008-05-04

mv = 51.1 / SD = 4.2

2008-05-04

mv = 51.1 SD = 4.2

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

10

20

30

40

50

60

70

80

90

entropy

alph

aangl

e[deg

.]

?

2007-09-17

mv = 48.7 / SD = 4.9mv = 48.7 SD = 4.9

2007-09-17

GRASSLAND H2α PLANES

Alp

ha [d

eg.]

Entropy

Alp

ha [d

eg.]

Entropy

- 8 -

Cloude, S.R. (2007): “The Dual Polarisation Entropy/Alpha Decomposition: A PALSAR Case Study, “ In Proceedings of PolInSAR 2007.

Page 9: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

0

000

11 hh

hvhvspanA

hhHERBA AH

HAH

- 9 -EMPIRICAL GRASSLAND PARAMETER MODEL

Page 10: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

4748.032.169' HERBA

- 10 -GRASSLAND SOIL MOISTURE ESTIMATION

Page 11: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

SURFACE SOIL MOISTURE DISTRIBUTION 25 75mv [Vol.-%]

Ü

0 10050m

Sigma Noughtmv_20070802Value

High : 75

Low : 25

Ü

0 10050m

Sigma Nought

Ü

0 10050m

Sigma Noughtmv_20070917Value

High : 75

Low : 25

2007-08-02 2007-09-17

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Page 12: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Conclusions• L-band dual-pol SAR has the potential to correct for

disturbing effects occurring in grassland ecosystems without the use of a priori knowledge

• The retrieval algorithm is suitable to account for varying effects of vegetation and thatch

• The thatch layer is the major source of attenuation

• At L-band the amount of above ground grass biomass and its geometric properties can be neglected if <2 kg/m²

CONCLUSIONS - 12 -

Page 13: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Thank you for your attention.

Acknowledgements The authors thank the Japan Aerospace Exploration Agency (JAXA) and the European Space Agency (ESA) for the provision of ALOS PALSAR data through their PI programme (AOALO.3570). Financial support by the SFB/TR32 "Patterns in Soil-Vegetation-Atmosphere Systems" funded by the German Research Foundation (DFG) is gratefully acknowledged.

[email protected]

- 13 -

Page 14: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

2009-07-21

0 200 400100Meters

0 200 400Meters

Dual-pol Pauli-RGB(R = C22 / G = C11-2xC12r+C22 / B = C11)

Ü

0 10050m

Sig ma Nou ght

Ü

0 10050m

Sig ma Nou ght

2009-07-212009-07-21

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Page 15: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

Surface Soil Moisture Distribution 25 75mv [Vol.-%]

Ü

0 10050m

Sigma Noughtmv_20080504Value

High : 75

Low : 25

Ü

0 10050m

Sigma Noughtmv_20080602Value

High : 75

Low : 25

Ü

0 10050m

Sigma Noughtmv_20080619Value

High : 75

Low : 25

2008-05-04 2008-06-02 2008-06-19

Page 16: Soil Moisture Retrieval Under Vegetation Using Dual Polarized PALSAR Data

Christian N. KoyamaUniversity of CologneIGARSS 2011Vancouver, July 26

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