Comparison of L and P band radar time series for the monitoring of Sahelian area

P.-L. Frison, G. Mercier, E. Mougin, P. Hiernaux

Context:• Better understanding Sahelian surface processes and their interaction with monsoon variability• Improve our understanding and documentation of long term trend in vegetation in response to climate change• radar data:

2 key parameters: soil moisture and vegetation

Goal:• Comparison of L band PALSAR and C band ASAR data

for Sahelian surface monitoring. Relation between radar vs surface parameter temporal evolution

Outline:

• Study site

• PALSAR and ASAR data

• change detection method

• Results and discussion

The Sahel

Semi-arid area

herbaceous layer (0-50 %) (annual grasses)

Dry season (Nov. – Apr.)

bare soil

Rainy season (May – Oct.)

shrub (0-20 %) trees (1-5 %)+

Region of study: the Gourma - Mali

Seno

PALSAR acquisitions: L band (Jan. 2007 - Apr. 2009)

DATASET

Mode # Polarization Resolution Incidence angle

Pass

Fine Beam 7 HH 15 m 40° Ascending

Fine Beam 5 HH / HV 15 m 40° Ascending

Wide Swath 6 HH 100 m 30° Descending

ASAR acquisitions: C band (Jul. - Dec. 2005)

Mode # Polarization Resolution Incidence angle

Pass

Wide Swath 41 HH 150 m 18-35° Ascending+

Descending

Gourma Region (MALI)ASAR –Wide Swath - HH

20th Dec 2005

GOURMA Region (MALI)PALSAR–WIDE BEAM- HH

1st Jan 2008

Gourma Region (MALI)ASARC-band

PALSARL-band

C-band (ASAR):Shallow sand and silt soils

L -band (PALSAR):Better discrimination of geological features

Remnant of alluvial systems and lacustrine depressions

Gourma Region (MALI)ASARC-band

PALSARL-band

C-band (ASAR):Shallow sand and silt soils

L -band (PALSAR):Better discrimination of geological features

Remnant of alluvial systems and lacustrine depressions

PALSAR Fine Beam – HH polarizationTemporal color composite image

GOURMA - MALI17 Jan. 200720 Oct. 200722 Jan.2009

Water pondsHombori mounts

Low-land (accacia forest)

Change detection methodConstraints:

Large dynamic range (high differences over bright patterns)Even after multi-looking, presence of noise (speckle) absolute or relative differences, ratios, rms,….. not

significant

Time series color composite image Relative differences

Temporally stable regions gray

Change detection colored areas

Case of 3 channels

Change detection methodConstraints:

Large dynamic range (high differences over bright patterns)Even after multi-looking, presence of noise (speckle) absolute or relative differences, ratio, rms,….. not

significant

Temporally stable areas gray areas (no saturation)

Change detection colored areas (saturation)

RGB space R

B

G0

HSV space

Case of 3 channels

Value

Saturation

Hue

Change detection methodConstraints:

Large dynamic range (high differences over bright patterns)Even after multi-looking, presence of noise (speckle) absolute or relative differences, ratio, rms,….. not

significant

17 Jan. 200720 Oct. 200722 Jan.2009

RGB Space

Value

Hue

Saturation

HSV Space

Areas that have changed

Color composite image Saturation image

17 Jan. 200720 Oct. 200722 Jan.2009

Change detection for a 3-date color composite image

PALSAR Fine BeamHH polarization

Change detection methodCase of N channels (N>3):

P iterations:1) random draw of 3 among the N available

channels2) Compute the saturation channel from HSV

space

Average of the P saturation channels

Example: 12 Finebeam acquisitions at HH pol.N=12 12! / (9! * 3!) = 220 possible random

draws

P =50 (arbitrary)

Color composite image Saturation image

17 Jan. 200720 Oct. 200722 Jan.2009

Change detection for a 3-date color composite image

PALSAR Fine BeamHH polarization

Color composite image Saturation image

Change detection for 12 FineBeam acquisitions (HH polarization)

17 Jan. 200720 Oct. 200722 Jan.2009

PALSAR Fine BeamHH polarization

Jan. 2007 – Apr. 2009

Temporal changes detected over 12 Fine Beam acquisitions

PALSAR dataHH polarisationJan. 2007 – Mar. 2009

Water ponds

Fields (millet) dep. Orientation!

Significant penetration depth over sandy soils

Changes in dry seasonChanges in rainy season

Temporal changes detected over 12 Fine Beam acquisitions

Water pondspermanent

PALSAR dataHH polarisationJan. 2007 – Mar. 2009

Fields (millet) dep. Orientation!

ALOS/PALSAR – FBD6th June 2008

HH HV

Sandy soils

Shallow soils

INFLUENCE OF POLARISATION

Change detection between HH and HV

PALSAR DUAL POLARIZATION

Shallow soils+

Water ponds

ALOS/PALSAR – WB1: HH Polarization

Water ponds discrimination

2008 dry season:1 Jan16 Feb2 Apr

3-date color composite image

Change detection (dry season)

ALOS/PALSAR – WB1: HH Polarization

Water ponds discrimination

• Main water resource • Hydrological indicator

surface runoffareas increase since begining of drought

period (50’s)

ASAR –Wide Swath – HH polarisation

41 acquisitions22 acquisitions in ascending pass

5 acquisitions same incidence angle (35°) – Jul. –Dec. 2005

ASAR –Wide Swath - HH polarisation

2nd Sept. 2005 change detection (5 dates)

low penetration over sandy soil upper surface changes

sandy soils

ASAR –Wide Swath - HH polarisation

2nd Sept. 2005 change detection (5 dates)

low penetration over sandy soil upper surface changes

sandy soils, water ponds

change detection (5 dates)PALSAR (L-band)

low penetration over sandy soil upper surface changes

sandy soils, water ponds

High penetration dpeth over sandy soilswater ponds millet fields

Comparison P band / L band temporal change detection

Conclusion

• RGB HSV simple but performant for change detection!

• Temporal change detection: penetration depth illustration

histogram must be the same across the hole image!

C band (low penetration over sandy soils)mix of upper surface changes

sandy soils (soil moisture + vegetation)water ponds

more difficult te discriminate special features

• L band: some variation over sandy soils (soil moisture?) Cross over with SMOS mission

L band (high penetration over sandy soils)Water pondsMillet fields

Thank you for your attention!