Large-scale deformation mapping over Danakil depression (Afar, Ethiopia) from

Wide-Swath SAR interferometric time series

Pablo J. González1, Nicolas d’Oreye2, Eugenio Sansosti3, Kristy F. Tiampo1 and José Fernández4

1. Dept. Earth Sciences, University of Western Ontario, London-Ontario, Canada.2. Musée National d’Histoire Naturelle (MNHN), Luxembourg.3. Istituto per il Rivelamento Elettromagnetico dell’Ambiente (IREA, CNR), Naples, Italy4. Institute of Geosciences (CSIC-UCM), Facultad CC. Matemáticas, Madrid, Spain

Outline

Motivation

SCANSAR interferometry time series

Case application: Danakil depression

Conclusions

Motivation Some Earth Sciences problems require the imaging of large areas:

DEM generation (efficient and reliable global coverage)Deformation mapping

Carbon cycle monitoring (large basins forestry),…

So far, Wide-swath interferometry - success - applied in ground deformation monitoring: In particular, static ground deformation due to large earthquakes

Why time series processing of Wide-swath interferometry time series?

WS Time Series could:

Reduce burden for the monitoring of extended areas

Estimation of reliable long-scale smoothly variable deformation signals

DInSARReliable tool to measure/mapping ground deformation of the Earth’s surface Interferometric synthetic aperture radar (InSAR) combines phase information from two radar (SAR) images of the same area acquired from similar view points at different times to produce an pattern of phase interference (interferogram).

The interferogram, depicting range changes between the radar and the ground within a fraction of the wavelength precision (mm-cm) under favorable conditions.

DInSAR time seriesHowever, ground deformation and Earth surface changes are dynamic (change with time).

Time series processing (SBAS or PSI) provides with: linear velocity maps and time series of displacements.

Proved to be more precise, successful reduction of atmospheric noise.

SCANSAR concept Large scale coverage though

a set of radar pulses (bursts)

Covering multiple swathes (loss of azimuth resolution)

ScanSAR sensors ENVISAT ALOS TSXNumber of sub-swaths 5 3-5 4 Swath width (ground range) 400 km 250-350 km 100 km Incidence angle range 16°-44° 16°-38° 20°-45° Azimuth resolution 150 m 100 m 18.5 m Ground range resolution 20 m 100 m 1.70 - 3.49 m

400 km

400

km

Figure: DLR

Stack processing issues:

Synchronization of bursts is necessary for phase preservation.If no or low burst overlap, corregistration maybe be problematic, and typical single “master” stack might not be accomplished.

Coregistration of differential interferograms:

All interferograms were spectrally cross-correlated

Resampled with a 12-points cosine-raised method

Common “master” interferogram geometry (200612-200701)

100 %overlap

50 %overlap

0 %overlap

Our processing chain for WS time series:Our processing chain for WS time series:

1) Wide Swath or ScanSAR raw focusing.1) Wide Swath or ScanSAR raw focusing.

2) Pair-wise single SLCs coregistration.2) Pair-wise single SLCs coregistration.

3) Resampling and mosaicking.3) Resampling and mosaicking.

4) (Differential) Interferogram computation (w/o DEM and F.E.) + Coherence.4) (Differential) Interferogram computation (w/o DEM and F.E.) + Coherence.

5) Repeat 2-4 until all interferograms are computed.5) Repeat 2-4 until all interferograms are computed.

Steps computed with:Steps computed with:SARScapeSARScape

6) Corregistration of all interferograms to a single interferogram (interferograms stack).6) Corregistration of all interferograms to a single interferogram (interferograms stack).

7) Resample.7) Resample.

8) Unwrapping (SNAPHU or GAMMA)8) Unwrapping (SNAPHU or GAMMA)

9) Small Baseline time series inversion (LSQ or SVD analysis)9) Small Baseline time series inversion (LSQ or SVD analysis)

Steps computed with:Steps computed with:Home-made softwareHome-made software

Danakil depression (Afar) Northern most segment of the on-shore African Rift

Extensional tectonics (~normal faulting) and magmatism

Similarities with divergent mid-ocean ridges (80% volcanism)

http://www.see.leeds.ac.uk/afar/new-afar/geology-afar/structure-tech-pages/geol-afar-dep-tech.html

Danakil depression (Afar) Northern most segment of the on-shore African Rift

Extensional tectonics (~normal faulting) and magmatism

Similarities with divergent mid-ocean ridges (80% volcanism)

Quaternary strain localized to ~60 km long zones of

fissures, aligned eruptive centers and faults –

“magmatic segments“

http://www.see.leeds.ac.uk/afar/new-afar/geology-afar/structure-tech-pages/geol-afar-dep-tech.html

Recent investigations (Reilinger et al., 2010) deducted the existence of a distinguished tectonic block between Arabia, Nubia and Ethiopian plates from GPS kinematics measurements.

The Danakil block has a strong NS gradient of rapidly E-W motion w.r.t. fixed Nubia. (~0 mm/yr @ 16ºN to ~20 mm/yr @ 12ºN)

So, the diverengence (horizontal strechting) rate is about 20-30 mm/yr at the central part of the depression. This accumulated energy should release, but how?

faulting vs. magmatism.

Ideal case for analyzing

large-scale, distributed

deformation processes

In September 2005, a huge seismo-magmatic (163)

event alerted about a possible large intrusion event.

Wright et al., (2006) and others studied this event

using DInSAR + seismic data.

Interferograms were consistent with a megadike that release large portion of the accumulated elastic energy and correctly forecasted many more intrusions (similar to 1975-1980s Katla rifting event in Iceland)

20050611-200601072.2 km3 magma along dyke (Mt St Helens 1.2 km3).

0.5 km3 sourced from Dabbahu and Gabho volcanoes at North.Earthquakes can be responsible for < 10 % of moment release.

Rowland et al., (2007) reported single

Envisat Wide-ScanSAR interferograms

Full scene Envisat Wide-ScanSAR Interferogram (20050611-20060107)

20050611-20060107

Dataset and processing parameters:

ENVISAT Ascending Track 71:

Number of WSSAR (35) between 2006-2009

Here, we exclude image before 2006 (no frame overlap)

Thresholds for interferograms computation:

50% burst-overlapping (few before 2007, better onwards)

Small perpendicular baselines: < 400 m

We generate a total number of 320 interferograms

and their corresponding coherence maps

Mean coherence map shows extrem good conditions

Interferograms stacking

Stack (average) of differential ifgs to obtain an estimated linear velocity map

Later, processing was performed over

all pixels with average 0.3 coherence

Variable deformation processes:

Northern and southern segmentGrabens deepening

Unknown deflaction source:Semara volcanic centre

Post-dike inflactionDabbahu and Gabho centres

Central-segment dike intrusions + other sources:

Time series resultshere, we show (wrapped) as comparison between consecutive time takes.

Cummulative displacements (2006-2009)

Contour lines each 10 cm of line-of-sight motion

Modelling approach

For reduce the computational burden, a quadtree data reduction was performed to keep points representatives of sigma above the noise (phase std)

InversionInversionRegularized linearRegularized linear

Analytical models Analytical models (green functions, G)(green functions, G)

Best fitting source parameters (s):Best fitting source parameters (s):

Φ (s, k) = || G s – d ||2 + k-2 ||Δ2 s ||2 , s ≥ 0

InterpretationInterpretation

geologically sound?geologically sound?

Geodetic data (d)Geodetic data (d)

d = G s + error

Initial modelling with a simple rift geometry:

Essentially, dislocation geometry follows

the graben (central valley) and

simmetry of the deformation field

data

model residual

Improved segment geometry (extended and tortuous)

Central segment:

Deep to midcrustal magma intrusion

Shallow lateral propagation

Northern segment:

Magma chamber inflaction under Dabbahu volcano

Remainder: solution is strong dependent of the regularization parameter

data model residual

Opening distribution

Profiles

Northern

CentralData (blue)Model (red) Residual (black)

More profiles

Central

Southern

Data (blue)

Model (red)

Residual (black)

Deep deflactionary source

mainly during 2006-2007

Susticious long-wavelength signal:Possible relaxation of the lower crust and upper-mantle under the active segment,

it is also possible to capture partially the secular motion of the spreading plate

GPS estimates indicate significant (uplift, not shown here) and horizontal pattern following the rift events 2006-2009 (Nooner et al., 2009). Intrusions were removed.

Black arrows, secular plate motion

Red arrows, post-dike hor. velocities

Some remarks We show one of the first applications of wide-swath interferometric time series.

Due to burst-overlapping problems, we adopted the coregistration of interferograms, using a cross-correlation algorithm.

The Danakil depression study case shows an ideal case for long-scale deformation mapping.

Severe spatial aliasing occurred close to the central segment (Phase gradient saturation).

Potential detection in a glimpse of deformation centres. Discovery of an unknown deflactiory source farther south of the normally studied region (central segment)

Long-scale wavelength deformation signals still be challenging (orbit contributions), without tie points. Probably, ideal for deformation scales from 100 m to half-width scene.

With the addition of few sparse GPS stations, the “full” characterization and monitoring of long-scale smoothly variable deformation signals (probably, so far more reliable when combined with sparse GPS)

Thanks for your attention

pabloj.glez@gmail.com