Measuring Co-Seismic deformation from SPOT satellite and Aerial
images
Sebastien Leprince (PhD student,
Electrical Engineering
)
Collaborators: Remi
Michel, Renaud Binet (CEA - France)
Francois Ayoub (Software engineer)
Jean-Philippe Avouac - PI - Professor
of Geology
Project supported
by NSF - Proposal EAR-0409652.
(North-South
displacement field - 1999 Hector-Mine earthquake, California. See
below for details).
In complement to seismological
records, the knowledge of the ruptured fault geometry and co-seismic
ground displacements are key data to investigate the mechanics of
seismic rupture. This information can be retrieved from sub-pixel
correlation of optical images. We are investigating the use of SPOT
(Satellite pour l'Observation de la Terre) satellites images.
The technique developed here is attractive due to the operational
status of a number of optical imaging programs and the availability of
archived data. However, uncertainties on the imaging system itself and
on its attitude dramatically limit its potential. We overcome these
limitations by applying an iterative corrective process allowing for
precise image registration that takes advantage of the availability of
accurate Digital Elevation Models with global coverage (SRTM).
This technique is thus a valuable complement to SAR interferometry
which provides accurate measurements kilometers away from the fault but
generally fails in the near-fault zone where the fringes get noisy and
saturated. Comparison between the two methods is briefly discussed,
with application on the 1992 Landers earthquake in California (Mw 7.3).
Applications of this newly developped technique are presented: the
horizontal co-seismic displacement fields induced by the 1999
Hector-Mine earthquake in California (Mw 7.1) and by the 1999 Chichi
earthquake in Taiwan (Mw 7.5) have recently been retrieved using
archive images. Data obtained can be downloaded (see further down)
Latest
Study Cases
Sub-pixel
correlation of optical images
Following is the flow chart of
the technique that as been developped. It allows for precise
orthorectification and coregistration of the SPOT images. More details
about the optimization process will be given in the next sections.

Understanding
the disparities measured from Optical Images
Differences
in geometry between the two images to be registered:
- Uncertainties on attitudes parameters (roll, pitch, yaw)
- Inaccuracy on orbital parameters (position, velocity)
- Incidence angle differences + topography uncertainties (parallax
effect)
- Optical and Electronic biases (optical aberrations, CCD misalignment,
focal length, sampling period, etc… )
» May account for
disparities up to 800 m on SPOT 1,2,3,4 images; 50m for SPOT 5 (see
[3]).
Ground deformations:
- Earthquakes, land slides, etc…
» Typically subpixel scale:
ranging from 0 to 10 meters.
Temporal decorrelation:
- Changes in vegetation, rivers, changes in urban areas, etc…
» Correlation is lost: add
noise to the measurement – up to 1m.
» Ground deformations are
largely dominated by the geometrical artifacts.
Precise
registration: geometrical corrections
SPOT (Systeme pour l'Observation
de la Terre) satellites are pushbroom imaging systems ([1],[2]): all
optical parts remain fixed during acquisition and the scanning is
accomplished by the forward motion of the spacecraft. Each line in the
image is then acquired at a different time and submitted to the
different variations of the platform.
The orthorectification process consists in modeling and correcting
these variations to produce cartographic distortion free images. It is
then possible to accurately register images and look for their
disparities using correlation techniques.

Attitude variations (roll,
pitch, and yaw) during the scanning process have to be integrated in
the image model (see [1],[2]).
Errors in correcting the satellite look directions will result in
projecting the image pixels at the wrong location on the ground:
important parallax artifacts will be seen when measuring displacement
between two images.
Exact pixel projection on the ground is achieved through an
optimization algorithm that iteratively corrects the look directions by
selecting ground control points. An accurate topography model has to be
used.
What
parameters to optimize?
- Initial attitudes values of the platform (roll, pitch, yaw),
-
Constant drift of the attitude values along the image acquisition,
-
Focal length (different value depending on the instrument , HRG1
– HRG2),
-
Position and velocity.
How
to optimize:
Iterative algorithm using a set
of GCPs (Ground Control Points). GCPs are generated automatically with
a subpixel accuracy: they result from a correlation between an
orthorectified reference frame and the rectified image whose parameters
are to be optimized.
A
two stages procedure:
- One of the image is optimized
with respect to the shaded DEM (GCP are generated from the correlation
with the shaded DEM). The DEM is then considered as the ground truth.
No GPS points are needed.
- The other image is then optimized using another set of GCP
resulting from the correlation with the first image (co-registration).
Measuring
co-seismic deformation with InSAR, a comparison
A fringe represents a
near-vertical displacement of 2.8 cm
SAR interferogram (ERS): near-vertical component of the ground
displacement induced by the 1992 Landers earthquake [Massonnet et al.,
1993].
No organized fringes in a band within 5-10 km of the fault trace:
displacement sufficiently large that the change in range across a radar
pixel exceeds one fringe per pixel, coherence is lost.
http://earth.esa.int/applications/data_util/ndis/equake/land2.htm
» SAR interferometry is not a suitable technique to measure near
fault displacements
The
1992 Landers earthquake revisited:

Profile
in offsets and elastic modeling show good agreement
From: [6] - Measuring earthqakes
from optical satellite images, Van Puymbroeck, Michel, Binet, Avouac,
Taboury - Applied Optics Vol. 39, No 20, 10 July 2000
Other applications of the technique, see [4], [5].
» Fault ruptures
can be imaged from this technique
Applying
the precise rectification algorithm + subpixel correlation:
The 1999 Hector-Mine
earthquake (Mw 7.1, California)


Obtaining the Data (available in ENVI
file Format. Load banbs as gray scale images. Bands are: N/S offsets,
E/W offsets, SNR):
Raw and filtered results: HectorMine.zip
Pre-earthquake
image:
SPOT 4, acquisition date: 08-17-1998
Ground resolution: 10m
Post-earthquake
image:
SPOT 2, acquisition date: 08-18-2000
Ground resolution: 10m
Offsets
measured from correlation:
Correspond to sub-pixel offsets
in the raw images.
Correlation windows: 32 x 32 pixels
96m between two measurements
So
far we have:
- A precise mapping of the rupture zone: the offsets field have a
resolution of 96 m,
- Measurements with a subpixel accuracy (displacement of at most 10
meters),
- Improved the global georeferencing of the images with no GPS
measurements,
- Improved the processing time since the GCP selection is automatic,
- Suppressed the main attitude artifacts. The profiles do not show any
long wavelength deformations (See Dominguez et al. 2003)
We
notice:
- Linear artifacts in the along track direction due to CCD
misalignments,
Schematic of a DIVOLI
showing four CCD linear arrays.
- Some topographic artifacts: the image resolution is higher than
the DEM one,
- Several decorrelations due to rivers and clouds,
- High frequency noise due to the noise sensitivity of the Fourier
correlator (See Van Puymbroeck et al.).
Conclusion
Subpixel correlation technique has been
improved to overcome most of its limitations:
» Precise rectification and co-registration of the images,
» No more topographic effects (depending on the DEM resolution),
» No need for GPS points – independent and automatic algorithm,
» Better spatial resolution (See Van Puymbroeck et al.)
To
be improved:
» Stripes due to the CCD’s
misalignment,
» high frequency noise from the correlator,
» Process images with corrupted telemetry.
»
The subpixel correlation technique appears to be a valuable complement
to SAR interferometry for ground deformation measurements.
References:
[1] SPOT 5 geometry handbook:
ftp://ftp.spot.com/outgoing/SPOT_docs/geometry_handbook/S-NT-73-12-SI.pdf
[2] SPOT User's Handbook Volume 1 - Reference Manual:
ftp://ftp.spot.com/outgoing/SPOT_docs/SPOT_User's
Handbook/SUHV1RM.PDF
[3] SPOT 5 Technical Summary
ftp://ftp.spot.com/outgoing/SPOT_docs/technical/spot5_tech_slides.ppt
[4] Dominguez S., J.P. Avouac, R. Michel Horizontal co-seismic
deformation of the 1999
Chi-Chi earthquake measured from SPOT satellite images: implications
for the
seismic cycle along the western foothills of Central Taiwan, J.
Geophys. Res., 107,
10 1029/2001JB00482, 2003.
[5] Michel, R. et J.P., Avouac, Deformation due to the 17 August Izmit
earthquake measured
from SPOT images, J. Geophys. Res., 107, 10 1029/2000JB000102, 2002.
[6] Van Puymbroeck, N., Michel, R., Binet, R., Avouac, J.P. and
Taboury, J. Measuring
earthquakes from optical satellite images, Applied Optics Information
Processing, 39,
23, 3486–3494, 2000.
Publications:
Leprince
S., Barbot S., Ayoub F., Avouac,
J.P. Automatic, Precise, Ortho-rectification and Co-registration for
Satellite Image Correlation, Application to Seismotectonics.
To be submitted.
Conferences:
F Levy, Y Hsu, M Simons, S Leprince, J Avouac.
Distribution of coseismic slip for the 1999 ChiChi Taiwan earthquake:
New data and implications of varying 3D fault geometry.
AGU 2005 Fall meeting, San Francisco.
M Taylor, S Leprince, J Avouac.
A Study of the 2002 Denali Co-seismic Displacement Using SPOT
Horizontal Offsets, Field Measurements, and Aerial Photographs.
AGU 2005 Fall meeting, San Francisco.
Y Kuo, F Ayoub, J Avouac, S Leprince, Y Chen, J H Shyu, Y Kuo.
Co-seismic Horizontal Ground Slips
of 1999 Chi-Chi Earthquake (Mw 7.6) Deduced From Image-Comparison of
Satellite SPOT and Aerial Photos. AGU 2005 Fall meeting,
San Francisco.