GDR INSAR & GDR STRAINSARFeigl et al.2018-10-07
Final Report of GDR STRAINSAR
Bilan scientifique du
GDR INSAR (1997-2000) et du GDR STRAINSAR (2001-2004)
For consideration by section 18 of the CNRS
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File nameBilan2005GDRstrainsar1.doc
Kurt L. Feigl
Department of Terrestrial and Planetary Dynamics (UMR 5562)
Centre National de la Recherche Scientifique
14 ave. E. Belin
31400 Toulouse
France
Fax. +33 5 61 33 29 00
Table of contents
Table of contents
People
Geodetic Techniques For Measuring Deformation Using Satellite Data
GPS
SAR interferometry
Correlation of two optical images acquired by optical satellites such as SPOT
Correlation of two SAR backscatter images acquired by the radar satellites such as ERS
Advances published between 1997 and 2004
Coseismic deformation for earthquakes
Volcanos
Landslides and subsidence
Glaciers
Interseismic Deformation
Postseismic Deformation
Troposphere
Orbits
Satellite missions
Services Provided by GDR INSAR and GDR STRAINSAR
mail list ()
Catalog of ERS-1 and ERS-2 orbits
Software for selecting interferometrically compatible pairs from ERS-1 and ERS-2 catalog
Software for filtering interferograms
Future Satellite Missions
Subscribers to mail list (2005)
Glossary
Acknowledgments
Bibliography of GDR INSAR and GDR STRAINSAR
1993-1994
GDR INSAR (1995-1999) – 53 peer-reviewed publications
GDR STRAINSAR (2000-2005) 98 peer-reviewed publications
Theses
Selected conference proceedings 1997- 2000
Other References Cited
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GDR INSAR & GDR STRAINSARFeigl et al.2018-10-07
People
Our community includes:
Over 100 people subscribed to the mail list ()
See section below entitled “Subscribers to mail list ”.
The authors of over 150publications in peer-reviewed journals between 1997 and 2005
See section below entitled “Bibliography of GDR INSAR”.
Over a dozen doctoral degrees related to INSAR between 1997 and 2005
See section below entitled “Theses”.
Over 50 people have participated in DIAPASON short courses since 1997
Geodetic Techniques For Measuring Deformation Using Satellite Data
Tectonic geodesy took a great leap forward when we published the first coseismic interferogram on the cover of Nature in the summer of 1993 [Massonnet et al., 1993]. Twelve years later, in 2005, interferometry on synthetic aperture radar images (INSAR) has become a widely used and widely accepted geophysical technique for measuring topography and deformation of the Earth’s lithosphere and cryosphere. Confronted with conventional models, these INSAR measurements have significantly advanced the study of earthquakes, volcanos, landslides, subsidence and glaciers.
GPS
The Global Positioning System can achieve sub-centimeter estimates of relative position with a relatively inexpensive and lightweight instrument for less than “10 kg, 10 Watts, and 10 $K”. Since the most precise solutions involve post-processing data from multiple instruments, it typically requires several days between acquisition and estimate. The constellation of satellites came into use gradually beginning in 1985 and becoming fully operational in 1992. Data from this early period are typically more difficult to analyze and may yield less precise results than more recent surveys. For reviews of geophysical applications, see Dixon[1991], Hager et al.,[1991], and Segall and Davis[1997]. For earthquake studies, GPS networks tend to operate in one of two end-member modes: Continuous operation of permanently installed, widely-spaced antennas (CGPS), or intermittent occupation of densely-spaced benchmarks in “campaign” mode. The former offers good temporal resolution (1 measurement/30 seconds = 33 mHz) but poor spatial resolution (> 100 km between stations), while the latter offers poor temporal resolution (1 measurement/year = 32 nHz) and good spatial resolution (~10 km between stations). This trade-off between temporal and spatial resolution creates a difficult decision in the face of limited resources. Although a compromise “hybrid” strategy could rotate expensive receivers on a roughly monthly basis through several fixed monuments, this approach has yet to be deployed, apparently because it requires more manpower than permanent installations.
Figure 1. Left: Map of Izmit region showing GPS sites (4-character, named sites are continuous stations operating before and after the main shock; two additional continuous stations used in this study are located off the map at 40.61°N, 27.59°E, and 40.97°N, 27.96°E) and observed (including 95% confidence ellipses) and modeled (yellow arrows) horizontal coseismic displacements relative to a station in Ankara, Turkey (ANKR, located at 39.89°N, 32.76°E). The five segment fault model used to investigate slip distribution the Izmit earthquake epicenter and focal mechanism from the Harvard CMT Catalog ( and pre-earthquake seismicity ( are also shown. Light lines are mapped or inferred faults [Barka, 1997]. MV = MudurnuValley fault. Right: Map of observed postseismic GPS station displacements (black arrows) relative to ANKR (located at 39.89°N, 32.76°E) during the first 75 days following the earthquake. Error ellipses indicate 95% confidence intervals. Modeled station displacements (yellow arrows) were computed with the slip distributed dislocation model shown in Fig. 3C. Station names (four-character ID) indicate continuously operating sites installed within 48 hours following the main shock. Red dots indicate aftershocks of the first 30 days. The blue dotted line indicates the fault geometry used in the postseismic model inversions (note that the fault is extended to the east of the coseismic fault model to include the Duzce segment). The "beach ball" shows the location and focal mechanism of the MW 7.2, 12 November 1999, Düzce earthquake. From Reilinger et al.[2000].
SAR interferometry
This geodetic technique calculates the interference pattern caused by the phase difference between two images acquired by a spaceborne synthetic aperture radar (SAR) at two distinct times. The resulting interferogram is a contour map of the change in distance between the ground and the radar instrument. Each fringe represents a range change of half the wavelength. Thus, the contour interval is 28 mm for C-band radars such as ERS and RADARSAT and roughly four times larger, 125 mm for the L-band JERS satellite. These maps provide an unsurpassed spatial sampling density (~100 pixels/km2), a competitive precision (~1 cm) and a useful observation cadence (1pass/month), as described in a review article by Massonnet and Feigl [1998], which I paraphrase here.
To capture an earthquake, INSAR requires three data sets: a SAR image before the earthquake, one after, and topographic information. The SAR images themselves are rich data sets well documented in the remote sensing literature [Curlander and McDonough, 1991; Henderson and Lewis, 1998]
The topographic information is necessary to model and remove the interferometric fringes caused by topographic relief as “seen in stereo” from slightly different points of view. To handle the topographic contribution, we can choose between the “two-pass” approach, [e.g., Massonnet and Feigl, 1998] and the “three-pass” or “double-difference” approach [e.g., Zebker et al., 1994]. For tectonic studies, there is usually a trade-off between the two-pass approach, which requires a digital elevation model (DEM), and the three-pass approach, which requires a third SAR acquisition. Further discussion of relative merits of the two- and three-pass approaches are beyond the scope of this chapter.
To interpret an interferogram, one must understand how different effects contribute to the fringe pattern. Many instructive examples appear in review papers by Massonnet and Feigl [1998] and Madsen and Zebker [1998]. The mathematical details appear in another review [Bamler and Hartl, 1998]. For earthquake studies, the most important effects involve topographic relief, orbital trajectories, and tropospheric refraction, usually in combination.
If the topographic information (a DEM for two-pass, or the “topo pair” in three-pass INSAR) is in error, the interferogram will contain artifactual fringes. They appear in the same location in every interferogram produced using that topographic model. To quantify this effect, Massonnet and Rabaute [1993] define the altitude of ambiguity ha , or the shift in altitude needed to produce one topographic fringe. Indeed, this parameter is inversely proportional to the perpendicular component of the (“baseline”) vector separating the two orbital trajectories, conventionally written B, pronounced “B-perp”, and given in meters [Zebker and Goldstein, 1986]. The number of “topographic” fringes is proportional to B and inversely proportional to ha. Thus we seek pairs of orbital trajectories with a small separation, that is, with small (absolute) values of B and large (absolute) values of ha for earthquake studies. It turns out that for the ERS satellites, an acceptably good orbital pair has both B and ha approximately equal to 100 m.
A topographic error of meters in the DEM will produce a phase error of /ha fringes in the resulting interferogram. Errors in typical DEMs range from 10 to 30 m [Wolf and Wingham, 1992], implying that choosing a pair of images with |ha | between 20 and 60 m will yield an interferometric measurement with an error better than /ha = ± 1/2 cycle, or ± 14 mm for ERS. Small values of |ha | can mask even large signals with artifactual topographic fringes. In an extreme (and rare) case, Massonnet and Feigl [1995a] uncovered a topographic error of ~250m, roughly 8 times larger than the published precision for the DEM. This artifact resembles the fringe pattern produced by a small earthquake. Avoiding such confusion requires looking at several interferograms with different values of ha. For an earthquake, the number of coseismic fringes does not depend on ha.
Atmospheric effects can also complicate the interpretation of an interferogram. Indeed, variations in the refractive index of the troposphere are the current limiting source of error in the INSAR technique [Delacourt et al., 1998; Goldstein, 1995; Hanssen, 1998; Massonnet and Feigl, 1995a; Rosen et al., 1996; Tarayre and Massonnet, 1996; Williams et al., 1998; Zebker et al., 1997]. Potentially, one could confuse a topographic signature with a displacement, if propagation effects create fringes which "hug" the topography like contour lines, but which measure the change in tropospheric delay, as first observed as several concentric fringes on a 1-day interferogram on Mount Etna [Massonnet and Feigl, 1998];. One can recognize this subtle effect by pair-wise logic [Massonnet and Feigl, 1995a] or using the DEM and local meteorological observations [Delacourt et al., 1998; Williams et al., 1998]. Yet separating the tropospheric noise from the deformation signal can be challenging, particularly when the signal is small, e.g. the magnitude 5.2 St. Paul de Fenouillet earthquake [Rigo and Massonnet, 1999].
Correlation of two optical images acquired by optical satellites such as SPOT
It is also possible to detect (large) coseismic displacements by correlating two optical images. The “lag” vectors estimated between the corresponding sub-pixel cells of a pre-quake and a post-quake image yields the horizontal components of the coseismic displacement vector with sub-meter precision and hectometer resolution [Crippen, 1992; Crippen and Blom, 1992; Vadon and Massonnet, 2000; VanPuymbroeck et al., 2000]. To capture the Izmit earthquake of August 17, two groups have correlated optical images acquired by the SPOT4 satellite on July 9 and the SPOT2 satellite on September 16, after anti-aliasing resampling [Michel and Avouac, 2000; Vadon and Massonnet, 2000].
The result is a measurement of the offset between the two images at each 20-meter pixel where the correlation succeeds. In this case, lines of the SPOT images are almost parallel to the fault, we use only the offset in columns to determine the horizontal component of displacement in the direction S77°E. Although the two images were acquired in very similar geometric configurations, the correlation map still shows the effects of slight differences in spacecraft position and sensor attitude. Michel and Avouac [2000] model these explicitly, while Vadon and Massonnet [2000] model them empirically with a biquadratic polynomial fit. These results are shown in Error! Reference source not found. and Figure 2, respectively. As Michel and Avouac write, SPOT images can also be used to map accurately the fault zone and determine the slip distribution by sub-pixel correlation of images acquired before and after an earthquake. It reveals a less than 100m wide and very linear fault zone that can be traced for 70km from Gölcük to Akyazi. The obtained slip distribution compares well with the field measurements, and is consistent with ground deformation measured at some distance from the fault zone using SAR images. Very little slip was absorbed off the main fault plane.” [Michel and Avouac, 2000].
Both these maps show a discontinuity corresponding to the trace of surface rupture mapped between the east end of the bay at Izmit and SapancaLake. The mean offset between two 5-by-20-km blocks on opposite sides of the fault is 4.60 ± 0.24 m. After median filtering with a 2-by-2-km window, Feigl et al. [2001] retain 148 values.
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GDR INSAR & GDR STRAINSARFeigl et al.2018-10-07
Figure 2. Component at S77°E of the coseismic displacement field measured by correlation of SPOT images. As described by Vadon and Massonnet (2000), these images were acquired on July 9 and September 16, 1999. These original 20-m pixels have been filtered using a 2-dimensional median filter on a 100-by-100-m window [Feigl et al., 2001].
Berthier Izmit Figure
Figure 3. The left panel shows the offsets in longitude determined by correlating two SPOT images acquired on 9 July and 16 September 1999. A clear discontinuity in the offset field indicate the location of the surface rupture. Area where the correlation failed are displayed in grey. The location and co-sismic deformation recorded at 4 GPS stations are also added. The right panel represent the slip along the surface rupture as a function of longitude. The blue dots represent the mean slip every 300 meters; the red dots a running average over 3-km segments[Berthier, 2005].
Correlation of two SAR backscatter images acquired by the radar satellites such as ERS
A similar correlation technique also applies to SAR images. By correlating two Single Look Complex (SLC) SAR amplitude (“backscatter”) images acquired at different times, Michel et al. [1999a] measured ground displacements for the Landers earthquake. Their result is “a two-dimensional displacement field with independent measurements every about 128m in azimuth and 250m in range. The accuracy depends on the characteristics of the images. For the Landers test case discussed in the study, the 1- uncertainty is 0.8m in range and 0.4 m in azimuth. [They] show that this measurement provides a map of major surface fault ruptures accurate to better than 1km and an information on coseismic deformation comparable to the 92 GPS measurements available. Although less accurate, this technique is more robust than SAR interferometry and provides a complementary information since interferograms are only sensitive to the displacement in range.” [Michel et al., 1999a]. Its greatest potential is for measuring cryospheric deformation, where flow can be sufficiently rapid ( > 10 cm/day) to allow detection in the short time (1, 3 or 35 days) between ERS acquisitions [Michel, 1997; Michel and Rignot, 1999].
For the Izmit earthquake, however, Sarti et al.[2000] find less accurate results than at Landers. Using multiple scales for their correlation cells, they find the range component of the coseismic displacement with a scatter in excess of a meter. Indeed, it is difficult to discern even the trace of the fault in the map of ERS range offsets (Figure 4). Consequently, Feigl et al.[2001] do not include these data in their inversion.
Figure 4. Component at S77°E of the coseismic displacement field measured by correlation of two ERS images, as described by Sarti et al. (2000). Note that discontinuity in these measurements does not follow the mapped trace of the fault (crosses) as well as the SPOT correlation map [Feigl et al., 2001].
Advances published between 1997 and 2004
Coseismic deformation for earthquakes
INSAR has now captured over a dozen earthquakes in the act of permanently deforming the Earth’s surface (Table 1.)
Table 1. Earthquake studies estimating parameters from satellite geodetic measurements using INSAR as compiled from the literature [Feigl, 2002; Funning, 2005].
Location / MW / Date / InSARLanders,CA,USA / 7.3 / 1992-06-28 / [Fialko, 2004c]
Litle Skull Mountain, CA, USA / 5.6 / 1992-06-29 / [Lohman, et al., 2002]
Fawnskin, CA,USA / 5.4 / 1992-12-02 / [Feigl, et al., 1995]
Ngamring County, Tibet / 6.1 / 1993-03-20 / [Funning, 2005]
Eureka Valley, CA, USA / 6.1 / 1993-05-17 / [Massonnet and Feigl, 1995]
Northridge, CA, USA / 6.7 / 1994-01-17 / [Massonnet, et al., 1996]
Double Spring Flat, NV, USA / 6.0 / 1994-09-12 / [Amelung and Bell, 2003]
Kobe, Japan / 6.9 / 1995-01-17 / [Ozawa, et al., 1997]
Grevena, Greece / 6.6 / 1995-05-13 / [Bernard, et al., 1997b]
Neftegorsk, Sakhalin, Russia / 7.2 / 1995-05-27 / [Tobita, et al., 1998]
Aigion, Greece / 6.2 / 1995-06-15 / [Bernard, et al., 1997a]
Antofagasta, Chile / 8.1 / 1995-07-20 / [Pritchard, et al., 2002b]
Dinar, Turkey / 6.3 / 1995-10-01 / [Funning, 2005]
Nuweiba, Egypt / 7.3 / 1995-11-22 / [Shamir, et al., 2003]
St Paulde Fenouillet, France / 5.0 / 1996-02-26 / [Rigo and Massonnet, 1998]
Nazca Ridge, Peru / 7.7 / 1996-11-12 / [Delouis, et al., 2002]
Kagoshima-ken-hokuseibu, Japan / 6.1 / 1997-03-26 / [Fujiwara, et al., 1998]
Manyi, Tibet / 7.5 / 1997-11-08 / [Funning, 2005]
Zhangbei-Shangyi, China / 6.2 / 1998-01-10 / [Zhang, et al., 2002]
Fandoqa, Iran / 6.6 / 1998-03-14 / [Funning, 2005]
Mt Iwate, Japan / 6.1 / 1998-09-03 / [Nishimura, et al., 2001]
Aiquile, Bolivia / 6.6 / 1998-05-22 / [Funning, et al., 2005]
Izmit, Turkey / 7.4 / 1999-08-17 / [Cakir, et al., 2003]
Athens, Greece / 6.0 / 1999-09-07 / [Kontoes, et al., 2000]
Colfiorito, Italy / 5.7 / 1999-09-26 / [Salvi, et al., 2000]
Colfiorito, Italy / 6.0 / 1999-09-26 / [Salvi, et al., 2000]
Hector Mine, CA, USA / 7.1 / 1999-10-16 / [Simons, et al., 2002]
Duzce, Turkey / 7.1 / 1999-11-12 / [Bürgmann, et al., 2002]
Cankiri, Turkey / 6.0 / 2000-06-06 / [Wright, 2000]
S Iceland Seismic Zone, Iceland / 6.5 / 2000-06-17 / [Pedersen, et al., 2003]
S Iceland Seismic Zone, Iceland / 6.4 / 2000-06-21 / [Pedersen, et al., 2003]
Nisqually, WA, USA / 6.8 / 2001-02-28 / [Bustin, et al., 2004]
Arequipa, Peru / 8.5 / 2001-06-23 / [Pritchard, et al., 2002a]
Kokoxili, Tibet / 7.8 / 2001-11-14 / [Lasserre, et al., 2002]
Nenana Mountain, AK, USA / 6.7 / 2002-10-23 / [Wright, et al., 2003]
Denali, AK, USA / 7.9 / 2002-11-03 / [Wright, et al., 2003]
Bam, Iran / 6.6 / 2003-12-26 / [Funning, 2005]
Volcanos
Volcanos continue to be the most fruitful target for INSAR studies. We know the location of the most active ones. We know that shield volcanos produce better fringe patterns than stratovolcanos [Massonnet and Sigmundsson, 2000; Zebker et al., 2000]. We know how to choose images to optimize radar correlation, by considering ground, weather, and orbit conditions. Techniques for separating tropospheric artifacts from deformation signals are are particularly useful in this case[e.g., Beauducel et al., 2000a].
For these reasons, INSAR on volcanos is now fully validated. The feasibility studies of the past few years have proven the concept. It works! Progress in the next few years will come from operational monitoring of many volcanos. This will require routine acquisitions every time the satellite passes over the volcano. Although some may argue against the utility of acquiring SAR images during the winter when there is snow on the ground, simple comparison of SAR images (without interferometry) has already revealed a subglacial eruption [Alsdorf and Smith, 1999].
Landslides and subsidence
[Carnec, 1996; Carnec and Delacourt, 2000; Carnec and Fabriol, 1999; Carnec et al., 1996; Delacourt, 1997; Delacourt et al., 2000; Fruneau et al., 1996].
Glaciers
[Joughin et al., 1996a; Joughin et al., 1996b; Joughin, 1995; Joughin et al., 1998; Joughin et al., 1995; Legresy et al., 2000; MacAyeal et al., 1998; Michel and Rignot, 1999; Rignot, 1996a; Rignot, 1996b; Rignot, 1997; Rignot et al., 1996; Rignot et al., 1995; Rignot, 1998].