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PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
M a rch 2007 217
continued on page 219
Interferometric Synthetic
Aperture Radar (InSAR):
Its Past, Present and Future
by
Zhong Lu, Ohig Kwoun, and Russell Rykhus
Introduction
Very simply, interferometric synthetic aperture radar (InSAR)
involves the use of two or more synthetic aperture radar (SAR)
images of the same area to extract landscape topography and its
deformation patterns. A SAR system transmits electromagnetic
waves at a wavelength that can range from a few millimeters to
tens of centimeters and therefore can operate during day and night
under all-weather conditions. Using SAR processing technique (Cur
-
lander and McDonough, 1991), both the intensity and phase of the
reflected (or backscattered) radar signal of each ground resolution
element (a few meters to tens of meters) can be calculated in the
form of a complex-valued SAR image that represents the reflectiv
-
ity of the ground surface. The amplitude or intensity of the SAR
image is determined primarily by terrain slope, surface roughness,
and dielectric constants, whereas the phase of the SAR image is
determined primarily by the distance between the satellite antenna
and the ground targets. InSAR imaging utilizes the interaction of
electromagnetic waves, referred to as interference, to measure pre
-
cise distances between the satellite antenna and ground resolution
elements to derive landscape topography and its subtle change in
elevation.
InSAR Past
The launch of the ERS-1 satellite in 1991
significantly promoted the development of
InSAR techniques and applications. InSAR-
related research in the 1990s can be grouped
into three categories: deformation mapping,
DEM generation, and landscape characteriza
-
tion. Initial applications of InSAR included the
following,
Imaging earthquake displacement
InSAR was first applied to map the ground
surface displacement caused by the 1992
Landers earthquake (Massonnet and Feigl,
1998). Using a pair of SAR images, one
before the earthquake and the other after the
earthquake, early research focused on map
-
ping the co-seismic deformation with InSAR.
Surface displacement data are extraordinarily
useful for understanding slip distribution and
rupture dynamics during earthquakes, and InSAR has made an
indispensable contribution to seismology by providing earthquake
location, fault geometry and rupture dynamics from the measured
co-seismic deformation field. In the late 1990s, studies using InSAR
to map ground surface deformation immediately after an earth
-
quake (i.e., post-seismic deformation) yielded important clues to
infer the properties of the Earth’s crust and upper mantle.
Mapping ground surface deformation during
volcanic eruptions
Early studies used SAR data acquired before and after a volcanic
eruption to image the co-eruptive deformation. Surface deforma
-
tion data from InSAR can provide essential information about
magma dynamics. In the late 1990s, InSAR was used to map the
deformation of volcanoes during quiescent periods. InSAR-derived
surface deformation patterns shed important insights into the
structure, plumbing, and state of restless volcanoes, and can be the
first sign of increasing levels of volcanic activity, preceding swarms
of earthquakes or other precursors that signal impending intrusions
or eruptions (Lu, 2007) (Figure 1).
Figure 1. InSAR image shows six concentric fringes that represent about 17 cm of inflation cen-
tered on the southwest flank of Peulik, Alaska. Each fringe (full color cycle) represents 2.83 cm of
change between the ground and the satellite. The volcano inflated aseismically from October
1996 to September 1998, a period that included an intense earthquake swarm that started in May
1998 and was located over 30 km northwest of Peulik Volcano.
218 M a rch 2007
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
InSAR is formed by combining, or “interfering” radar signals from
two spatially or temporally separated antennas. The spatial separa-
tion of the two antennas is called the baseline. The two antennas
may be mounted on a single platform for simultaneous interferom-
etry, which is the usual implementation for aircraft and spaceborne
systems such as the Topographic SAR (TOPSAR) and the Shuttle
Radar Topography Mission (SRTM) systems that were created for
generating high-resolution, high-precision digital elevation models
(DEMs) over large regions. Alternatively, InSAR can be created by
using a single antenna on an airborne or spaceborne platform in
nearly identical repeating flight orbits for repeat-pass interferometry
(Massonnet and Feigl, 1998). In the latter case, even though the an-
tennas do not illuminate a given area at the same time, the two sets
of signals recorded during the two passes will be highly correlated if
the scattering properties of the ground surface remain undisturbed
between viewings. In this configuration, InSAR is capable of measur-
ing ground-surface deformation with centimeter-to-subcentimeter
precision at a spatial resolution of tens-of-meters over a large region.
This is the typical implementation for spaceborne sensors such as:
1. U.S. SEASAT (operated June to October, 1978, L-band,
wavelength λ = 25.0 cm),
2. European Remote-sensing Satellite (ERS-1) (operated 1991-2000,
C-band, λ = 5.66 cm),
3. Japanese Earth Resources Satellite (JERS-1) (operated 1992-1998,
L-band, λ = 23.5 cm),
4. Shuttle Imaging Radar-C (SIR-C) (operated April to October 1994,
X-, C-, and L-band, λ = 3.1 cm, 5.66 cm, and 24.0 cm,
respectively),
5. European Remote-sensing Satellite (ERS-2) (operating 1995-
present, C-band, λ = 5.66 cm),
6. Canadian Radar Satellite (Radarsat-1) (operating 1995-present,
C-band, λ = 5.66 cm),
7. European Environmental Satellite (Envisat) (operating 2002-
present, C-band, λ = 5.63 cm), and
8. Japanese Advanced Land Observing Satellite (ALOS) (operating
2006-present, L-band, λ = 23.6 cm).
An InSAR image (also called an interferogram) is created by co-
registering two SAR images and calculating the difference between
their corresponding phase values on a pixel-by-pixel basis. The
phase change (or range distance difference) in the original interfero-
gram is caused mainly by five effects: (1) differences in the satellite
orbits when the two SAR images were acquired, (2) landscape
topography, (3) ground deformation, (4) atmospheric propagation
delays, and (5) systematic and environmental noises. Knowledge
of a satellite’s position and attitude is required to remove the effect
caused by the differences in the satellite orbits of the two passes.
The topographic effects in the interferogram can be removed by
producing a synthetic interferogram created from an accurate DEM
and the knowledge of InSAR imaging geometry. The synthetic in-
terferogram is then subtracted from the interferogram to be studied
(Massonnet and Feigl, 1998). Alternatively, the topographic contri-
bution can be removed through the use of a different interferogram
of the same area. These procedures will remove the topography
effect from InSAR images, and the component of ground deforma-
tion along the satellite’s look direction can potentially be measured
with a precision of centimeter or sub-centimeter for C-band sensors,
and a few centimeters for L-band sensors. Because of problematic
tropospheric propagation delay and ionospheric disturbance, repeat
observations are critical to confidently interpret small geophysical
signals related to movements of the Earth’s surface. If the two SAR
images are acquired simultaneously (i.e., single-pass InSAR), or the
deformation during the SAR acquisition time is negligible, or can be
modeled and removed, then the InSAR image can be used to derive
a DEM (Lu et al., 2003). The single-pass InSAR is the fundamental
building block for the generation of the SRTM DEM.
How InSAR Works
Illustration of how InSAR works (image courtesy of Charles Wicks/USGS).
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
M a rch 2007 219
Figure 2. Radarsat-1 SAR intensity images over Yukon River Basin, Alaska acquired on a) August 17, 2003, b) September 10,
2003, and c) October 4, 2003. These SAR images show the procession of a fire that started in July of 2003. The derived fire
severity map is shown in Figure 2d.
Mapping of land surface deformation associated
with fluid withdrawal
Surface subsidence and uplift that were related to extraction and
injection of fluids in groundwater aquifers and petroleum reservoirs
can be seen in InSAR images. InSAR-based surface deforma
-
tion mapping can provide fundamental data on reservoir/aquifer
properties and processes, and improve the ability to assess and
mitigate adverse consequences. InSAR capability was also demon-
strated for mapping the slow movement of landslides, providing a
new tool for landslide monitoring.
Recording the movement of glaciers
InSAR was successfully applied to record the movement of glaciers
and ice fields, and significantly advanced the studies of glacier
and ice flows and ice-sheet mass balance. By regularly imaging
ice sheets over the Arctic, Antarctic, and Greenland, InSAR has
contributed to building an unprecedented series of snapshots
that document the short-term evolution of the ice sheet, aiding in
the understanding of their impact on sea level change and global
warming.
Mapping of water-level changes over wetlands
InSAR (particularly at longer wavelengths) was found to be an ef-
fective tool in the accurate measurement of water-level changes
in river valleys and wetlands. Calibrated by in-situ measurements,
the InSAR-derived water-level changes within wetlands will allow
precise estimation of volumetric changes in water storage which
can improve hydrological modeling predictions and enhance the
assessment of future flood events over wetlands.
continued from page 217
Use of InSAR to construct DEMs
InSAR was applied to construct DEMs over areas where the
photogrammetric approach to DEM generation was hindered by
inclement weather conditions. For example, repeat-pass InSAR
was used to generate ice surface topography that determined the
magnitude and direction of the gravitational force that drives ice
flow and ice dynamics. In addition, volcano surface topography
measurements from before and after an eruption were used to
estimate the volume of extruded material. There are many sources
of error in DEM construction from repeat-pass InSAR images:
inaccurate determination of the InSAR baseline, atmospheric delay
anomalies, and possible surface deformation due to tectonic,
volcanic, or other loading sources over the time interval spanned
by repeat-pass interferograms, etc. To generate a high-quality DEM
from repeat-pass InSAR images, these errors must be corrected (Lu
et al.
, 2003).
The study of landscape characterization
and changes
InSAR images and their associated products have proved useful for
mapping flood extents, fire scars, land cover types, changes in soil
moisture content, etc. For example, multiple SAR images can be
used to map the progression of fire and to estimate fire severity.
InSAR products that characterize the changes in SAR backscatter
-
ing return (both intensity and phase signal) are indispensable for
precise mapping of fire scar extents and severities (Figure 2).
continued on page 220
220 M a rch 2007
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
interseismic deformation. Combined with seismology and other
geophysical and geodetic measurements, InSAR can be expected
to aid many breakthroughs in understanding the entire phase of
the earthquake cycle (Wright, 2002).
InSAR Future
The next few years will witness more exciting technical and
scientific breakthroughs in many aspects of InSAR. First, longer
wavelength SAR images (such as L-band PALSAR onboard the
ALOS) will be available that will enable InSAR deformation map
-
ping at global scales where C-band InSAR can be plagued by loss
of coherent signal because of vegetation. Second, fully-polarized
SAR sensors (ALOS, Radarsat-2, TerraSAR-X, TanDEM-X, etc) will
allow better characterization of vegetation structure and ground
features. The combination of polarimetric and interferometric
analysis (called Pol-InSAR) will offer a new capability for landscape
mapping and deformation monitoring (Cloude and Papathanas
-
siou, 1998). Pol-InSAR will enable optimization procedures that
maximize the interferometric coherence and target decomposi
-
tion approaches to the separation of radar backscattering returns
from the canopy top, from the bulk volume of the vegetation, and
from the ground surface. The difference in interferometric phase
measurement then leads to the difference in height between the
physical scatterers that possess these mechanisms. Accordingly,
future Pol-InSAR instruments will enable significant advances in
many fields of application: 1) land cover mapping and wetland
mapping, particularly over regions where weather conditions
hinder optical remote sensing; 2) inferring soil moisture with a
horizontal resolution (several meters) that is not attainable other
-
wise; 3) mapping forest height and biomass with the generation of
“bare-earth” DEMs; 4) monitoring ship traffic on the oceans, and
much more.
A third breakthrough is ScanSAR, an advanced SAR imaging
technique achieved by periodically switching the antenna look
angle into neighboring subswaths in the range direction in order
to increase the size of accessible range swath. ScanSAR will be
equipped with InSAR capability to enhance spatial coverage of
InSAR Present
Deformation mapping with InSAR
has advanced from the interpreta
-
tion of a few InSAR image pairs
to the analysis of multi-temporal,
time-series InSAR images. The
ultimate goal of the time-se-
ries analysis has been to reduce
artifacts due to atmospheric delay
anomalies, orbit errors, and loss of
coherence measurements in order
to improve the accuracy of defor
-
mation measurements. Stacking
and least-squares inversion ap
-
proaches, which take into account
covariance characteristics of data
distribution, have been applied
to multi-temporal InSAR images
to reduce atmospheric delay
anomalies and improve tempo
-
ral sampling in order to reveal
transient, dynamic deformation
patterns.
Persistent Scatterer (PS) InSAR (PSInSAR) represents the most
significant advancement in InSAR research. PSInSAR uses unique
characteristics of atmospheric delay anomalies and the distinctive
backscattering of certain ground targets (called PS) to improve the
accuracy of conventional InSAR deformation measurements from
10-20 mm to 2-3 mm (Ferretti et al., 2001). The SAR backscatter
-
ing signal of a PS target has broadband spectra in the frequency
domain, implying that the radar phase of this kind of scatterer
correlates over much longer temporal intervals and over much
larger baseline separations than other scatterers. As a result, if the
backscattering return of a pixel is dominated by PS(s), this pixel
will always be coherent over long time intervals. At PS pixels,
the difficulty of decorrelation in conventional InSAR can therefore
be overcome. In addition, the atmospheric contribution is rather
smooth spatially and is independent over time. At PS pixels,
the atmospheric contribution to the backscattered signal can be
identified and removed from the data using a multi-interferogram
approach. Therefore, the ultimate goal of PSInSAR processing is to
separate the different contributions (surface deformation, atmo
-
spheric delay anomaly, DEM error, orbit error, and decorrelation
noise) by means of least-squares estimations and iterations, taking
into account the spatio-temporal distribution and the correlation
between the PS samples. After removing errors due to the atmo
-
spheric anomaly, orbit error, and DEM error, deformation histories
at PS points can be appreciated at millimeter accuracy (Figure 3).
PSInSAR has been successfully applied to monitor landslides, urban
subsidence, fault movement, and volcanic deformation.
In the meantime, applications of InSAR have made many
ground-breaking discoveries in Earth science. For example, in
earthquake study, InSAR has played an increasingly important role
in mapping triggered slip, which occurs during an earthquake on
a fault or faults not involved in the main shock ¬¬and is therefore
extremely difficult to measure with conventional technology. InSAR
is ideally suited to detect triggered slip because of its high spatial
resolution, high measurement precision, and large areal coverage.
In addition, InSAR can identify blind faults from the surface defor-
mation patterns. Furthermore, InSAR has great potential to monitor
Figure 3. Average deformation image of New Orleans, southeastern Louisiana during 1992-1998, derived
from multiple temporal InSAR images based on PSInSAR technique.
continued from page 219
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
M a rch 2007 221
conventional InSAR for large-scale deformation measurement and
to improve temporal sampling of InSAR deformation images (Guar
-
nieri and Rocca, 1999). Fourth, the atmospheric delays that hamper
InSAR accuracy will be lessened by routinely estimating water-
vapor content using a high-resolution weather model, continuous
global positioning system (CGPS) network, or other satellite sensors
such as the Moderate Resolution Imaging Spectroradiometer
(MODIS), Advanced Spaceborne Thermal Emission and Reflection
Radiometer (ASTER), and European Medium Resolution Imaging
Spectrometer (MERIS) to improve InSAR deformation measure
-
ments (Foster et al., 2006). Fifth, advances in multi-temporal,
multi-dimensional data-mining techniques (such as PSInSAR) will
continue to improve deformation measurement, which will enable
the mapping of time-variant ground surface deformation caused by
many natural and man-made hazards.
Finally, automated SAR and InSAR processing systems will be
more widely available, which will improve SAR/InSAR process
-
ing throughput and lay the foundation for routine monitoring of
natural hazards and natural resources. Because more satellite radar
sensors and radar satellite constellations become available in the
next decade, the automated SAR/InSAR processing system is of
paramount importance for near-real-time decision support.
Conclusion
InSAR is one of the fastest growing fields in Earth science and
remote sensing. The precise land surface topography and their
time-transient variability provided by InSAR systems will accelerate
development of predictive models that can anticipate the behavior
of many natural hazards such as volcanic eruptions, earthquakes,
landslides, and others. In addition, InSAR will provide tools to
better characterize the contribution of ground water, surface water,
soil moisture, and snow to the global fresh water budget, and the
role of glaciers and ice sheets in sea level rise and global warming.
Furthermore, InSAR will offer the capability of imaging the three-
dimensional structure of vegetation on a global scale for improved
characterization and management of Earth’s resources. With more
and more operational SAR sensors available for rapid data acquisi
-
tions, armed with state-of-the-art information technologies such as
data-mining and grid computation, InSAR will continue to address
and provide solutions to many scientific questions related to natu
-
ral hazard monitoring and natural resource management.
Acknowledgments
ERS-1/-2 and Radarsat-1 SAR images are copyrighted European
Space Agency (ESA) and Canadian Space Agency (CSA), respec
-
tively, and were provided by the Alaska Satellite Facility (ASF)
and ESA. This work was supported by funding from the NASA,
the USGS Land Remote Sensing Program, and the USGS Volcano
Hazards Program. Technical reviews by B. Wylie and C. Wicks are
greatly appreciated. We thank C. Wicks for providing the figure
illustrating how InSAR works.
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Authors
Zhong Lu
U.S. Geological Survey (USGS), Earth Resources Observation &
Science (EROS) Center and David A Johnston Cascades Volcano
Observatory, 1300 SE Cardinal Court, Vancouver, WA 98683-9589
phone: (360) 993 8911; email: lu@usgs.gov
Ohig Kwoun
Science Applications International Corporation (SAIC), Contractor
to USGS EROS Center, 47914 252nd Street, Sioux Falls, SD 57198
phone: (605) 594 6153; email: okwoun@usgs.gov
Russell Rykhus
Science Applications International Corporation (SAIC), Contractor
to USGS EROS Center, 47914 252nd Street, Sioux Falls, SD 57198
phone: (605) 594 6121; email: rykhus@usgs.gov
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