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Interferometric Synthetic Aperture Radar (InSAR): Its Past, Present and Future

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Interferometric Synthetic
Aperture Radar (InSAR):
Its Past, Present and Future
Zhong Lu, Ohig Kwoun, and Russell Rykhus
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
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
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
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,
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).
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
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
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
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
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.
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.
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.
Cloude S., and K. Papathanassiou, 1998. Polarimetric SAR interferom-
IEEE Trans. Geosci. Remote Sensing
, 36, 1551-1565.
Curlander, J., and R. McDonough, 1991.
Synthetic aperture radar
systems and signal processing
, New York: John Wiley & Sons.
Ferretti, A., C. Prati, and F. Rocca, 2001. Permanent scatterers in SAR
IEEE Trans. Geosci. Remote Sensing
, 39, 8-20.
Foster, J., and others, 2006. Mitigating atmospheric noise for InSAR
using a high resolution weather model,
Geophy. Res. Lett.
, 33,
L16304, doi:10.1029/2006GL026781.
Guarnieri, A.M., and F. Rocca, 1999. Combination of Low- and High-
Resolution SAR Images for Differential Interferometry,
IEEE Trans.
Geosci. Remote Sensing
, 37, 2035-2049.
Lu, Z., E. Fielding, M. Patrick, and C. Trautwein, 2003. Estimating lava
volume by precision combination of multiple baseline spaceborne
and airborne interferometric synthetic aperture radar: the 1997
eruption of Okmok volcano, Alaska,
IEEE Trans. Geosci. Remote
, 41, 1428-1436.
Lu, Z., 2007. InSAR Imaging of Volcanic Deformation Over Cloud-
prone Areas—Aleutian Islands,
Photogrammetric Engineering &
Remote Sensing
, 245-257.
Massonnet, D., and K. Feigl, 1998. Radar interferometry and its
application to changes in the Earth’s surface,
Rev. Geophys.
, 36,
Wright, T., 2002. Remote monitoring of the earthquake cycle us
ing satellite radar interferometry,
Phil. Trans. R. Soc. Lond.
, 360,
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:
Ohig Kwoun
Science Applications International Corporation (SAIC), Contractor
to USGS EROS Center, 47914 252nd Street, Sioux Falls, SD 57198
phone: (605) 594 6153; email:
Russell Rykhus
Science Applications International Corporation (SAIC), Contractor
to USGS EROS Center, 47914 252nd Street, Sioux Falls, SD 57198
phone: (605) 594 6121; email:
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... High acquisition cost is a hindrance in using LiDAR datasets in some developing countries (Muhadi et al., 2020). IfSAR, also termed InSAR, on the other hand, is considered a relatively cheaper and complementary 3-D mapping technology with varying applications in many fields including flood simulations and mapping flood hazards (Lu et al., 2007). It is more cost-effective compared to LiDAR and is readily available for use in flood modeling with quality and accuracy of results higher than other satellite systems (Gopal, 2010). ...
... In the Philippines, the LiDAR data was made available through the Data Acquisition Component (DAC) of the University of the Philippines-Disaster Risk and Exposure Assessment for Mitigation (UP-DREAM) and Phil-LiDAR Programs of the UP Training Center for Applied Geodesy and Photogrammetry (UP-TCAGP) supported by the Department of Science and Technology (DOST) (Makinano- Santillan et al., 2019). On the other hand, the IfSAR technology utilizes a Synthetic Aperture Radar (SAR) system of two or more images of the same extracted area (Lu et al., 2007). The data is formed from two radar images of the recorded phase and amplitude using microwave echoes, a combination of conventional SAR and interferometry techniques (Smith, 2002). ...
... The data is formed from two radar images of the recorded phase and amplitude using microwave echoes, a combination of conventional SAR and interferometry techniques (Smith, 2002). The interaction of electromagnetic waves measures the precise distance between satellite antenna and ground resolution elements, deriving landscape topography of subtle elevation changes (Lu et al., 2007). The available IfSAR data in the Philippines from the National Mapping and Resource Information Authority (NAMRIA) has a resolution of 5 m with 1 m RMSE vertical accuracy and 2 m RMSE horizontal accuracy (Belen, 2015). ...
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BACKGROUND AND OBJECTIVES: Fine topographic information is a key input parameter for a detailed flood simulation and mapping. This study aimed to compare the accuracy statistics of the flood models developed using the digital elevation datasets with different resolutions from the light detection and ranging and interferometric synthetic aperture radar systems. METHODS: The study applied the Hydrologic Engineering Center-Hydrologic Modeling System and Hydrologic Engineering Center-River Analysis System models workable within the geographic information system to simulate and map flood hazards in Maapag Watershed. The models’ validity and accuracy were tested using the confusion error matrix, f-measurement, and the root means square error statistics. FINDINGS: Results show that using the light detection and ranging dataset, the model is accurate at 88%, 0.61, and 0.41; while using the interferometric synthetic aperture radar dataset, the model is accurate at 76%, 0.34, 0.53; for the error matrix, f-measurement, and root mean square error; respectively. CONCLUSION: The model developed using the light detection and ranging dataset showed higher accuracy than the model developed using the interferometric synthetic aperture radar. Nevertheless, the latter can be used for flood simulation and mapping as an alternative to the former considering the cost of model implementation and the smaller degree of accuracy residual error. Hence, flood modelers particularly from local authorities prefer to use coarser datasets to optimize the budget for flood simulation and mapping undertakings.
... The technique can be used for detection and monitoring of ground displacement, which can be measured in the Line of Sight (LoS) of the SAR sensor (Carnec and Delacourt, 2000;Casagli et al., 2016;Castaneda et al., 2009) Kandregula et al., 2021). The Interferrometric Synthetic Aperature Radar (InSAR) and Differential Synthetic Aperture Radar Interferometry (DInSAR) can detect the change in the surface over the period of time in the LoS very efficiently (Lu et al., 2007;Lubis et al., 2011;Maruo, 1979;Massonnet et al., 1994;Ostir and Marko, 2007;Peltzer et al., 1999;Perissin, 2016;Putri et al., 2013;Rodriguez and Martin, 1992;Salvi et al., 2004;Stockamp et al., 2015;Virk et al., 2019;Zebker et al., 1994;Zebker and Villasenor, 1992;Ludwig et al., 2000) (Ostir and Marko, 2007). However, the PSI (Persistent Scatterer Interferometry) is more precise method of InSAR, which uses consistent radar targets, which are distinctly identifiable in all Synthetic Aperture Radar (SAR) images (Ferretti et al., 2001). ...
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Active surface deformation, displacement pattern, and erosional variability is estimated using the geomorphologically sensitive morphometry along with the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique using the SENTINEL-1A data (119 images) acquired between 07-02-2017 and 10-02-2021. The average velocities for this are estimated to be between ±11mm/y. The Raunthi River catchment from where the flood was triggered is undergoing ∼8 mm/y subsidence and ∼10mm/y uplift. Compared to this the basin wide deformation (Rishiganga basin) is estimated to be around ±10mm/y with ground displacement of around ±45mm/y. The times series analysis suggests an increase in the ground displacement by around 5mm/y and seems to be responsible for the expansion pre-existing cracks in the vicinity of the Vaikrita Thrust (VT) and subsequent failure of the northern face of Nandi Peak on 7th February. The GPS derived strain distribution pattern indicate a relatively higher accumulation of strain (>0.35 µ strain/yr). The normalized steepness index (ksn) variation along the longitudinal section of Rishiganga and Raunthi River sub-basin which shows anomalous increase at the glacio-fluvial transitional processes. Moreover, the χ profiles as well as planform plots shows anomalously lower values within the Raunthi River sub-basin when compared with the Rishiganga basin. Based on the lower values of χ it is observed that Raunthi River sub-basin is undergoing high erosion which can be due to the presence of sheared lithology and incision of the relict glacial and paraglacial sediments. We negate the suggestion that abrupt rise in the temperature was the major triggering mechanism for the recent disaster, instead it the sheared lithology and pre-existing fissure developed because of differential uplift and subsidence in Raunthi River that led to the wedge failure and subsequent flash flood. Had the climate was the major driver of the recent tragedy, it should have impacted multiple hanging glaciers in the Rishi Ganga valley. Therefore, the study calls for detailed geomorphological, structural and glaciological investigation in regions dominated by glacial and paraglacial processes in the strategic regions of Himalaya. Towards this, the state of art Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique seems to provide fast and reliable statures of terrain instability/stability along with identify potential areas of slope failures in near future in the glacial and preglacial zones.
... (or more frequent) surface displacement maps with a precision of the order of a few 51 millimeters (Lu et al., 2007) or even at sub-millimeter scale for relative rates over small 52 distances (Rucci et al., 2012). InSAR has already proven to be a powerful and cost 53 effective technique for ground deformation observations because of its high spatial 54 resolution (20 m × 20 m or better), wide spatial coverage (~100 km), and day-and-night 55 and all-weather imaging capability (Galloway et al, 1998;Massonnet and Feigl 1998;56 Rosen et al., 2000). ...
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Ground deformation related to aquifer exploitation can cause damage to buildings and infrastructure leading to significant economic losses. Understanding reservoir behavior helps in assessing possible future ground movements and water depletion hazards of a region under study. We have developed an ensemble-based data assimilation framework for groundwater reservoirs that efficiently incorporates Interferometric Synthetic Aperture Radar (InSAR) data for improved reservoir management and forecasts. Using the groundwater modeling software MODFLOW, we progressively calibrate model parameters such as transmissivity and elastic skeletal storage coefficients while simultaneously providing an estimate of the model parameter uncertainties. A 2D and layered aquifer models were built to demonstrate the capability of the ensemble method incorporating simulated InSAR surface displacement measurements. We find from these numerical tests that including both InSAR and well water level data as observations improves the RMSE of the transmissivity estimates by up to 15% and elastic skeletal storage coefficient estimates more than 50% comparing to using only one type of observation. The results suggest that the high spatial resolution subsidence observations from InSAR help to quantify hydraulic parameters and should lead to better groundwater reservoir management and forecasts.
... As a powerful tool of modern geodesy, InSAR has been widely and effectively used in geological disaster monitoring. Compared with traditional surveying and mapping methods, such as leveling, GNSS (Global Navigation Satellite System), total station, InSAR exhibits many advantages over owing to its large-scale, high-precision, and all-weather applicability [6]. At present, InSAR technology has been used for surveying the geological disasters occurring in Deltas [7][8][9], such as the Pearl River Delta [10], Nile Delta [11], and Yangtze River Delta [12]. ...
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Due to overexploitation of natural resources in the northern Yellow River Delta and the resulting land subsidence, interferometric synthetic aperture radar (InSAR) technology is utilized to analyze the deformation trend. Based on Advanced Land Observation Satellite PHASE Array Type L-band Synthetic Aperture Radar and Sentinel-1 data, this paper obtains the annual subsidence rate in two time periods (2007-2010 and 2017-2020) and verifies the correctness by comparing the ascending and descending orbit results. Subsequently, the 11 deformation interference pairs of the three-month interval are extracted to analyze the time series displacement of deformation areas. The results show that there are three large-scale subsidence areas with maximum annual subsidence of 250 mm, all of which are located in the oil or brine exploitation areas, and each deformation area displays a larger linear rate from January to May and then displays different nonlinear deformation from June to December.
... This study aims to implement the TimeFun-DInSAR algorithm to estimate time-series surface deformation at Mt. Bromo regarding big eruptions in 2011 and 2016. The remote sensing method (Lu et al., 2007) is the most commonly rapid assessment unrest volcano technique. Remote sensing has been largely implemented to rapid assess assessment (e.g., Voigt et al., 2011) Haiti earthquake in 2010. ...
Mt. Bromo is geographically located in eastern of Java Island at 112°57'30'' longitude and 7°56' latitude, with a large area of caldera ~10 Km2. The land over the volcano is a perfect area for farming, one of the important factor affects the level of soil fertility is the most mineral rich soils. Volcanic activities at Mt. Bromo has been recorded in 1775 which characterized by small eruptions with cycles ranging from one to five years. Regarding this evidence, we tried to investigate the surface changes over the Mt. Bromo by using Time-Series InSAR with TimeFun algorithm. TimeFun is an extension of SBAS to allow incorporating various functions such as seasonal oscillations, polynomials, and step functions as generally it estimates DEM errors as well and allows missing observation. The maximum allowed baseline value is defined and used to constrain the interferogram pair by selecting manual after differential InSAR processing in single face working. The proposed analysis is based on 27 SAR data sets acquired by the ALOS/PALSAR sensors during the 2007–2017 time interval. The result shows us deformation occurred up to ~10 cm at summit of Mt. Bromo during the eruption period. Time-series monitoring of surface deformation to infer volume changes, geometries and locations of sources of deformation involved in the future eruption
... With the development of synthetic aperture radar (SAR), SAR products have been widely used in lots of different fields nowadays [1]. Furthermore, interferometric SAR (InSAR) technology plays a significant role in detecting surface deformation caused by natural processes such as earthquakes, tectonics, volcanic unrest, shallow hydrological process, landslides, glaciers, or caused by anthropogenic activities, such as groundwater and oil pumping, gas and geothermal extraction, mining and urban subsidence [2][3][4][5][6][7][8][9]. Under many circumstances, an interferogram contains several ...
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Interferometric synthetic aperture radar (InSAR) products may be significantly distorted by microwave signals traveling through the ionosphere, especially with long wavelengths. The split-spectrum method (SSM) is used to separate the ionospheric and the nondispersive phase terms with lower and higher spectral sub-band interferogram images. However, the ionospheric path delay phase is very delicate to the synthetic aperture radar (SAR) parameters including orbit vectors, slant range, and target height. In this paper, we get the impact of SAR parameter errors on the ionospheric phase by two steps. The first step is getting the derivates of geolocation with reference to SAR parameters based on the range-Doppler (RD) imaging model and the second step is calculating the derivates of the ionospheric phase delay with respect to geometric positioning. Through the numerical simulation, we demonstrate that the deviation of ionospheric phase has a linear relationship with SAR parameter errors. The experimental results show that the estimation of SAR parameters should be accurate enough since the parameter errors significantly affect the performance of ionospheric correction. The root mean square error (RMSE) between the corrected differential interferometric SAR (DInSAR) phase with SAR parameter errors and the corrected DInSAR phase without parameter errors varies from centimeter to decimeter level with the L-band data acquired by the Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) over Antofagasta, Chile. Furthermore, the effectiveness of SSM can be improved when SAR parameters are accurately estimated.
... Surface deformation mapping is very important because it is a fundamental information to acquire detailed knowledge about the mechanism of geological activities. Synthetic aperture radar (SAR) interferometry (InSAR) technique has been shown to be a feasible technique for mapping that allows for the precise measurement of surface deformation (millimeter-to meter-level deformation) over a large area running at thousands of square kilometers [1]- [3]. However, because the InSAR method can only measure deformation along the antenna's line-of sight (LOS) direction, it has a limitation of one-dimensional (1D) deformation mapping. ...
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For the measurement of abrupt and large surface movements caused by earthquakes, volcanic eruption and melting glacier, Synthetic aperture radar (SAR) offset tracking method would be a feasible solution because it can provide unambiguous ground displacements in both the ground range and azimuth directions when the interferometric phase is not coherent. However, the measurement performance of the method largely depends on the kernel size, which denotes the size of search window to estimate the azimuth and range offsets between reference and target SAR images. Thus, there is a trade-off between sensitivity and measurement density depending on the search kernel size. In this study, an enhanced SAR offset tracking method based on multi-kernel processing has been developed to find an optimized measurement from the trade-off between resolution and measurement accuracy. It can obtain optimal surface displacement measurements by calculating multiple offset measurements and determining a final measurement from the statistical properties of the multiple measurements. The measurement performance of the proposed method was evaluated by using European Remote Sensing 2 (ERS-2) satellite SAR data sets of the Hector Mine earthquake event in 1999 and Advanced Land Observing Satellite-2 Phased Array type L-band Synthetic Aperture Radar-2 (ALOS-2 PALSAR-2) data sets of the 2016 Kumamoto earthquake event. Our results showed that an optimized measurement from the trade-off between the observation accuracy and resolution can be effectively determined by our proposed processing strategy. The results are improved results for measurement density and accuracy over previously published results. It further confirmed that our new method is allowed for the optimal measuring the large-scale fast surface displacements that cannot be sufficiently observed with the phase-based SAR method.
The success achieved by using SAR data in the study of the Earth led to a firm commitment from space agencies to develop more and better space-borne SAR sensors. This involvement of the space agencies makes us believe that it is possible to increase the potential of SAR interferometry (InSAR) to near real-time monitoring. Among this ever-increasing number of sensors, the ESA’s Sentinel-1 (C-band) mission stands out and appears to be disruptive. This mission is acquiring vast volumes of data making current analyzing approaches inviable. This amount of data can no longer be analyzed and studied using classic methods raising the need to use and create new techniques. We believe that Machine Learning techniques can be the solution to overcome this issue since they allow to train Deep Learning models to automate human processes for a vast volume of data. In this paper, we use deep learning models to automatically find and locate deformation areas in InSAR interferograms without atmospheric correction. We train three state-of-the-art classification models for detection deformation areas, achieving an AUC of 0.864 for the best model (VGG19 for wrapped interferograms). Additionally, we use the same models as encoders to train U-net models, achieving a Dice score of 0.54 for InceptionV3. It is necessary more data to achieve better results in segmentation.
Interferometry technique generates an elevation model using interferometric image pair acquired by synthetic-aperture radar (SAR). The present article has investigated the potential of Sentinel-1 SAR imageries for topographic analysis. Interferometric SAR utilizes phase difference information from complex-valued interferometric SAR images captured at two different imaging positions. Extracted topographic information is highly useful in various applications like crustal deformation, glacial movement, deformation studies, and topographical analysis. Various satellite systems such as RADARSAT, ERS, TerraSAR-X, ALOS PALSAR, and Sentinel-1 acquire interferometric images. The present article examines the DEM generation using the interferometry method. Sentinel-1A satellite datasets have been used to generate digital elevation model (DEM) for Tonk district and surrounding area. The study area comprises various land cover features including built-up, agriculture land, water bodies, barren land, and scrubland. SNAP toolbox has been used to generate the DEM using Sentinel-1A interferometric wide swath (IW) in single look complex (SLC) image format. The DEM generation process includes baseline estimation, co‐registration, interferogram generation, coherence, interferogram filtering, flattening, phase unwrapping, phase to height conversion, orbital refinement, and geocoding followed by generation of digital elevation model. Visual interpretation of derived DEM has been carried out using Google Earth. Coherence influences the accuracy of generated DEM. The quality of coherence depends on the baseline, wavelength, and temporal resolution of the interferometric pair. Pixels having coherence values greater than 0.5 have shown elevation values near to SRTM DEM values.
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The high levels of geo-hydrological, seismic, and volcanic hazards in the Campania region prompted full data collection from C-band satellites ERS-1/2, ENVISAT, and RADARSAT within regional (TELLUS) and national (PST-A) projects. The quantitative analysis, interpretation, and classification of natural and human-induced slow-rate ground deformations across a span of two decades (1992–2010) was performed at regional scale (Campania, Italy) by using interferometric archive datasets, based on the Persistent Scatterer Interferometry approach. As radar satellite sensors have a side-looking view, the post-processing of the interferometric datasets allows for the evaluation of two spatial components (vertical and E-W horizontal ones) of ground deformation, while the N-S horizontal component cannot be detected. The ground deformation components have been analyzed across 89.5% of the Campania territory within a variety of environmental, topographical, and geological conditions. The main part (57%) of the regional territory was characterized during 1992–2010 by stable areas, where SAR signals do not have recorded significant horizontal and vertical components of ground deformation with an average annual rate greater than +1 mm/yr or lower than −1 mm/yr. Within the deforming areas, the coastal plains are characterized by widespread and continuous strong subsidence signals due to sediment compaction locally enhanced by human activity, while the inner plain sectors show mainly scattered spots with locally high subsidence in correspondence of urban areas, sinkholes, and groundwater withdrawals. The volcanic sectors show interplaying horizontal and vertical trends due to volcano-tectonic processes, while in the hilly and mountain inner sectors the ground deformation is mainly controlled by large-scale tectonic activity and by local landslide activity. The groundwater-related deformation is the dominant cause of human-caused ground deformation. The results confirm the importance of using Persistent Scatterer Interferometry data for a comprehensive understanding of rates and patterns of recent ground deformation at regional scale also within tectonically active areas as in Campania region.
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1] A high resolution weather model is used to predict atmospheric delays for the acquisition times of synthetic aperture radar images over Hawaii. Refraction of the radar by water vapor in the atmosphere in Hawaii leads to apparent ground-motions with wavelengths and magnitudes similar to the actual ground motions generated by tectonic and volcanic processes. We examine the potential for a weather model to help characterize the atmospheric component in InSAR scenes and find that in the best cases it models the observed delays well, reducing the variance at wavelengths of 30 km and greater by $60%, while even in the worst cases it provides an independent means of quantifying the expected variance in the image due to the atmosphere. Citation: Foster, J., B. Brooks, T. Cherubini, C. Shacat, S. Businger, and C. Werner (2006), Mitigating atmospheric noise for InSAR using a high resolution weather model, Geophys. Res. Lett., 33, L16304, doi:10.1029/ 2006GL026781.
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Geophysical applications of radar inter-ferometry to measure changes in the Earth's surface have exploded in the early 1990s. This new geodetic technique calculates the interference pattern caused by the difference in phase between two images acquired by a spaceborne synthetic aperture radar at two distinct times. The resulting interferogram is a contour map of the change in distance between the ground and the radar instrument. These maps provide an unsurpassed spatial sampling density (100 pixels km 2), a competitive pre-cision (1 cm), and a useful observation cadence (1 pass month 1). They record movements in the crust, pertur-bations in the atmosphere, dielectric modifications in the soil, and relief in the topography. They are also sensitive to technical effects, such as relative variations in the radar's trajectory or variations in its frequency standard. We describe how all these phenomena contribute to an interferogram. Then a practical summary explains the techniques for calculating and manipulating interfero-grams from various radar instruments, including the four satellites currently in orbit: ERS-1, ERS-2, JERS-1, and RADARSAT. The next chapter suggests some guide-lines for interpreting an interferogram as a geophysical measurement: respecting the limits of the technique, assessing its uncertainty, recognizing artifacts, and dis-criminating different types of signal. We then review the geophysical applications published to date, most of which study deformation related to earthquakes, volca-noes, and glaciers using ERS-1 data. We also show examples of monitoring natural hazards and environ-mental alterations related to landslides, subsidence, and agriculture. In addition, we consider subtler geophysical signals such as postseismic relaxation, tidal loading of coastal areas, and interseismic strain accumulation. We conclude with our perspectives on the future of radar interferometry. The objective of the review is for the reader to develop the physical understanding necessary to calculate an interferogram and the geophysical intu-ition necessary to interpret it.
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Interferometric synthetic aperture radar (InSAR) techniques are used to calculate the volume of extrusion at Okmok volcano, Alaska by constructing precise digital elevation models (DEMs) that represent volcano topography before and after the 1997 eruption. The posteruption DEM is generated using airborne topographic synthetic aperture radar (TOPSAR) data where a three-dimensional affine transformation is used to account for the misalignments between different DEM patches. The preeruption DEM is produced using repeat-pass European Remote Sensing satellite data; multiple interferograms are combined to reduce errors due to atmospheric variations, and deformation rates are estimated independently and removed from the interferograms used for DEM generation. The extrusive flow volume associated with the 1997 eruption of Okmok volcano is 0.154±0.025 km<sup>3</sup>. The thickest portion is approximately 50 m, although field measurements of the flow margin's height do not exceed 20 m. The in situ measurements at lava edges are not representative of the total thickness, and precise DEM data are absolutely essential to calculate eruption volume based on lava thickness estimations. This study is an example that demonstrates how InSAR will play a significant role in studying volcanoes in remote areas.
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Temporal and geometrical decorrelation often prevents SAR interferometry from being an operational tool for surface deformation monitoring and topographic profile reconstruction. Moreover, atmospheric disturbances can strongly compromise the accuracy of the results. The authors present a complete procedure for the identification and exploitation of stable natural reflectors or permanent scatterers (PSs) starting from long temporal series of interferometric SAR images. When, as it often happens, the dimension of the PS is smaller than the resolution cell, the coherence is good even for interferograms with baselines larger than the decorrelation one, and all the available images of the ESA ERS data set can be successfully exploited. On these pixels, submeter DEM accuracy and millimetric terrain motion detection can be achieved, since atmospheric phase screen (APS) contributions can be estimated and removed. Examples are then shown of small motion measurements, DEM refinement, and APS estimation and removal in the case of a sliding area in Ancona, Italy. ERS data have been used
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The authors propose a combination of low-resolution (LR) and full-resolution (FR) SAR images for differential SAR interferometry. The principal problem in such a combination is the volume scattering decorrelation that limits the useful baseline of the interferometric pair to very small, impractical values. A technique has been introduced to remove this decorrelation by exploiting a digital elevation model (DEM) of the area imaged. The resulting interferogram has the quality (in terms of coherence or phase noise standard deviation) of a conventional FR interferogram, but reduced geometric resolution. The technique is suited to those differential interferometry applications where the resolution of the “differential” phase field to be monitored is much coarser than that of local topography. As a possible application, they propose a system that exploits the wide swath imaged by low-resolution ScanSAR modes for frequent monitoring of hazardous areas
Interferometric synthetic aperture radar (INSAR) is capable of measuring ground-surface deformation with centimeter-tosubcentimeter precision and spatial resolution of tens-of meters over a relatively large region. With its global coverage and all-weather imaging capability, INSAR is an important technique for measuring ground-surface deformation of volcanoes over cloud-prone and rainy regions such as the Aleutian Islands, where only less than 5 percent of optical imagery is usable due to inclement weather conditions. The spatial distribution of surface deformation data, derived from INSAR images, enables the construction of detailed mechanical models to enhance the study of magmatic processes. This paper reviews the basics of INSAR for volcanic deformation mapping and the INSAR studies of ten Aleutian volcanoes associated with both eruptive and noneruptive activity. These studies demonstrate that all-weather INSAR imaging can improve our understanding of how the Aleutian volcanoes work and enhance our capability to predict future eruptions and associated hazards.
The earthquake cycle is poorly understood. Earthquakes continue to occur on previously unrecognized faults. Earthquake prediction seems impossible. These remain the facts despite nearly 100 years of intensive study since the earthquake cycle was first conceptualized. Using data acquired from satellites in orbit 800 km above the Earth, a new technique, radar interferometry (InSAR), has the potential to solve these problems. For the first time, detailed maps of the warping of the Earth's surface during the earthquake cycle can be obtained with a spatial resolution of a few tens of metres and a precision of a few millimetres. InSAR does not need equipment on the ground or expensive field campaigns, so it can gather crucial data on earthquakes and the seismic cycle from some of the remotest areas of the planet. In this article, I review some of the remarkable observations of the earthquake cycle already made using radar interferometry and speculate on breakthroughs that are tantalizingly close.
The authors examine the role of polarimetry in synthetic aperture radar (SAR) interferometry. They first propose a general formulation for vector wave interferometry that includes conventional scalar interferometry as a special case. Then, they show how polarimetric basis transformations can be introduced into SAR interferometry and applied to form interferograms between all possible linear combinations of polarization states. This allows them to reveal the strong polarization dependency of the interferometric coherence. They then solve the coherence optimization problem involving maximization of interferometric coherence and formulate a new coherent decomposition for polarimetric SAR interferometry that allows the separation of the effective phase centers of different scattering mechanisms. A simplified stochastic scattering model for an elevated forest canopy is introduced to demonstrate the effectiveness of the proposed algorithms. In this way, they demonstrate the importance of wave polarization for the physical interpretation of SAR interferograms. They investigate the potential of polarimetric SAR interferometry using results from the evaluation of fully polarimetric interferometric shuttle imaging radar (SIR)-C/X-SAR data collected during October 8-9, 1994, over the SE Baikal Lake Selenga delta region of Buriatia, Southeast Siberia, Russia