Lecture slides on theory and applications of Synthetic Aperture Radar given at Badan Informasi Geospatial, Bogor, Indonesia.

1. Theory and applications of
Synthetic Aperture Radar
Yosuke Aoki
Earthquake Research Institute, The University of Tokyo
Email: yaoki@eri.u-tokyo.ac.jp
29 November 2018
Banda Informasi Geospasial
Bogor, Indonesia

2. Image of an earthquake
Nature Cover page of the 8 July 1993 issue (Vol. 364, No. 6433)
Massonnet et al. (Nature, 1993)
 Coseismic deformation of the 1992
Landers (California, USA; Mw=7.3)
earthquake measured by Synthetic
Aperture Radar (SAR).
 Amazing spatial resolution (~3-5 meters)
 No need for a ground-based instruments
 Available day and night. All weather.
Compare with optical measurements.

3. The 1995 Kobe earthquake (Mw=6.9)
Ozawa et al.
(GRL, 1997)
 A L-band SAR satellite JERS-1 was available between 1992 and 1998.
 No L-band SAR satellite available between 1998 and 2006, stagnating
research in Japan.
 What is L-band? Why L-band satellites are so important in Japan (and
Indonesia)?

4. Frequencies of electromagnetic waves
 Electromagnetic
waves of longer
wavelength are better
at transmitting
vegetation. Big
advantage for
vegetated areas such
as Indonesia and
Japan!
 L-band satellites are
better than C- or X-
band satellites in
vegetated areas.

5. Previous and current SAR satellites
 ALOS-4 (L-band) is to be launched in 2019.
 NISAR (L-band) is to be launched in 2020 (http://nisar.jpl.nasa.gov).

6. ALOS (2006-2011)
2007 Chuetsu-oki earthquake (Mw=6.8)
Aoki et al. (EPS, 2008)
2011 Tohoku-oki earthquake (Mw=9.0)
Feng & Jónsson (GRL, 2012)
LUSI Aoki & Sidiq (JVGR, 2014)

7. ALOS-2 (2014-)
2018 Palu earthquake (Mw=7.5)
2015 Wolf volcano
(Galápagos) eruption
Xu, Jónsson, Ruch & Aoki
(GRL, 2016)

8. Palu earthquake with ALOS-2

9. SAR amplitude image
 Biwa Lake, Japan
 SAR image is complex
with phase and
amplitude.
 Larger amplitude is
represented by white.
 Higher amplitude in the
cities.
 Lower amplitude on the
lake.

10. How SAR works
 Radar = Radio detection and
ranging
 The satellite trasmits
electromagnetic wave
obliquely to the ground and
observes reflected waves.
 The transmission needs to be
oblique to distinguish different
points by different line-of-
sight distance.
 Flat surface does not generate
much reflected waves.

11. Shadow and layover
 Layover: Different points cannot be separated because they are at the
same distance from the satellite.
 Shadow: Rugged topography does not allow the electromagnetic wave
to reach.

12. Resolution in azimuth direction
 The resolution in azimuth
direction is a function of
antenna size.
 Moving antenna enhance the
resolution as if the target
were viewed by a big
antenna.

13. SAR interferometry and
Young’s interference experiment
Optical path difference
Width of fringes
which is inversely propotional
To the separation of two
satellites (baseline) and
proportional to the wavelength
of the electromagnetic wave.

14. Effect of orbital separation
Critical baseline
Satellites with longer
wavelength has larger critical
baseline.
L-band satellites require less
strict orbital controls than C-
band and X-band satellites.
Range resolution

15. Effect of topography
Phase difference

16. Effect of topography
Height difference over which the phase
difference is one cycle
Sensitivity to topography is higher with
longer wavelength.

17. Effect of topography
Topography of Etna volcano
Massonet & Feigl (Rev. Geophys., 1998)
Longer baseline is better to
measure topography in higher
sensitivity, but the baseline
should not exceed the critical
baseline.

18. Effect of Digital Elevation Model (DEM)
The 2007 Chuetsu-oki earthquake
Furuya, Takada, and Aoki (2010)
Interferogram with
higher-resolution DEM
gives more detailed
deformation field.
(top) GSI 50 m
(bottom) ASTER 15 m

19. Correcting interferograms
Interferogram = Orbit separation + Topography + Deformation
Pritchard (Phys. Today, 2006)

20. Phase unwrapping
phase change
integer
ambiguity
What we get by InSAR is the
phase fraction (wrapped phase).
We need to estimate integer
ambiguity to extract the real
line-or-sight changes
(unwrapped phase).

21. Limitation of InSAR: Line of sight (LOS)
 InSAR measures the line-of-
sight component of the
displacement, not the 3D
displacement as in GNSS.
 Insensitive to north-south
displacements.
 More sensitive to vertical
displacements, but impossible
to separate vertical and
horizontal displacements.
LOS change from ascending and
descending orbits

22. Limitation of InSAR: Swath width
2008 Wenchuan (Mw=8.0) earthquake
Hao et al. (GRL, 2009)
 The swath width is 50-70 km for stripmap mode. It takes some time to
observe the whole deformation field if the deformation is extended in
east-west direction.
 ALOS-2 has ScanSAR mode with a width of 350 km.

23. Limitation of InSAR:
Decorrelation
2018 Hokkado Eastern Iburi earthquake (Mw=6.5)
 Change in surface feature caused by
landslide, surface faulting, volcanic ash,
etc, decrease the coherence to degrade
the observation.
 Temporal decorrelation is severe in
vegetated regions such as in Indonesia
and Japan. Images with temporal
separation of 1 year can be incoherent in
Indonesia.

24. Limitations of InSAR:
Atmospheric disturbance
 Electromagnetic waves refract in the
presence of water vapor, making the
apparent line-of-sight distance longer.
 Interferograms contain long-wavelength
patterns even if no real deformation is
present.
 Precise correction of the atmospheric effect
requires a precise knowledge of the spatial
variations of water vapor.
 Removal of altitude-correlated signals does
a reasonably good job. Lohman & Simons
(Geochem. Geophys. Geosyst., 2005)

25. Limitations of InSAR:
Ionospheric disturbance
Massonnet & Feigl (GRL, 1995)
 Electromagnetic waves propagate slower than
speed of light in the presence of ionized
atmosphere, making apparent line-of-sight
distance longer.
 The ionospheric effect is frequency-dependent,
so multiple frequencies of electromagnetic
waves allow us to extract the ionospheric effect.
 GNSS has two frequencies, but current SAR
satellites use only single frequency.
 L-band waves are more susceptible to the
ionospheric effect than C- and X-band waves.

26. Other limitations of InSAR
 Oblique incidence of electromagnetic waves makes layover and shadow
in areas of steep topography.
 Temporal resolution is limited by the recurrence time of the satellite.
ALOS-2: >14 days
ALOS: 46 days
Sentinel-1: 6 days (originally 12 days)

27. Earthquake deformation
Zagros Mountains, Iran
Lohman & Simons (Geochem. Geophys. Geosyst., 2005)
 InSAR is capable of detecting
displacements by
earthquakes down to M5.0-
5.5.
 InSAR is capable of precisely
locating M5.0-5.5
earthquakes whose location
error is up to a few tens of
kilometers with teleseismic
waveforms only.

28. Postseismic deformation
Gourmelen & Amelung
(Science, 2005)
 Three possible mechanisms of
postseismic deformation
- Deep afterslip (a few years)
- Viscoelastic relaxation (long)
- Poroelastic (< a few months)
 Gourmelen & Amelung (2005)
detected postseismic deformation
of earthquakes that occurred a
few tens of years before in
Nevada, USA. The observed
deformation is due to viscoelastic
relaxation of the lower crust and
upper mantle.

29. Poroelastic
deformation
Jónsson et al. (Nature, 2003)
 InSAR is capable of discriminating postseismic deformation of different
origin.
 Jónsson et al. (2003) succeeded in constraining the mechanism of early
postseismic deformation of two M6.5 earthquakes in South Iceland
Seismic Zone.

30. Interseismic
deformation
Fialko (Nature, 2006)
 Stacking large numbers of
interferograms allows us to infer
interseismic displacements as low as
~3-5 mm/yr by reducing noise.
 Fialko (2006) succeeded in separating
contribution from San Jucinto and San
Andreas faults in Southern California.
 Applicable to the Sumatra fault and
major faults elsewhere? Spatially
variable fault slip rates on an
active fault is an important
information for hazard assessment!

31. Volcano deformation
Amelung et al. (Nature, 2000)
 Volcanoes are inaccessible in
some areas because of steep
topography and danger from
volcanic activity.
 InSAR is capable of measuring
deformation of where ground-
based measurements are not
available.

32. Heuristic volcano
deformation study
Pritchard & Simons (Nature, 2002)
 Pritchard & Simons (2002) found
that some volcanoes in South
America which were recognized
inactive are actually accumulating
magma.
 A discovery only done by remote
sensing technique!
 Applicalble to Indonesian
volcanoes? We did it!

33. Application to Indoneisan volcanoes
Chaussard, Amelung & Aoki
(JGR Solid Earth, 2013)
Many volcanoes have sub-
optimal ground-based
network, so a systematic
monitoring by remote
sensing techniques is
required!

34. Post-eruptive thermal contraction of
Usu volcano, Japan
 The 2000 vent: LOS velocity of about
38 mm/yr in the ALOS-1 period
(2006-2011). Negligible deformation
in the ALOS2 period (2014-2017).
 The 1977 vent: Maximum LOS
velocities of about 66, 45 and 43
mm/yr in the JERS (1992-1998),
ALOS-1 and ALOS-2 periods.
 The 1943 vent: Steady deformation
with a maximum LOS velocity of
about 20 mm/yr in 1992-2017.
Ascending Descending
2000
1977
1943
Wang & Aoki (JGR Solid Earth, in revision)

35. Temporal evolution of vertical
displacements: The 1943 vent

36. Temporal evolution of vertical
displacements: The 1977 vent

37. Temporal evolution of vertical
displacements: The 2000 vent

38. Optimum deformation parameters
 Shallow sources (<400 m bsl) are responsible.
 Thermal diffusivity much larger than that derived in lab
experiments (0.1–1×10-5 m2/s) .
Longitude
(deg)
Latitude
(deg)
Depth
( m bsl)
Thermal
diffusivity
(×10-5 m2/s)
Volume
(×106 m3)
2000 vent
140.8034 42.5541 213±19 8.21±1.01 6.67±0.21
140.8118 42.5563 100±13 8.06±1.20 2.05±0.13
1977 vent 140.8353 42.5416 369±29 10.05±1.09 132.18±8.01
1943 vent 140.8662 42.5426 92±12 1.65±0.22 49.51±3.12

39. Time-varying volcano deformation: LUSI
Aoki & Sidiq (JVGR, 2014)

40. Land subsidence
Figure 7. Identification of subsided areas in Jakarta based on DInSAR technique. (a) Interferogram
from 2007-2011 based on ALOS-PALSAR data, (b) subsided area in Pluit region from 2007-2011 or
1472 days based on ALOS-PALSAR data, (c) subsided area in Pluit area from 2014 -2016 or 658 days
based on ALOS-2 data, image not rectified.
4. Conclusions
This research shows the ability of SAR data to identify ground deformation in Jakarta area by
analysing the amplitude and phase components. Sentinel-1A data and S1TBX software are useful to
obtain the land surface changes based on amplitude analysis. This research also found that
atmospheric phase affects much to C-band SAR data as already identify by previous studies [11] and
c
b
a
2nd International Conference of Indonesian Society for Remote Sensing (ICOIRS) 2016 IOP Publishing
IOP Conf. Series: Earth and Environmental Science 47 (2016) 012022 doi:10.1088/1755-1315/47/1/012022
Surabaya, ~30 mm/yr of subsidence
Aditiya, Takeuchi & Aoki (2017) North Jakarta,
Up to 260 mm/yr (!) of subsidence
Agustan et al. (2016)
“If we look at our models, by 2050 about 95% of North Jakarta will
be submerged.” – Heri Andreas (ITB), BBC Indonesian, Aug. 2018

41. Damage detection
mum case the temporal baseline between each acquisition is only one repeat
so Section 4).
(or more) SAR images, fulfilling the requirements mentioned above, are co-registered
master image and resampled to its reference grid (Figure 4). Additionally, a common
sures that only the overlapping parts of the spectrums are used. Thereby, the spatial
fect (see Section 2.1.) is reduced [74]. In the next step, interferograms between
he two slave images are generated: One pre-disaster InSAR pair (t1 and t2) and one
R pair (t2 and t3). Then, for both InSAR pairs the coherence is computed according to
e Section 2.1). Moreover, as described by Equation (9), also two SAR intensity
computed using again the co-registered pre- (t1 and t2) and co-disaster (t2 and t3)
airs [8]. The damage caused by the natural disaster is then assessed by detecting the
he corresponding image pairs (see Section 2.3 for more details).
pre co
Two possible metrics for damage
detection as a function of coherence C
e.g., Arciniegas et al.
(IEEE TGRS, 2007)
Hoffmann et al.
(Int. J. Remote Sens., 2007)
Here we only look at co-
disaster coherence.
Pre-disaster coherence should
also be used to for damage
detection to evaluate temporal
decorrelation.
Source of decorrelation
 Surface rupture
 Too much deformation
 Too much vegetation
 Landslide, ashfall
 Snow

42. The 2016 Kumamoto
earthquake
Earthquakes of MJMA>5.5
Mo d hr min lon lat depth MJMA
04 14 21 26 130.8087 32.7417 11.39 6.5
04 14 22 07 130.8495 32.7755 8.26 5.8
04 15 00 03 130.7777 32.7007 6.71 6.4
04 16 01 25 130.7630 32.7545 12.45 7.3
04 16 01 45 130.8990 32.8632 10.55 5.9
04 16 03 03 131.0868 32.9638 6.89 5.9
04 16 03 55 131.1910 33.0265 10.89 5.8
04 18 20 41 131.1998 33.0020 8.64 5.8
04 19 17 52 130.6353 32.5352 9.96 5.5

43. SAR Interferometry (InSAR) and
pixel offset (or offset tracking)
InSAR Pixel offset
Measurement Phase Amplitude
Error 20-30 mm ~300 mm
Large deformation Incoherent Capable

44. Decorrelation and landslides
Landslide sites are identified
from optical images by
Geospatial Information
Authority.
Source of decorrelation
Surface rupture, Too much deformation
Too much vegetation
Landslide, ashfall, Snow

45. Surface fractures
Identified from an optical image by Geospatial Information Authority

46. New (unconventional) technique:
Amplitude changes
Tobita et al. (EPS, 2006)
 Tobita et al. (2006) compared amplitude of SAR
images before and after the 2004 Sumatra-
Andaman earthquake to detect uplifted and
subsided regions on the coast.
 Subsidence decreases
amplitude of the SAR
image on the coast.
 Applicable to e.g.,
identifying tsunami-
inundated areas.

47. New (unconventional) technique:
pixel offset
InSAR Pixel offset
Measurement Phase Amplitude
Error 20-30 mm ~300 mm
Large deformation Incoherent Capable
The 2016 Kumamoto earthquake

48. Pixel offset analysis:
Kumamoto earthquake
 Pixel offset analysis can give two-component displacements.

49. The Palu earthquake

50. What to do: The Palu earthquake
 Numerical rupture simulation to be consistent with SAR
measurements. The Palu earthquake may have been a super-
shear earthquake.
 Damage detection from the coherence of interferograms.
Establishing a system to systematically process the incoming
data may be beneficial.
 Postseismic deformation?
 Combining SAR measurements with GNSS.

51. What to do: Volcano deformation
 Monitoring all Indonesian (and beyond?) volcanoes
systematically with SAR images by processing incoming
images.
 Detecting ashfall, pyroclastic flow, and lava flow from InSAR
coherence. Establishing a system to systematically process
the incoming data may be beneficial.
 Combine InSAR with GNSS measurements (if any) to correct
InSAR measurements.

52. Summary
 SAR can measure Earth’s surface day and night, regardless
of the weather.
 SAR can measure surface displacements associated with
various phenomena with a high spatial resolution, but with
some limitations.
 SAR can be a powerful tool in detecting damages caused
by landslide, flooding, tsunami, ….
Terima Kasih!