Proceedings of the International Symposium on Engineering Lessons Learned fromthe 2011 Great East Japan Earthquake, March 1-4, 2012, Tokyo, JapanSURFACE CHANGE OF THE SOIL LIQUEFACTION
CAUSED BY THE 2011 GREAT EAST JAPAN
EARTHQUAKE DERIVED FROM SAR DATA
Kazuya ISHITSUKA1, Takeshi TSUJI2 and Toshifumi MATSUOKA3
1Department of Urban Management, Kyoto University, Kyoto, Japank_ishitsuka@earth.kumst.kyoto-u.ac.jp
2Assistant Professor, Department of Urban Management, Kyoto University, Kyoto, Japantsuji@earth.kumst.kyoto-u.ac.jp
3Professor, Department of Urban Management, Kyoto University, Kyoto, Japanmatsuoka@earth.kumst.kyoto-u.ac.jp

ABSTRACT: To reveal changes in surface scatters associated with the 2011 Great East
Japan Earthquake, we performed Interferometric processing using SAR images in Kantoregion. As a result, we detected areas of scatter changes at the waterfront along Tokyobay and Tone River. Furthermore, spatially-continuous ground subsidence inferred fromDInSAR analysis was found in the same area. Since these results are consistent with fieldstudies in liquefaction areas, we concluded that our results demonstrate surface changes
due to soil liquefaction caused by the earthquake.
Key Words: soil liquefaction, remote sensing, the 2011 Great East Japan earthquake,
DInSAR analysis

INTRODUCTIONOn March 11th 2011, the 2011 Great East Japan Earthquake was generated along northeast of the Japan
Trench with ruptured fault as large as 500km×250km (Ozawa et al., 2011). Moreover, several large
aftershocks continuously struck along the Japan Trench. In Kanto region including Tokyo, it has beenreported that wide range of soil liquefaction was occurred mainly at the waterfront along the shore(Yasuda and Harada, 2011; Bhattacharya et al., 2011). Due to the soil liquefaction, residentialbuildings and infrastructures have suffered a great deal of damages. Soil liquefaction is usuallyinvestigated by field reconnaissance and aerial photography. In order to investigate soil liquefaction
associated with the 2011 earthquake, several studies have been performed and revealed the areal extent
of soil liquefaction areas (e.g., KRDB and JGS, 2011). In this study, however, we tried to investigate
the areal extent and its degree of the occurrence of the soil liquefaction using images acquired bySynthetic Aperture Radar (SAR). SAR is active sensor which irradiate electromagnetic microwave toscatters on earth's surface and receive backscatter signal. The main reason we used SAR images in thisstudy is an advantage for providing us broad and dense information on the Earth’s surface without theneed of ground-based observation.

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First of all, we created initial interferogram from two SAR images. Then, phase-corrected
coherence (coherence map) was calculated based on the amplitude (backscatter intensity) of two SAR
images. When soil liquefaction is occurred, the ground surface might become more wetting andconstructions might be inclined. Hence, we can detect the changes in the relationship of amplitude
among adjacent pixels before and after the 2011 earthquake using the loss of phase-corrected
coherence. Since the loss of coherence is composed of several effects, coherence difference map wascreated to extract the effect due to the 2011 earthquake (Figure 1). After that, we compared our resultswith previous research (KRDB and JGS, 2011) to validate our results. Several studies have tried todetect surface changes due to soil liquefaction as the loss of coherence after previous huge earthquake(Saraf et al., 2002; Ramakrishnan et al., 2006). However, this study has a distinguishing characteristic
in the view of validation of the ability of satellite-based liquefaction investigation using such a detailfield investigation conducted by KRDB and JGS (2011).
Moreover, to reveal the degree of soil liquefaction, we used phase difference before and afterearthquake. This method is usually referred to as Differential Interferometric SAR (DInSAR)(Massonnet and Feigl, 1998; Simons and Rosen, 2007) and provide us from ground displacements ofcentimeter or sub-centimeter accuracy. Since GPS stations in the liquefaction area are also sufferedfrom damages due to tilted ground, it is important to estimate ground subsidence inferred fromDInSAR analysis in the liquefaction area (Figure 1).

Fig. 1 The flow of this study

METHODSThe SAR images in this study were acquired by the Phased Array Type L-band SAR (PALSAR)
instrument on the Japanese Advanced Land Observing Satellite (ALOS). We used interferograms of I1
I3 in Table 1 covered with Tokyo bay and I2 I4 in Table 1 covered with Tone River for estimating theloss of coherence and interferograms of I3 I4 in Table 1 for estimating ground subsidence (Table 1,Figure 2).
Table 1 SAR images used in this study
TypeID

MasterSlave

Direction

Bperp

Preseismic
Preseismic
Coseismic
Coseismic

I1
I2
I3
I4

2011/01/04
2010/10/05
2011/02/19
2010/11/20

2011/02/19
2010/11/20
2011/04/06
2011/04/07

Ascending
Descending
Ascending
Descending

709m
593m
394m
914m

850

Coveredarea
Tokyo bay
Tone RiverTokyo bay
Tone River

Fig. 2 Kanto region and covered area of SAR image used in this study.

Estimating the loss of coherence
To measure physical change of the earth surface statistically, we used phase-corrected coherence (  )(Hagberg et al., 1995).
N|  C1( n ) C 2*( n ) e i (1 2 ) |n 1N

| Cn 1(3)N| | C( n) 21n 1(n) 22|i

where C  Ae is complex value in Single Look Complex (SLC), which contains amplitude ( A )and phase (  ), N indicates the number of adjacent pixels to compute coherence as spatial average,
referred to as window size. In this study, we chose N =7×7, which indicate adjacent area of 98 m×
112 m is used to estimate coherence. Phase corrected coherence has the characteristics of computing
coherence using amplitude. Amplitude represents backscatter intensity on the surface at a eachlocation. It is known that backscatter intensity is affected by the water content and roughness on thesurface with the same incidence angle, polarization and electromagnetic microwave length. Hence,sand boiling on the surface or inclined buildings induced by soil liquefaction change the relationshipof amplitude among adjacent pixels, which result in decorrelation. Although, these temporal changes
on the surface are one of the sources of decorrelation by this earthquake, other effects are included as
the source of decorrelation as follows. The coherence (  ) comprises contributions from four effects(i.e.,  N : thermal noise,  V : geometric effect,  V : volumetric effect and  T : temporal effect)(Zebker and Villasenor, 1992). Since the influence of soil liquefaction appear as the decreasing of  T ,we need to extract  T from total coherence. Therefore, we made coherence difference map which is
the result of subtracting coherence of preseismic pair acquired before earthquake (I1 I2 in Table1)
from that of coseismic pair acquired before and after earthquake (I3 I4 in Table1).
Estimating ground subsidence
We used DInSAR analysis to estimate ground subsidence associated with soil liquefaction. Phase
difference between data acquisitions (  1   2 ) is composed of several effects.

851   disp   orbit   topo   atm   noise(4)where  disp is phase difference induced by surface displacement toward line of sight (LOS) direction.

 orbit ,  topo ,  atm and  noise are phase difference due to satellite position difference, topography,
atmosphere inhomogeneity and noise. To subtract phase component other than surface displacement,
we can estimate phase difference induced by ground displacement. We performed DInSAR analysis
using coseismic pair acquired before earthquake and after earthquake (I3 I4 in Table1). Although sandboiling on the surface might have been removed at the acquisition of SAR images after earthquake(2011/04/06 in I3 and 2011/04/07 in I4), we estimated surface displacement without consideration of
the effects of removed sand boiling. To eliminate the effect of the difference in the satellite positions
for the two acquisitions of a pair, we used 50m mesh digital elevation models provided by geospatial
information authority of Japan (GSI). As the strategy for remaining high resolution, we used adaptive
filter whose performance magnitude depend on coherence (Baran et al., 2003) which is calculated byonly phase in this study. As a result, we obtained differential interferogram which represents surface
displacement toward LOS direction caused by the 2011 earthquake. To pick up the local groundsubsidence associated with soil liquefaction, we removed the long wave ground displacement causedby the 2011 earthquake by applying a best fit quadratic function.
RESULTSThe loss of coherence
The coherence difference map is calculated to extract temporal decorrelation due to the earthquake.
The negative value indicates the areas where coherence decrease due to the earthquake. In the result ofcoherence difference map, negative value is distributed in the waterfront (artificially filled ground)along Tokyo bay, and waterfront along Tone River. These observations suggest that physical propertiesof the ground surface such as water contents of soil or surface roughness were changed due to theearthquake in these areas. To confirm whether surface scatter change is associated with soilliquefaction or not, we compared our result with existing survey, which is performed by foot or air
photograph soon after earthquake (KRDB and JGS, 2011). As a result of comparison, at the areas
along Tokyo bay and the Tone River, 93 and 91 percent of the liquefaction locations detected by thefield survey performed by KRDB and JGS (2011) are consistent with the results of this study,
respectively (e.g., Figure 3). Because our result is consistent with the result of existing survey,
negative coherence corresponds to the surface change due to soil liquefaction caused by the 2011
earthquake.

Ground subsidence
Local surface displacement after removing global surface displacement demonstrates that local surface
displacement was mainly occurred at the soil liquefaction area, (i.e., waterfront along Tokyo bay andTone River). In soil liquefaction areas, there are certainly decorrelation-induced phase discontinuity,
however, we obtained spatially continuous displacement. Moreover, local surface displacement
inferred from DInSAR analysis was occurred in the opposite to LOS direction in both pair taken on
ascending orbit (I3 in Table1) and descending orbit (I4 in Table1), which denote that the local
displacement is ground subsidence (e.g., Figure 4). Therefore, we concluded that this local surface
displacement was associated with soil liquefaction induced by the 2011 earthquake.

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Fig. 3 Comparison the loss of coherence and field survey (KRDB and JGS, 2011). The red lines andblue lines indicate liquefaction and non-liquefaction locations detected by field survey. The yellow andorange area indicate negative value (under -0.1) inferred from phase corrected coherence in ouranalysis.

Fig. 4 Local surface displacement at waterfront along Tokyo bay.

CONCLUSIONS
We detected the change in surface scattering property caused by the 2011 earthquake using thedifference of phase corrected coherence between preseismic and coseismic SAR data pairs. We furtherrevealed local surface displacement using DInSAR analysis. These results are consistent with existing
field survey results. Therefore, these surface changes should be associated with soil liquefaction. This
study further detected undiscovered liquefaction area especially in waterfront along midstream anddownstream of Tone River. This study proposes the effective use of SAR data to investigate soilliquefaction and clarify that SAR data can provide spatially broad insight to the soil liquefaction. In
this study, we performed interferometric processing and then compared the result obtained from SAR
data and the result of field survey, but if we apply the proposed methodology in this paper immediately
after the occurrence of the earthquake using SAR data, field survey works would be performed moreefficiently.

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ACKNOWLEDGMENTS
The ownership of PALSAR data used in this study belongs to Ministry of Economy, Trade andIndustry (METI) and Japan Aerospace Exploration Agency (JAXA), and Level 1 data was processedand provided by Earth Remote Sensing Data Analysis Center (ERSDAC). We also acknowledge Kanto
Regional Development Bureau of Ministry of Land, Infrastructure, Transport and Tourism (KRDB)
and Japanese Geotechnical Society (JGS) for providing the data of soil liquefaction. This study wassupported by Global Center for Education and Research on Human Security for Asian Megacities(GCOE).
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