20090701_JurnalGeografiVol02No02pp51-59LuhurBayuajietal.pdf

8/8/2019 20090701_JurnalGeografiVol02No02pp51-59LuhurBayuajietal.pdf

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ISSN

02T6

-

I5I7

JURNAL GEOGRAFI

Volume2No.2lJuli2009

DInSAR

FOR

VOLUME

CHANGE

ESTIMATION

oF

SUBSIDENCE

AT

BANDUNG

BASIN

Estimasi

Perubahan

Volume

dengan

Metode

DInSAR

untuk

Kajian

Penurunan

Taneh

di

Cekungan

Bandung

Josaphat

Tetuko

sri Sumantyo,

Masanobu

Shimada,

piene-phillippe

and

Hasanud

din Zainal

Abidin

POLA

WITAYAH

BAHAYA

LIKUIFAKSI

DI

PROVINSI

D.I.

YOGYAKAR Th

(Studi

kasus

:

Gempabumi

yogyakarta2T

Mei

2006)

spatial

Pattern

of

Liquefaction

Hazard

in

yogyakarta

province

(A

case

study

of

earthquake

in

yogyakarta

May 27,

2006)

R.

Adawiyah,

Supriatna

dan

Ratna

Saraswati

A

GIS-SITE

SUITABILITY

MODELING

FOR

ALLOCATION

FOREST

HARVEST,

ZONES

IN

PENINSULAR

MALAYSIA

Pemodelan Kesesuaian

Lokasi

Berbasiskan SIG untuk

Alokasi

Zona

Pemanenan

Hutan di

Semenanjung

Malaysia

Mohd

Hasmadi

Ismail

and Farah

Dayana

Sulaiman

PERILAKU

TANGGAP

DIRI

MASYAR,AKAT

DALAM

MENGHADAPI

BENCANABANJIR

DI

KOTA

SEMARANG

Performance

self Perceptive

of

Flood

Disaster

in

semarang

Municipalie

Maman

Rachman,

Joko

Widodo

dan

laturahono

B.S

IDENTIFIKASI

PULAU

DI

KEPULAUAN TOGEAN PROVINSI

SULAWESI

TENGAH

BERDASARKAN

KAIDAH

TOPONIMI

(Identffication

of

Island

in

Archipelago

of rogean

Central

sulawesi

province

Based

on Tbponymy

Method)

Yulius

dan

Triyono

MONITORING

OF

JAKARTA

URBAN

AREA

SUBSIDENCE

By

USING

ALOS/PALSAR

DINSAR

Pemantauan

Penurunan

Tanah

Jakarta

menggunakan

DINSAR

AL)9/?ALSAR

Luhur Bayuaji,

Josaphat

Tetuko

Sri Sumantyo

and

Hiroaki

Kuze

Diterbitkan

oleh:

Departemen

Geografi

Fakultas

Matematika

dan

Ilmu

pengetahuanAlam


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Identikasi Pulau Di Kepulauan Togean Provinsi

Sulawesi Tengah Berdasarkan Kaidah Toponimi 51

Jurnal Geogra, Vol. 2 No. 2 / Juli 2009

MONITORING OF JAKARTA URBAN AREA SUBSIDENCE

BY USING ALOS/PALSAR DINSAR

Luhur Bayuaji, Josaphat Tetuko Sri Sumantyo and Hiroaki Kuze

Center for Environmental Remote Sensing (CEReS), Chiba University, Japan

Abstract

Differential Interferometry Synthetic Aperture Radar (DInSAR) is known as a technique capable to detect land

surface displacement. In this research, we employ ALOS/PALSAR data to investigate land subsidence in Jakarta

during 2007 and 2008. It is found that four northern areas in the city exhibit clear indications of land subsidence

mostly caused by the geological structure and high human activities on those areas. The subsidence estimations

during the study time are varying from 11.5 to 26.6 cm. Comparison with ground survey data indicates that the

result of DInSAR analysis gives reliable estimation of the subsidence in the urban environment.

Keyword : Land surface displacement, land subsidence

Abstrak

Diferensial interferometri Synthetic Aperture Radar (DInSAR) dikenal sebagai suatu teknik yang mampu mendeteksi

pergerakan permukaan tanah. Dalam penelitian ini, kami menggunakan ALOS / data untuk menyelidiki PALSAR

subsiden tanah di Jakarta selama 2007 dan 2008. Dalam penelitian ini ditemukan bahwa empat daerah di utara

kota itu jelas menunjukkan indikasi pengendapan tanah yang sebagian besar disebabkan oleh struktur geologi

dan aktivitas manusia yang tinggi di daerah tersebut. Perkiraan subsiden selama waktu penelitian berbeda-beda

11,5-26,6 cm. Perbandingan dengan data survei lapang menunjukkan bahwa hasil analisis DInSAR memberikan

perkiraan subsiden yang dapat diandalkan di lingkungan perkotaan.

Kata kunci : Pergerakan permukaan tanah, subsiden tanah

1. INTRODUCTION

Synthetic Aperture Radar (SAR) is a remote

sensing system with capabilities to monitor

the Earth environment during day-night,

under all-weather conditions. In particular, the

Differential Interferometry SAR (DInSAR)

technique is able to detect accurately the

ground displacement or land deformation in theantenna line-of-sight (LOS) direction using data

taken at two separated acquisition times (Chang

et al , 2004; Stramondo et al , 2006; Tralli et al ,

2005). By comparing to ground-based methods

such as leveling and Global Positioning System

(GPS) measurements, the DInSAR method can

easily be applied in a wide coverage area with

high accuracy and low cost (NG et al , 2008;

Raucoules et al , 2007).

The area studied in the present work isJakarta, the capital city of Indonesia. The data

from Phased Array L-band SAR (PALSAR)

onboard Advanced Land Observing Satellite

(ALOS) is employed to observe the land

subsidence during 2007 and 2008, and affected

areas are detected with spatial perspective.

Since the launch of ALOS in 2006, the PALSAR

data have been applied to several subsidence

studies (Onuma and Ohkawa 2009; Takeuchi

and Yamada 2002; Wang and Allen 2008). The

satellite-derived estimation of the subsidencedepths in some observation points are compared

with the results of our ground survey in 2009,

as well as with results of a previous GPS survey

(Abidin et al, 2007). The observation points

are spotted as high human activity area for

residence, trading and industrial complexes.

2. STUDY AREA

Jakarta is located between 106º33’00”-107º00’00” E longitude and 5º48’30”-

6º24’00” S latitude, in the northern part of West


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Monitoring of Jakarta Urban Area Subsidence

by Using ALOS/PALSAR DInSAR52

Jurnal Geograf, Vol. 2 No. 2 / Juli 2009

Java province. The city consists of 5 regions,

covering an area of about 652 km2. The area is

relatively at: in the northern and central part,

topographical slopes range between 0º-2º and

in the southern part; it is up to 5º. The altitude in

the southern

most area is about 50 m above sea

level and the other areas are lower (Figure 1).

Jakarta is located on a groundwater basin

(Jakarta groundwater basin), and can be

categorized into the following ve landforms:

alluvial, marine-origin, beach ridge, swamp

(including mangrove), and former channel(Abidin et al , 2007). It is known that the basin

is lled with marine Pliocene, quaternary

sand and delta sediments, with a thickness

of up to 300 m (Delinom et al , 2009). Figure

2A shows the geological information of study

area, which is mostly dominated by alluvial

deposit. There are 13 natural and articial

rivers owing through the city. It has humid

tropical climate with annual rainfall varying

between 1500-2500 mm, inuenced by the

monsoons. The nighttime population is around

8 millions, which increases to 11 million during

business hours since many people commute

from satellite cities of Jakarta in order to work.The population (residence) density in the ve

districts was between 9,600-23,000 km-2 as of

Figure 1. Study area map


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by Using ALOS/PALSAR DInSAR 53


Figure 2. (A) Geological map of Jakarta (B) DInSAR interferogram of Jakarta (20070131-20081105). (CP1-EP4) DInSAR Interferogram enlargement of every point

observation derived from each data pair.

year 2000 (http://demogra.bps.go.id), while

the most recent statistics in 2009 indicates that

the values are between 12,000-19,000 km-2

(http://www.kependudukancapil.go.id/).

The occurrence of land subsidence in

Jakarta was recognized by a Dutch surveyor as

early as 1926 (Abidin et al , 2005). Scientic

investigations started in 1978, and continuous

investigation using leveling measurement was

conducted during 1982-1999 (Djaja et al , 2004).

The measurement using Global Positioning

System (GPS) was also undertaken during

1997-2005 (Abidin et al , 2007). Although the

GPS measurement can provide more precise

data with much better efciency than the

point-to-point leveling method, however its

implementation for a long-time measurement

not only imposes considerable effort and cost to


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map the subsidence for a large area but also only

able to acquire vertically shifting on every GPS

station. The present study will use the ALOS/

PALSAR data to detect land subsidence in both

directions (horizontally and vertically) from

2007 to 2008. The methodology of DInSAR

technique will be used for detecting and

monitoring land subsidence in this research.

3. METHODOLOGY DInSAR

Interferometry SAR (InSAR) and DInSAR

techniques are based on the combination of two

radar images taken at different acquisition times.

The phase data of SAR images are analyzed toderive the local topography (InSAR) or detect

and quantify the ground displacement that

has occurred between the two acquisitions

(DInSAR) (Raucoules et al., 2007).

The phase difference between an InSAR data

pair ( ) can be expressed as (Chatterjee et

al., 2006)

(1)

Here, disp, atm, noise, topo, and at refer to the phase difference originating from ground

displacement along the slant-range, atmospheric

noise, noise from radar instrument and temporal

deceleration, noise due to topographic height,

and noise due to the assumption of ideally

at earth terrain, respectively. In the process

of extracting the ground displacement, the

topographic ( topo

) and at earth phase difference

( at

) can be removed using digital elevation

model (DEM) data and precise satellite orbitaldata, respectively. The result of this process is

generally called DInSAR.

In this study, JAXA SIGMA-SAR software

developed by Shimada (1999) is used to obtain

the interferogram. In order to remove the noise

from radar instrument and temporal deceleration

(noiseφ ), the Goldstein-Werner ltering process

is applied to the noisy interferogram (Goldstein

and Werner, 1998). The resulting DInSARinterferogram is in the form of phase cycle

(phase difference), each cycle being correlated

to ground displacement along the slant-range

direction. In the case of ALOS/PALSAR, the

wavelength is 23.6 cm (L-band) and hence,

each cycle in interferogram represents ground

displacement of 11.8 cm.

4. DATA AND PROCESSING SOFTWARE

A series of SAR interferograms are

computed from ALOS/PALSAR data taken on

three different acquisitions days (31 January

2007, 3 February 2008 and 11 November 2008),

with the same observation parameters: reference

system for planning (RSP) number 437, path

number 7050 and nadir angle 34.3º. Among the

three pairs generated from these data, the last

pair is the most accumulative one corresponding

to the longest interval time of about 92 weeks.Detailed parameters of each pair (interval time

and perpendicular baseline) are summarized in

Table 1. For DInSAR processing, we employed

the JAXA SIGMA-SAR software (Shimada,

1999). The DInSAR result can be derived by

using precise satellite orbital information, with

the help of Digital Elevation Model (DEM) of

Jakarta area obtained from the Shuttle Radar

Topography Mission (SRTM).

In addition to the DInSAR study, we conducteda ground survey of the study area in 28 January

to 3 February 2009.

disp atm noise topo flat φ φ φ φ φ φ∆ = + + + +

Table 1. ALOS/PALSAR pair and baseline information

PairData 1 Data 2 I n t e r v a l

(week)

Perpendicular

baseline (m)Date Mode Date Mode

1 20070131 FBS 20080203 FBS 52 220

2 20080203 FBS 20081105 FBS 39 840

3 20070131 FBS 20081105 FBS 92 618


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5. RESULTS AND DISCUSSION

The DInSAR results for the three pairs

are shown in Figure 2B-E. Figure 2B shows

the interferogram of Jakarta during the whole

time span

of this study, from January 2007 to

November 2008. Several subsidence areas can

easily be recognized in the northern part of the

city, where geological formations are mostly

alluvium and sand bar. In particular, signicant

phase variations are seen for four areas, for

which subsidence

features are detected in every pair of the DInSAR result, as well as in the GPS

measurement

conducted by Abidin et al (2007).

Different land type/usage can be associated with

each of the four points. Point 1 (P1), Mutiara,is a luxury residence area, tourism resort and

seaport built on a beach reclamation area. Point

2 (P2), Cengkareng, is a settlement area

which

covers an area of more than 23 km2 and the

international airport was built nearby. Point 3

(P3), Glodok, is the biggest trading region in

Jakarta, covering a wide area of more than 7

km2, with a large number of people commuting

to this area everyday. Point 4 (P4), Cakung, is an

industrial area in the northeast

part of Jakarta.Figure 2C-E shows the enlarged differential

SAR interferogram from every data pair (three

Figure 3. (A) Subsidence contours derived from the DInSAR interfero gram

overlaid on optic sensor image (TERRA/ASTER) (B-E) Enlarged

contour of P1-P4, respectively. Subsidence rate 5 cm/year has

been detected in every point and in Point 2 subsidence rate 15 cm/

year has been detected.


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interferograms) for P1-P

4 areas. Displacement

features in all points, except in DP4, where the

interferogram pattern is not clear due to noise.

The interferogram results of pair 1 (Figure 2C)

and pair 2 (Figure 2D) show the continuous

subsidence that occurred in the every

observation point. Even though the subsidence

may vary from time to time because of complexfactors, the cycle number of interferogram

shows that subsidence in a longer time interval

of 52 weeks (pair 1) is deeper than the one in a

shorter time interval of 39 weeks (pair 2). As

summarized in Table 2, the largest subsidence

of 26.6 cm and the largest subsidence area

coverage was observed for Cengkareng (P2)

and Glodok (P3), respectively, during the

whole study period between January 2007

and November 2008. Deformation contours

have been obtained by interpreting digitizing

the limits of interferograms (Figure 3). Every

contour indicates subsidence rate level.

Subsidence rate 5 cm/year has been estimated

in every observation point. Subsidence rate 15

cm/year has been detected in Cengkareng (P2).

The maximum subsidence rates found for P1-

P4 in this study time span are 9.3, 15.0, 9.2

and

6.5 cm/year, respectively. The result ofGPS measurement conducted by Abidin et al.

(2007), indicates that the maximum subsidence

rates calculated from GPS stations around

observation point are 12.5±0.2, 13.3±0.3,

6.5±0.2 and 10±1.2 cm/year, respectively. The

result of DInSAR and GPS shows similarity in

spite of the differences in the applied techniques

and study time (Table 3).

Figure 4 shows pictures taken at every

point during our ground survey in 2008,

indicating effects of subsidence that appear in

surface constructions. In Figure 4 P1-1 shows

the dam in Mutiara area (P1) built by a housing

developer and the government to prevent sea

water tide ood. Wall crack and subside surface

are also seen in Figure 4 P1-2. In Cengkareng

area (P2), many houses in settlement areas have

sunk beneath the road and land-surface levels as

shown in Figure 4 P2

-1 – P2

-2. A large number

of traders and costumers visit the center of

Glodok (P3) trading areas. The well-constructed

and well-maintained trading buildings did not

show any serious damages but smaller houses

show serious damages as seen in Figure 4 P3-1 –

P3-2. Figure 4 P

4shows the cracking brick fence

around the industrial area in Cakung (P4).

Various human activities such as ground water

pumping and construction working should

have affected the local subsidence phenomenain Jakarta, as in the case of other large-scale

cities (Delinom et al., 2009; Herrera et al,

Table 2. Observation’s points information

Point Name Area specication

Subsidence

coverage area

(km2)

Maximum subsidence

200701-200811 (cm)

1 MutiaraResidence, port and

recreation resort1.7 16.47

2 Cengkareng Settlement 4.4 26.63 Glodok Trading 7.5 16.34 Cakung Industrial 0.5 11.5

Table 3. GPS observation and DInSAR estimation result subsidence rate in cm/year

Point name

Observation periode

GPS observationDInSAR

estimation

199712-

199906

200006-

199906

200106-

200006

200110-

200106

200207-

200110

200212-

200207

200509-

200212

200811-

200702

Mutiara 0.8 0.5 5.3 1.2 9.2 4.9 12.5 9.3

Cengkareng 3 12.4 5.7 13.3 15.0

Glodok 3.3 0.7 3.5 6.3 6.5 9.2

Cakung 1.3 8.8 10 0.1 6 6.5


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2008; Raucoules et al., 2003). The main

cause of subsidence in Jakarta has not been

revealed because of the complex feature of

the phenomena. Nevertheless, the result ofthe present study strongly suggests that the

human activity and land use alteration are

inuencing the geomorphological changes in

this megacity.

6. CONCLUSION

We have shown that the application of

DInSAR technique to ALOS/PALSAR data can

reveal subsidence conditions in the study area.

Mostly the subsidence occurred in the northern

part of Jakarta city during the time interval

studied here, though the population density in

northern part is lowest among the entire city

regions. Industrial district, reclamation area,

trading center area, international airport and

the seaport are built in this region. The center

of the subsidence with the subsidence-affected

coverage area can also be estimated easily. It

has been found that the subsidence occurred

in separated regions with different land usage.

Nevertheless, the ground survey has indicated

that high human activity exists in every point

of subsidence.

The L-band ALOS/PALSAR DInSARresults have produced good results of urban

subsidence either in short or long time interval.

This ability is benecial to create temporal urban

subsidence map for further studies. Continuous

information of subsidence will be useful for

urban maintenance and urban development

eld, as one important factors for planning and

construction works. So far, only few subsidence-

related studies have been carried out using

ALOS/PALSAR data over urban area of Jakarta.

The continuation of DInSAR analysis based on

ALOS/PALSAR data combined with other in-

situ studies will contribute to elucidating the

cause of local subsidence

phenomenon with

appropriate prevention ideas.

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Figure 4. Images in observation areas.


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