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THESIS

MULTI-TEMPORAL ANALYSIS FOR DIFFERENTIAL INTERFEROMETRY SYNTHETIC APERTURE RADAR (D-InSAR) AND ITS APPLICATION TO

MONITORING LAND SURFACE DISPLACEMENTS

PUTU EDI YASTIKA

POSTGRADUATE PROGRAM

UDAYANA UNIVERSITY

DENPASAR

2015

THESIS

MULTI-TEMPORAL ANALYSIS FOR DIFFERENTIAL INTERFEROMETRY SYNTHETIC APERTURE RADAR (D-InSAR) AND ITS APPLICATION TO

MONITORING LAND SURFACE DISPLACEMENTS

PUTU EDI YASTIKA

NIM 1391261009

MASTER DEGREE PROGRAM

GRADUATE STUDY OF ENVIRONMENTAL SCIENCE


UDAYANA UNIVERSITY

DENPASAR

2015

ii

MULTI-TEMPORAL ANALYSIS FOR DIFFERENTIAL

INTERFEROMETRY SYNTHETIC APERTURE RADAR (D-InSAR) AND

ITS APPLICATION TO MONITORING LAND SURFACE

DISPLACEMENTS

Thesis to Get Master Degree at Graduate Study of Environmental Science

Postgraduate Program Udayana University

PUTU EDI YASTIKA

NIM 1391261009

MASTER DEGREE PROGRAM

GRADUATE STUDY OF ENVIRONMENTAL SCIENCE


UDAYANA UNIVERSITY

DENPASAR

2015

iii

AGREEMENT SHEET

THIS THESIS HAS BEEN APPROVED

ON AUGUST 25th, 2015

Knowing,

Head of Graduate Study

on Environmental Science

Postgraduate Program

Udayana University

Prof. Dr. I Wayan Budiarsa Suyasa, MS.

NIP. 196703031994031002

Director of

Postgraduate Program

Udayana University

Prof. Dr. dr. A.A Raka Sudewi, Sp.S(K).

NIP. 195902151985102001

iv

Multi-Temporal Analysis for Differential Interferometry Synthetic Aperture

Radar (D-InSAR) and Its Application to Monitoring Land Surface

Displacements

Thesis

Thesis to Get Master Degree

At Graduate Study of Environmental Science

Postgraduate Program Udayana University

By:

Putu Edi Yastika

Approved by:

Committee Member,

Asst. Prof. Dr. Takahiro Osawa

Committee Member,

Prof. I Wayan Arthana, MS. PhD.

NIP. 196007281986091001

Committee Member,

Dr. I Wayan Nuarsa, M.Si.

NIP. 196805111993031003

Committee Member,

Prof. Dr. I Wayan Budiarsa Suyasa, MS.

NIP. 196703031994031002

Head of Committee,

Prof. Made Sudiana Mahendra, PhD.

NIP. 195611021983031001

v

This Thesis Has Been Examined and Assessed

By the Examiner Committees of Postgraduate Program Udayana University

On August 13th, 2014

Based on the Letter of Agreement from Rector of Udayana University

Number : 2470/UN.14.4/HK/2015

Date : August 7th, 2015

The Examiner Committees are:

Head of Examiner : Prof. Made Sudiana Mahendra, PhD.

Members:

1. Prof. Dr. I Wayan Budiarsa Suyasa, MS.

2. Prof. Ir. I Wayan Arthana, MS, PhD.

3. Dr. Ir. I Wayan Nuarsa, M. Si.

4. Ass. Prof. Dr. Takahiro Osawa

vi

STATEMENT FREE FROM PLAGIARISM

The undersigned below:

Name : Putu Edi Yastika

Students ID : 1391261009

Dates of Born : Bengkel, August 2nd 1990

Address : Jalan Pendidikan, Gang Baja III/8 Denpasar

Thesis Title : Multi-Temporal Analysis for Differential

Interferometry Synthetic Aperture Radar (D-InSAR)

and Its Application to Monitoring Land Surface

Displacements

Hereby declare that the scientific work is plagiarism free. If in the future

prove to have plagiarism in scientific work, and then I am willing to accept

sanctions in accordance with the regulations of the Minister of Republic number 17

in 2010 and regulations applicable in the Republic of Indonesia.

Denpasar, August 2015

I respectfully,

Putu Edi Yastika

vii

ACKNOWLEDGMENTS

Om Swastyastu Awignam Astu Nama Sidham, I am grateful to Ida Sang

Hyang Widhi Wasa the almighty God for the good health and wellbeing that were

necessary to complete this Thesis.

It is with great pleasure that I present my sincere thanks to all those who

helped me to complete this work.

I would like to express my deep gratitude to Professor Norikazu Shimizu,

my supervisors, for his patient guidance, enthusiastic encouragement and useful

suggestions to finishing this research through dozens of research meeting. I would

also like to thank Professor Tasuku Tanaka, for his advice and support in keeping

my progress on schedule.

My sincere thanks to Dr. Masanobu Shimada for his valuable advice and

knowledge to enhancing this research. My sincere thanks also to Dr. Luhur Bayuaji,

Professor David Sandwell and Dr. Xiaopeng Tong for their valuable assistance to

installing and configuring GMTSAR on my PC.

I would like to thank all the examiner in Yamaguchi University for

accepting to review my work: Professor Fusanori Miura, Professor Tasuku Tanaka,

Associate Professor Motoyuki Suzuki and Dr. Sinichiro Nakashima. I also would

like to thank all the examiner in Udayana University for the reviewing on this work:

Prof. Made Sudiana Mahendra, PhD., Prof. Dr. I Wayan Budiarsa Suyasa, MS., Prof.

Ir. I Wayan Arthana, MS, PhD., Dr. Ir. I Wayan Nuarsa, M. Si., and Ass. Prof. Dr.

Takahiro Osawa and also to Prof. Dr. dr. A.A Raka Sudewi, Sp.S(K) as a director

of Post Graduate program of Udayana University.

I am belong to double degree program between Udayana University and

Yamaguchi University, many thanks to both universities principal for the chance,

facility and accepting me in this program. A lot of thanks also to the Government

of Republic of Indonesia for the financial support through the BUPKLN (Beasiwa

Unggulan Luar Negeri) scholarship.

I would like to thanks all of parties who, providing the data used in this

research: JAXA for the Alos-Palsar Data, NASA for the DEM data and Dr.Abidin

and Dr.Irwan Gumelar from the Geodesy Research of ITB for the GPS data on

Semarang.

viii

I wish to thank all Professor and Lecturer from Udayana and Yamaguchi

University who involved in my program study for the valuable knowledge and

experiences.

Special thanks to all friends belong to Shimizu Laboratory and Shinji

Laboratory: Uesaka san, Furuyama, Ito, Fujimoto, Kawaguchi, Okazaki, Ichihara,

Sakai, Nakashima, Sasaki, Kobayashi, Hayashi, Sakamoto, Terada, Iwamoto,

Okuda, Amafuji, Suma and Taguchi for the spirit support, hospitality, help and

convenient environment to study. I also thanks to all of my friend from Udayana

University: Rian, Arto, Hanggar, Yogi, Shanti, Putri, Nita, Olive, Tri, Ardi, Riri,

Dhita, Martiwi, Masita and many others for support and friendship.

The last, but not least I wish to thank my beloved Mother (Komang Yastini),

Father (Ketut Rauh) and Brother (Kadek Rudiantika) for their support, motivations,

loves and prayers. Also thanks to beloved Dian Meita Sari for hers loves,

motivations and patience.

Denpasar, August 2015

Putu Edi Yastika

ix

ABSTRAK

Analisis Multi-Temporal untuk Differential Interferometric Synthetic Aperture

Radar (D-InSAR) dan Aplikasinya untuk Pemantauan Pergeseran

Permukaan Tanah

Tingkat penurunan permukaan tanah (land subsidence) di Semarang telah

diamati dengan teknik D-InSAR berdasarkan data ALOS PALSAR pada orbit

ascending dan descending. D-InSAR diproses dengan menggunakan software

GMTSAR dan ArcGIS. Dua jenis strategi yaitu Single D-InSAR dan Multi-

Temporal D-InSAR dipilih untuk diaplikasikan pada studi ini. Untuk menghapus

komponen topografi menggunakan data DEM SRTM3 dan ASTER1DEM,

sejumlah 67 pasang inteferogram telah dihasilkan. Daerah timur laut dan daerah

pantai teramati telah terjadi penurunan muka tanah sekitar 200-320 mm selama 4

tahun atau rata-rata tingkat 50-80 mm / tahun. Karena daerah barat laut dan daerah

pusat, memiliki tingkat penurunan yang lebih rendah dan bahkan tidak ada

penurunan yang teramati, daerah ini tampaknya lebih stabil membandingkan daerah

timur laut. Fase dari komponen topografi yang dihapus dari interferogram dengan

menggunakan SRTM3 DEM dan data DEM ASTER1, keduanya menghasilkan

hasil yang sangat mirip dengan nilai korelasi 0,995. Ambang batas koherensi

merupakan faktor penting untuk mendapatkan akurasi yang lebih baik, tetapi jika

pengaturan ambang batas terlalu tinggi, proses interferensi akan gagal dan tidak

mampu mendapatkan hasil di banyak daerah. Perpendicular baseline dan temporal

baseline merupakan faktor penting untuk menentukan ambang batas koherensi.

Dengan menggunakan banyak SAR data, Multi-Temporal D-InSAR diterapkan, dan

dengan memilih hanya pada interferogram yang dianggap baik, keakuratan hasilnya

akan meningkat. Nilai korelasi hasil dari Multi-Temporal D-InSAR dengan GPS

meningkat dari 0,63 menjadi 0,77. Untuk memperkirakan penurunan muka tanah

akhir, pengabungan metode Multi-Temporal D-InSAR dan metode hiperbolik

diusulkan dalam penelitian ini. Dengan menggunakan penggabungan dua metode

tersebut, subsidence akhir diperkirakan mencapai lebih dari 50 cm dan terjadi lebih

dari 50 tahun untuk stabil.

Kata Kunci: ALOS-PALSAR, D-InSAR, GPS, Metode hiperbolik, Multi-

Temporal method, Penurunan permukaan tanah.

x

ABSTRACT

Multi-Temporal Analysis for Differential Interferometry Synthetic Aperture

Radar (D-InSAR) and Its Application to Monitoring Land Surface

Displacements

Land subsidence rate in Semarang has been observed by D-InSAR

technique based on ALOS-PALSAR data on ascending and descending orbits,

which is processed by GMTSAR and ArcGIS software. Two kind of strategy

namely single D-InSAR and Multi-Temporal D-InSAR has been done. By

employing SRTM3 and ASTER1 DEM data to remove the topography component,

total 67 pairs of inteferogram has generated. Northeast area and shoreline area has

largest subsided about 200-320 mm for 4 years or average rate 50-80 cm/year. Since

the northwest area and center area has lower subsidence rate and even no

remarkable subsidence occurred, this area seems to be stable comparing the

northeast area. Removing the topography component phase to get displacement

phase from the phase interferogram by using SRTM3 DEM and ASTER1 DEM

data respectively, the both results coincided with 0.995 correlation value. The

coherence threshold is an important factor to get better accuracy, but if setting the

threshold too high, the process of interference will be failed and not be able to obtain

the results in a lot of area. The perpendicular baseline and the temporal baseline

(time period) is an important factor to determining the coherence threshold. By

using many scenes the Multi-Temporal D-InSAR was applied, and by selecting only

good pairs of the scenes the accuracy of the results will be improved. The

correlation value for GPS data eventually increased from 0.63 to 0.77. In order to

estimate the final subsidence, a method coupling the Multi-Temporal D-InSAR and

hyperbolic method was proposed in this study. By using the method the final

subsidence was predicted to reach more than 50 cm and to take more than 50 years

for settling down.

Keywords: ALOS-PALSAR, D-InSAR, GPS, Hyperbolic method, Land

Subsidence, Multi-Temporal method.

xi

SUMMARY

Putu Edi Yastika, Multi-Temporal Analysis for Differential Interferometry

Synthetic Aperture Radar (D-InSAR) and Its Application to Monitoring Land

Surface Displacements

Interferometric Synthetic Aperture Radar (InSAR) is a powerful

technology for observing the Earth surface, especially for mapping the Earth's

topography and deformations (Hanssen, 2003). From previous study on InSAR

concludes, some factor affected on its accuracy. These factors affected on the

coherence of two images, and determination of coherence threshold become the

important point. Another factor severely decreasing the accuracy of InSAR is

atmospheric disturbance. Many scientist are study in mitigating on atmospheric

effect on InSAR such as, Shimada (2014), Xiao-li (2008), and Wadge (2002).

Removing the atmospheric effects especially by ionospheric disturbance needs

sophisticated technique and programs and this problems is challenging on

improvement of InSAR accuracy.

Although the application of D-InSAR by single pair interferogam has a

good result, but when applying to derive the subsidence for long periods, it is will

lose their coherence. Time series analysis by using only single inferogram also not

possible, because of that in this study not only generating for single inteferogram

but also multi-temporal interferogram. By applying the multi-temporal

interferogram method the land subsidence behavior of the chosen observation point

can be obtained.

The study area is Semarang City Indonesia, this is the main city in Central

Java with a dense population which industry activity as a main business. Semarang

extremely threatened by land subsidence that make some buildings and

infrastructure sinking to the ground. Land subsidence phenomena in Semarang has

been observed by many researcher with various method and discipline such as

InSAR method (Kuehn et al., 2009, Leveling method (Marfai and King 2005),

Gravity method (Sarkowi et al., 2005) and Global Positioning System (GPS) by

Geodesy Reseach group of Institute of Technology Bandung ITB (Abidin et al.,

2008-present). Monitoring of land subsidence in this area should be continued and

the accuracy should be improved especially on D-InSAR technique. This research

result compared to Geodesy research group (ITB) results, as a validation of the

InSAR result to the GPS result.

All pairs both of ascending and descending direction data has been

processed, the coherence, phase interferogram, phase filtering, phase masking,

phase unwraping and geocoding has been done by using GMTSAR. Single D-

InSAR has a bigger correlation to GPS data instead of Multi-Temporal D-InSAR in

this case. Comparing to GPS data single D-InSAR has root mean squared error

(RMSE) 4.27 cm for observation during 2008-2009 and 5.47 cm for 2009-2010

respectively. On the other hand RMSE value of multi-temporal D-InSAR is 4.57

xii

cm for observation during 2008-2009 and 5.21 cm for 2009-2010 respectively.

By setting the higher coherence threshold in D-InSAR resulting the higher

correlation to the GPS data which is 0.84576 while coherence threshold set at 0.25

comparing to 0.69893 while coherence threshold set at 0.13. The RMSE for

threshold at 0.25 also smaller than threshold at 0.13. In general higher coherence

threshold will lead better accuracy in subsidence monitoring. But the higher

coherence threshold resulting many area loss of their data.

Although subsidence rate derived by multi-temporal D-InSAR has worse

correlation than single D-InSAR comparing to GPS data, but multi-temporal D-

InSAR providing the time series analysis which that is impossible in single D-

InSAR. There are three major pattern of land subsidence in Semarang, North east

area seem has a largest subsidence comparing to another area.

By using ArcGIS software, the map of Subsidence rate can be made based

on multi-temporal D-InSAR results. Subsidence rate for 4 years derived by using

multi-temporal D-InSAR which the topography phase removed by using SRTM3-

DEM. Northeast area and shoreline area seem has largest subsidence range 200-320

mm for 4 years or average rate 50-80 mm/year, at the northwest area subsidence

observed at lower rate about 20-80 mm for 4 years or 5-20 mm/year in center area

there is no subsidence or slightly uplifted relative to reference point.

In order to predict the final subsidence, the hyperbolic method (Tan, et al

1991) is adopted in this study. From those results, Semarang city will settle down

for some decades into future. In the area including the point RMPA the subsidence

may continue for more than 73 years and will exceed more than 82 cm. The periods

of subsidence depend on ground condition of those area, which is composed by

alluvium with low permeability. On the other hand, the point 1124 and K370 which

lies on sandy and gravel area has shorter periods to reach the final subsidence

conditions that is not more than 3 decades and also amount of subsidence is smaller

than other points. The estimation of final subsidence by coupling on Multi-

Temporal D-InSAR and Hyperbolic method was proposed in this study.

xiii

TABLE OF CONTENTS

Page

INSIDE COVER i

PREREQUISITE ii

AGREEMENT SHEET iii

APPROVED BY COMMITTEES iv

EXAMINERS OF THESIS v

STATEMENT FREE FROM PLAGIARISM vi

ACKNOWLEDGMENTS vii

ABSTRAK ix

ABSTRACT x

SUMMARY xi

TABLE OF CONTENTS xiii

LIST OF TABLES xvi

LIST OF FIGURES xvii

LIST OF ABBREVIATIONS xxi

LIST OF APPENDIX xxiii

CHAPTER I INTRODUCTION 1

1.1 Background 1

1.2 Problems Formula 4

1.3 Research Objectives 4

1.4 Benefit of the Research 5

CHAPTER II BASIC THEORY 6

2.1 Remote Sensing 6

2.1.1 Definitions 6

2.1.2 Types of Remote Sensing 7

2.2 Radar Remote Sensing 8

2.2.1 Radar Remote Sensing Satellites 9

2.2.2 ALOS-PALSAR System Overview 10

2.3 Basic Concept of Synthetic Aperture Radar (SAR) 13

xiv

2.3.1 Observation Geometry and Principles of SAR

Imaging 16

2.3.2 SAR Geometric Resolution 17

2.3.3 Geometrical Effects Introduced by SAR 21

2.4 Interferometry SAR (InSAR) Basic 26

2.4.1 Geometrical Equations of CT-InSAR 27

2.4.2 Contributors to Signal Phase 29

2.4.3 Coherence 30

2.4.4 Applications 31

2.5 Differential InSAR (D-InSAR) 32

2.5.1 D-InSAR Processing to Land Deformation

Monitoring 32

2.5.2 Derivation of Land Subsidence from LOS

Displacement 35

2.6 D-InSAR Processor, GMTSAR 36

2.7 Reviews of Application of D-InSAR to Land Displace-

ment Monitoring 39

CHAPTER III RESEARCH FRAMEWORK AND CONCEPT 41

3.1 Research Framework 41

3.2 Research Concept 42

CHAPTER IV RESEARCH METHOD 44

4.1 Study Area 44

4.2 Data Collections 45

4.2.1 Primary Data 45

4.2.1.1 SAR Images 45

4.2.1.2 Digital Elevation Model (DEM) data 48

4.2.2 Secondary Data 50

4.3 D-InSAR Generation by Images on Ascending Orbit 51

4.3.1 Selecting Pairs of Interferogram to Single D-InSAR 53

4.3.2 Selecting Pairs of Interferogram to Multi-Temporal

D-InSAR 53

4.3.3 Selecting Pairs of Interferogram to Avoid Ionos-

pheric and Orbital Error on Multi-Temporal 54

4.4 D-InSAR Generation by Images on Descending Orbit 55

xv

4.5 Land Subsidence Derivation Flowchart 55

CHAPTER V RESULTS AND DISCUSSIONS 57

5.1 Results of D-InSAR on Ascending Orbits 57

5.1.1 Coherence 58

5.1.2 Phase Interferogram 59

5.1.3 Line of Sight (LOS) Displacement 59

5.2 Results of Descending Orbits 60

5.2.1 Coherence 60

5.2.2 Phase Interferogram 61

5.2.3 Line of Sight (LOS) Displacement 61

5.3 Discussions of Ascending Results 61

5.3.1 Phase Interferogram Pairs for Derive Subsidence

By Single D-InSAR and Multi-Temporal D-InSAR 61

5.3.2 Subsidence Rates for Each Observation point Deri-

ved by Single D-InSAR and Multi-Temporal D-

InSAR 62

5.3.3 Comparison of Single and Multi-Temporal D-

InSAR Result with GPS data 64

5.3.3.1 SRTM3 DEM and ASTER1 DEM Issues 69

5.3.3.2 The Coherence Thresholds Issues 71

5.3.4 Subsidence Rate inn Time Series Analysis 74

5.3.5 Correction of Multi-Temporal D-InSAR From

Ionospheric and Orbital Error 83

5.4 Discussions of Descending Results 94

5.5 Comparison of Ascending and Descending Results 96

5.6 Map of Subsidence Rate of Semarang City 102

5.7 Prediction of Land Subsidence by Using Hyperbolic

Method 104

CHAPTER VI CONCLUSION AND SUGETION 110

6.1 Conclusion 110

6.2 Suggestion 111

REFERENCES 112

APPENDICES 115

xvi

LIST OF TABLES

Page

2.1 Frequency and wavelength for microwave bands (Lusch, 1999) 8

2.2 Processing Levels and Their Definitions 11

2.3 Processing Levels of Observational Modes 12

2.4 File names and its content on ALOS-PALSAR product format 12

2.5 Selected fields of SAR application examples. Note that not all

applications are in practical use; many applications are still at

developing stages Ouchi,2013) 14

2.6 Highlights of SAR History with space emphasis, modified from USA

SAR Marine User’s Manual 15

4.1a ALOS-PALSAR data set on ascending orbit used in the study, all

data has same observation path number (431) and same Center

frame number (7040) 46

4.1b ALOS-PALSAR data set on Descending orbit, that use in the study,

all data has same observation path number (96) and same Center

frame number (3760) 47

4.2 Data acquisition date of ALOS-PALSAR and GPS 47

4.3 The Comparison of ASTER GDEM data and SRTM3 DEM

data (jspacesystems.or.jp, 2015) 49

4.4 Interferogram pairs information for ascending orbit 54

5.1 Baseline perpendicular information for each pair on ascending orbit 57

5.2 Baseline perpendicular information of each pair has generated 60

5.3 Correlation value and RMSE for both of coherence threshold

(0.13 and 0.25) for Single and Multi-temporal D-InSAR 74

5.4 Results of subsidence parameter to predict the land

subsidence by hyperbolic fitting method, and its results 109

xvii

LIST OF FIGURES

Page

2.1 Satellite radar system available now and into the future 9

2.2 Picture of Alos satellite with the its parts (eorc.jaxa) 11

2.3 SAR geometry (1): Off-nadir angle (2): Depression angel

(3): Range beam width (4): Incidence angle (5): Azimuth beam

width (source: Restec/Jaxa) 16

2.4 The illustration how SAR work to make an radar imagery

(adopted and modified from Restec/Jaxa) 17

2.5 The relationship between the ground range (Δx) and slant range (ΔR).

The distance (height) of spacecraft from the ground surface

represent as H 18

2.6 Top view of SAR antenna imaging a point reflector (P) 19

2.7 Schematic illustration showing how mountainous terrain can create

noise through layover and shadow effects (Farretti et al, 2007) 22

2.8 Illustration of foreshortening effect on radar imaging

system. Foreshortening effect occurs as long as the slope of the

terrain is smaller than the local incidence angle 24

2.9 An example of SAR image of Mount Fuji Japan. Yellow circle

area in the image severely affected by shadow, dark color representing

no energy backscattered from those are 25

2.10 Illustration of Geometry of repeat pass CT-InSAR (left) and

AT-InSAR (right) 26

2.11 InSAR geometry: B-the base line; Br-the radial base line;

Bn-the normal baseline (Lazarov, 2010) 27

2.12 Flow chart of focusing process to form Single Look Complex (SLC)

image from raw SAR image 33

2.13 Illustration of processing stage to obtain Line of Sight (LOS)

displacement by D-InSAR technique, (source: Wang, etal 2013) 35

2.14 Illustrations of the relation between LOS displacement and

subsidence or vertical displacement (Z) observed in

ascending and descending direction (A) 36

2.15 Flow diagram of two-pass processing in GMTSAR 37

3.1 Research Flowchart 42

3.2 Research concept 43

xviii

4.1 Semarang city location on a map (Google earth image, 2015) 45

4.2 An example of superimposed of phase InSAR image to DEM image 48

4.3 Images of Digital Elevation Model (DEM) of Semarang city

and surrounding area to remove topography phase in this study,

(A) for ASTER DEM and (B) for SRTM3 DEM 50

4.4 The GPS stations for land subsidence in Semarang city by

Abidin et al (2012) 51

4.5 Flow diagram of two-pass processing in GMTSAR 56

5.1 Subsidence rate for 2008-2009 of each observation points

observed by GPS and D-InSAR. Subsidence period taken by

GPS and D-InSAR in July 2008-June 2009 63


observed by GPS and D-InSAR. Subsidence data taken by GPS

for June 2009-July 2010, while for June 2009-June 2010

by D-InSAR 63

5.3 Correlation GPS with Multi-Temporal D-InSAR and Single

D-InSAR (dem SRTM3) for subsidence during 2008-2009 65

5.4 Correlation GPS with Multi-Temporal D-InSAR and Single D-InSAR

(dem ASTER1) for subsidence during 2008-2009 66


(dem SRTM3) for subsidence rate during 2009-2010 67

5.6 Correlation GPS with Multi-Temporal D-InSAR and Single

D-InSAR (dem ASTER1) for subsidence during 2009-2010 68

5.7 Correlation of Multi-Temporal D-Insar obtained by utilizing

SRTM3 DEM data and ASTER1 DEM data to remove topography

phase during observation in 2008-2009 69

5.8 Correlation of Multi-Temporal D-Insar obtained by utilizing SRTM3

DEM data and ASTER1 DEM data to remove topography phase

during observation in 2009-2010 70

5.9 Chart of the difference in the altitude direction from DEM and

SAR in relationship with Baseline perpendicular for ALOS-PALSAR

(GSI, 2004) 71


(dem SRTM3) for subsidence rate during 2008-2009 where

the coherence threshold is 0.25 72

xix


(dem SRTM3) for subsidence rate during 2009-2010 where

the coherence threshold is 0.25 73

5.12 In this Figure showing the pattern of subsidence globally,

for each observation point obtained by Multi-Temporal

D-InSAR on ascending orbit 75

5.13 Pattern of land subsidence of 12 observation points derived

by Multi-Temporal D-InSAR during Jan 2007-Dec 2010 78

5.14 There are 3 major pattern of land subsidence in Semarang city

distinguished in dash orange circle, blue circle and black area 83

5.15 Phase Interferograms pair state 84

5.16 Comparison of subsidence pattern obtained by Multi-Temporal

D-InSAR before corrected (orange lines) and after excluding

the pairs that suspected has large error (after corrected) represent

by blue lines 86

5.17 The Subsidence pattern of each observation point during

Jan 2007- Dec 2010 derive by multi-temporal D-InSAR after

correction on its combination 90


observed by GPS and Multi-Temporal D-InSAR before and after

corrected 93

5.19 Correlation of subsidence data derived by GPS and

Multi-Temporal D-InSAR after and before correction of pair

combination land subsidence observation during 2009-2010 94

5.20 Phase interferogram state of Descending direction images 95

5.21 Subsidence rate of each observations points relative to reference

point (SMG1) during September 2007-August 2009,

observed at descending orbit 96

5.22 Comparison of subsidence for each points observed at ascending

and descending orbits during June-September 2007 97

5.23 Comparison of subsidence for each points observed at ascending

and descending orbits during September 2007-December 2008 97

5.24 Comparison of the subsidence pattern in time series analysis

observed at ascending orbits and descending direction for

selected observation points 99

xx

5.25 Map of Subsidence rate map of the Semarang city derived

by ALOS-PALSAR Multi-Temporal D-InSAR for 4 years

(Jan 2007 –Dec 2010) 103

5.26 Land subsidence in Semarang during January 2007 to Dec 2010

derived by ALOS-PALSAR data using Multi-Temporal D-InSAR

methods, superimposed on the Google eye image was taken

on March 2007 104

5.27 Landsat 7 image (gap-filled, slc-off, bands 4/R, 5/G, 7/B)

taken on September 17, 2006 showing the investigation area

(dashed frame) and simplified geological section AB (not to scale)

(Kuehn, et al 2009) 105

5.28 Selected observation point on map, to analyzing of its subsidence

behavior from geotechnical view point 106

5.41 The land subsidence value plotted against its periods, both of

measured by Multi-Temporal D-InSAR (blue dots) and prediction

(orange lines) 107

xxi

ABREVIATIONS LIST

ADSP : Advanced Digital SAR processor

AIRSAR : Air-borne Synthetic Aperture Radar

ALOS : Advanced Land Observation Satellite

ALOS-AVNIR2 : ALOS-Advanced Visible Near Infrared2

ALOS-PALSAR : ALOS-Phase Array L Synthetic Aperture Radar

ALOS-PRISM : ALOS-Panchromatic Remote-sensing Instrument

for Stereo Mapping

ASTER : Advanced Spaceborne Thermal Emission and

Reflection Radiometer

AT-InSAR : Along Track-InSAR

CCRS : Canadian Center of Remote Sensing

CLI : Command Line Interface

CEOS : Committee on Earth Observation Satellites

CT-InSAR : Cross Track-InSAR

DEM : Digital Elevation Model

DSM : Digital Surface Model

D-InSAR : Differential InSAR

ERS-1, ERS-2 : European Remote Sensing Satellites 1-2

ESRI : Environmental System Research Institute

FBD : Fine Beam Dual

FBS : Fine Beam Single

FORTRAN : Formula Translating System

KOMPSAT : Korean Multi-Purpose Satellites

GDEM : Global Digital Elevation Model

GIS : Geographic Information System

GMTSAR : Generic Mapping Tools SAR

GPS : Global Positioning System

GSI : Geospatial Information Authority

ITB : Institut Teknologi Bandung (Bandung Technology

Institute).

In-SAR : Interferometric Synthetic Aperture RADAR

JAXA : Japan Space Exploration Agency

JPL : Jet Propulsion Laboratory

LANDSAT : Land Satellite

xxii

LOS : Line of Sight

NASA : National Aeronautics and Space Agency

RADAR : Radio Detection and Ranging

RISAT : Radar Imaging Satellites

RMSE : Root Mean Square Error

SAR : Synthetic Aperture Radar

SIR-C : Shuttle Imaging Radar-C

SLC : Single Look Complex

SNAPHU : Statistical-cost Network-flow Algorithm for Phase

Unwrapping

SPOT : Satellite Pour l’Observation de la Terre

SRTM : Shuttle Radar Terrain Mission

TInSAR : Terrestrial SAR Interferometry

UAV : Unmanned Aerial Vehicle

xxiii

LIST OF APPENDIX

Page

1 DEM generation steps 173

2 Table of Subsidence values 174

3 Images of the Correlation of Master and slave image for each pair 122

4 Images of the Phase of D-InSAR (topographic phase component

removed using SRTM3-DEM) 124

5 Images of the Phase of D-InSAR after unwrapping, process

continued to obtain LOS displacement 140

6 Images of the Correlation of Master and slave image for each

pair in Descending direction 148


removed using SRTM3-DEM) 151

8 Images of the Phase of D-InSAR after masking, the phase below

the threshold was removed, showing by dark grey area in the image154

9 Images of the Phase of D-InSAR after unwrapping, process

continued to obtain LOS displacement 156


removed using SRTM3-DEM), the coordinates system already

converted to geographic coordinates from radar coordinates 158


removed using ASTER1-DEM), the coordinates system already

converted to geographic coordinates from radar coordinates 160

12 Geocoded of Phase interferogram masked at coherence threshold

0.25 to derive the subsidence during July 2008 until June 2010 162

13 The inteferogram that involved in corrected Multi_temporal

D-InSAR on ascending orbit 163

14 The phase interferogram that involve to derive land subsidence

observed at descending orbit 164

15 Subsidence data derived by using selected interferogram at

descending orbit. 165

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