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THESIS

EXTRACTION OF TSUNAMI DAMAGED AREAS DUE TO THE 2010 CHILEAN EARTHQUAKE USING

OPTICAL AND SAR DATA OF ALOS

Thesis to Get Master Degree at Master Program of Environmental Science Postgraduate Program Udayana University

NI MADE PERTIWI JAYA NIM 1391261029

MASTER DEGREE PROGRAM

STUDY PROGRAM OF ENVIRONMENTAL SCIENCE POSTGRADUATE PROGRAM

UDAYANA UNIVERSITY DENPASAR

2015

iii

AGREEMENT SHEET

THIS THESIS HAVE BEEN APPROVED On September 8th, 2015

Knowing,

Director of Postgraduate Program Udayana University

Prof. Dr. dr. A. A. Raka Sudewi, Sp.S (K) NIP. 195902151985102001

Head of Graduate Study of Environmental Science

Postgraduate Program Udayana University

Prof. Dr. I Wayan Budiarsa Suyasa, MS.

NIP. 196703031994031002

iv

EXTRACTION OF TSUNAMI DAMAGED AREAS DUE TO THE 2010 CHILEAN EARTHQUAKE USING OPTICAL

AND SAR DATA OF ALOS

Thesis

Thesis to Get Master Degree At Graduate Study of Environmental Science Postgraduate Program Udayana University

By:

NI MADE PERTIWI JAYA

Approved by Committee

Committee Member,

Ass. Prof. Dr. Takahiro Osawa

Committee Member,

Dr. Ir. I Wayan Nuarsa, M. Si. NIP. 196805111993031003

Committee Member,

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

NIP. 196007281986091001

Head of Committee,

Prof. Made Sudiana Mahendra, PhD. NIP. 195611021983031001

Secretary of Committee,

Prof. Dr. I Wayan Budiarsa Suyasa, MS.

NIP. 196703031994031002

v

THIS THESIS HAS BEEN EXAMINED AND ASSESSED

On August 13th, 2015

Based on the Letter of Agreement from the Rector of Udayana University

Number : 2469/UN.14.4/HK/2015

Date : August 7th, 2015

The Examiner Committee are:

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

Secretary of Committee : Prof. Dr. I Wayan Budiarsa Suyasa, MS.

Members:

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

2. Ass. Prof. Dr. Takahiro Osawa

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

vi

STATEMENT FREE FROM PLAGIARISM

The undersigned below:

NAME : Ni Made Pertiwi Jaya

NIM : 1391261029

PLACE, DATE OF BIRTH : Singaraja, June 16th, 1990

ADDRESS : Jalan Tukad Batanghari IV A/ 8

Denpasar, Bali 80225

THESIS TITLE : Extraction of Tsunami Damaged Areas

due to the 2010 Chilean Earthquake

Using Optical and SAR Data of ALOS

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,

Ni Made Pertiwi Jaya

vii

ACKNOWLEDGEMENT

Firstly, the author would like to express sincere gratitude to the Almighty “Ida Sang Hyang Widhi Wasa” for a grace, kindness and blessing in finishing this master thesis. The title of this thesis is “Extraction of Tsunami Damaged Areas Due to the 2010 Chilean Earthquake Using Optical and SAR Data of ALOS”. This thesis is focused on the use of satellite data for disaster mitigation.

In this opportunity, the author would like to acknowledge: 1. Prof. Dr. dr. Ketut Suastika, Sp.PD KEMD as the Rector of Udayana

University. 2. Prof. Dr. dr. A. A. Raka Sudewi, Sp.S (K) as the Director of Postgraduate

Program Udayana University. 3. Prof. Dr. I Wayan Budiarsa Suyasa, MS. as the Head of Graduate Study of

Environmental Science Postgraduate Program. 4. Prof. Tasuku Tanaka as the special professor for the master course join degree

program of the Udayana University and Yamaguchi University. 5. Prof. Fusanori Miura as the supervisor of this master thesis for the dedication,

suggestion, and motivation. 6. The examiner committee in Yamaguchi University; Prof. Tasuku Tanaka,

Prof. Norikazu Shimizu, Prof. Koji Asai, and Prof. Motoyuki Suzuki for the input, advises and guidance of the master thesis writing.

7. The examiner committee in Udayana University; Prof. Made Sudiana Mahendra, PhD., Prof. Dr. I Wayan Budiarsa Suyasa, MS., Prof. Ir. I Wayan Arthana, MS, PhD., Ass. Prof. Dr. Takahiro Osawa, and Dr. Ir. I Wayan Nuarsa, M. Si. for the suggestions in order to improve this master thesis.

8. The Bureau of Planning and International Cooperation of the Ministry of National Education and Culture of the Republic of Indonesia for the funding through Beasiswa Unggulan framework. The funding has been used for the completion of the master degree join program between Udayana University and Yamaguchi University.

9. Academic section staffs in Yamaguchi University and Udayana University for providing all necessary information related to the master study.

10. Laboratory members of the Disaster Prevention System Engineering Laboratory, Department of Environmental Science and Engineering, Faculty of Engineering and all Indonesian students in Yamaguchi University for the help and motivation in finishing this research.

11. The 2013 students of the Study Program of Environmental Science, Postgraduate Program, Udayana University for the friendship and support.

12. Family members, especially father, mother, older brother and younger brother for the love, support, and understanding.

The author realizes that this thesis is not yet perfect. Therefore, the author expects the constructive suggestion and criticism from readers.

Denpasar, August 2015

Author

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ABSTRAK

Ekstraksi Daerah Bencana Akibat Tsunami pada Kejadian Gempa Chili Tahun 2010 Menggunakan Data Optikal dan SAR dari ALOS

Informasi tentang daerah yang mengalami kerusakan akibat bencana sangat penting berkaitan dengan berbagai kejadian bencana yang terjadi di seluruh dunia. Beberapa tahun terakhir, aplikasi penginderaan jauh baik optikal maupun SAR mulai diterapkan di berbagai penelitian mengenai bencana, salah satunya deteksi kerusakan akibat tsunami. Dalam penelitian ini, citra ALOS AVNIR-2 dan PALSAR digunakan untuk mengekstrak daerah bencana akibat gempa Chili tahun 2010.

Dalam pengolahan ALOS/AVNIR-2, daerah genangan diekstraksi berdasarkan analisa NDVI dan proses klasifikasi. Selanjutnya, daerah kerusakan dari citra ALOS/PALSAR diperoleh dengan mengintegrasikan citra AVNIR-2 dan DEM untuk proses masking (air dan elevasi). Daerah bencana yang diperoleh dari proses pengolahan citra AVNIR-2 adalah 8,91 Km2 dan dari ekstraksi citra PALSAR adalah 8,72 Km2 yang berada di sepanjang daerah pesisir.

Hasil ekstraksi citra menunjukkan hasil yang baik dimana daerah bencana sesuai dengan peta institusional daerah genangan di Chili. Penelitian lebih lanjut di daerah lain diperlukan untuk memperkuat metode pengolahan data yang digunakan.

Kata kunci: Daerah Bencana Tsunami, Data Optikal dan SAR, ALOS

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ABSTRACT Extraction of Tsunami Damaged Areas Due to the 2010 Chilean Earthquake

Using Optical and SAR Data of ALOS

Information about damage areas is important due to the large-scale disasters worldwide. In the last decade, both optical and SAR remote sensing were applied in many disaster researches, such as tsunami damage detection. In this study, the ALOS AVNIR-2 and PALSAR images are used to extract the damaged areas caused by the 2010 Chile earthquake.

In the processing of ALOS/AVNIR-2, the inundation area was estimated based on the NDVI calculation and classification. Furthermore, damaged areas of the ALOS/PALSAR are extracted by integrating the AVNIR-2 image for water mask and the DEM image for elevation mask. The damaged area result of AVNIR-2 is 8.91 Km2 and for the PALSAR is 8.72 Km2 that is along the coastal areas.

The image results showed a good agreement and corresponding area according to the institutional map of the inundation area. Future study in another area is needed in order to strengthen the processing method. Keywords: Tsunami Damage Areas, Optical and SAR Data, ALOS

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SUMMARY

In the past, acquiring tsunami damage information was limited to only field surveys or using aerial photographs. In the last decade, remote sensing was applied in many tsunami researches, such as tsunami damage detection. Recently, space missions such as Advanced Land Observation Satellite (ALOS) has concerned both optical and Synthetic Aperture Radar (SAR). The AVNIR-2 data can be useful in identifying major incidents, such as disaster areas. The extraction using ALOS PALSAR is also considered to be able to conduct by utilizing a microwave property which irradiated from SAR. The aims of this research are to investigate the ability of ALOS data both optical (ALOS/AVNIR-2) and SAR (ALOS/PALSAR) in extracting the tsunami damaged areas and to compare both of the imageries of analysis of damaged areas caused by the 2010 Chile earthquake.

Study areas are Talcahuano and Conception which are areas near the epicenter of the earthquake and experienced a huge damaged along the coastal area caused by the tsunami. Data that were used in this study are ALOS/AVNIR-2 and ALOS/PALSAR images before and after tsunami, ASTER GDEM, QuickBird image, and institutional map of inundation area in Talcahuano, Chile. Research softwares used in this study are ENVI 4.8, ArcMap 10 on ArcGIS, and Microsoft Office Excel. The extraction of damaged areas from optical data of ALOS/AVNIR-2 is conducted by obtaining the NDVI index. It is obtained from the data before and after the 2010 Chilean earthquake in Chile. There are some processes for analyzing AVNIR-2 data, such as obtain absolute value of the difference between the image before and after tsunami, classification-segmentation, and small noise removal. The result is the area of tsunami damaged areas based on the extraction process. Image processing techniques for extracting tsunami damaged areas from PALSAR consists of three stages that are pre-processing, analysis processing, and post-processing. In the analysis processing, the near-infrared (NIR) band data of ALOS/AVNIR-2 is used as a waters mask for creating data of water area. A digital elevation model image is also used as elevation mask for creating data to integrate and improve the extraction accuracy. The processes in pre-processing are speckle noises removal and conversion of the DN value into backscatter coefficient. Images before and after the disaster after conducted the pre-processing will be used to obtain an absolute difference image. This is the first stage of the analysis processing. Then the image is used to extract tsunami damaged areas by applying some processes. Those processes are binarization process to divide water and another area, water mask processing to clearly show water areas in the image, median filter process for reducing some disturbances in the image, elevation mask processing to mask the image based on the tsunami inundation height, and very small region removal. After removing some very small regions which are not necessary, the area calculation can be done to obtain the area of tsunami damaged areas.

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Coastal Chile has a history of very large earthquakes. Since 1973, there have been 13 events of magnitude 7.0 or greater. The February 27th shock originated about 230 km north of the source region of the magnitude 9.5 earthquake of May, 1960 which was the largest earthquake worldwide in the last 200 years or more. This giant earthquake spawned a tsunami that engulfed the Pacific Ocean. The earthquake produced a tsunami that caused major damage locally over 500 km of coastline, from Tirúa to Pichilemu, and at the Juan Fer-nandez Islands about 600 km off the coast. Around the Pacific, the tsunami was recorded at over 150 locations, triggering tsunami alerts (Warnings/Advisories) in 54 countries and territories.

The extraction of damaged areas in Talcahuano and Concepcion from the optical image of ALOS/AVNIR-2 was obtained by calculating the NDVI on both the image before and after the disaster. Then some processes were conducted using the image result of NDVI, such as binarization, classification and majority analysis. Those processes were performed in order to extract the damage area. Some parts are obtained as inundation area from the image processing, such as areas along the coast, area near the airport and some parts around rivers. The area of inundation which is obtained from the image is 8.91 Km2.

Furthermore, the extraction of damaged areas due to the 2010 Chilean earthquake from the SAR image of ALOS/PALSAR also shows that some parts such as such as areas along the coast, area near the airport and some parts around river are the inundated area caused by tsunami. Since the PALSAR image cannot be able to observe visually there are more processes are needed to be able to obtain damage areas. The extraction process mainly consists of three steps, i.e. pre-processing, analysis processing and post-processing.

In the pre-processing, the image are registered, calibrated into backscatter coefficient and filtered in order to reduce noises. After the pre-processing, there are some processes to analyze the different between the image before and after the disaster. Water mask using band 4 of the optical image of AVNIR-2 before the disaster was then used for water mask processing. The band 4 of the AVNIR-2 optical image is near-infrared band which clearly shows parts of water in the area. The binarization and median filter processing are conducted before applied a DEM mask to the image. Binary image from the image after water mask processing is already showed the segment of water and another area. In order to highlight the extraction target of edge, median filter of the 3x3 filter window is applied to the image. The DEM mask is generated from the ASTER GDEM image with the resolution of 30m. The last process of the analysis processing is the removal of very small region which does not necessary in the image. Then the post-processing of the PALSAR image is area calculation. From the statistics calculation, the area of inundation is 8.72 Km2.

Comparing those images, the extraction result of ALOS/AVNIR-2 and ALOS/PALSAR showed same area of the inundation, such as areas along the coast, area near the airport and some parts around river. The result of the area also gave a good agreement. Compare to the referenced inundation areas in Chile, those images showed a corresponding result in extracting the tsunami damage areas due to the 2010 Chilean earthquake.

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Future study is needed in order to make sure the processes of the extraction areas, such as examine the difference between satellite remote sensing result and in situ observation, try to analyze other events which we can get satellite images just after the event, make a preparation for the use of ALOS-2/ PALSAR-2 and other optical image with high space resolution, and extract a higher resolution of DEM data to get better image result in the processing of SAR image.

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TABLE OF CONTENTS

Page INSIDE COVER ................................................................................................ i PREREQUISITES DEGREE ............................................................................. ii AGREEMENT SHEET ..................................................................................... iii APPROVED BY COMMITTEES ..................................................................... iv THE DECREE OF EXAMINER COMMITTEE .............................................. v STATEMENT FREE FROM PLAGIARISM ................................................... vi ACKNOWLEDGEMENT ................................................................................. vii ABSTRAK ......................................................................................................... viiii ABSTRACT ....................................................................................................... ix SUMMARY ....................................................................................................... x TABLE OF CONTENTS ................................................................................... xiii LIST OF TABLE ............................................................................................... xv LIST OF FIGURE .............................................................................................. xvi LIST OF ABBREVIATIONS ............................................................................ xviii CHAPTER I INTRODUCTION ........................................................................ 1

1.1 Background ..................................................................................... 1 1.2 Problem Formula ............................................................................ 3 1.3 Research Objectives ....................................................................... 3 1.4 Research Benefit ............................................................................. 4

CHAPTER II LITERATURE REVIEW ........................................................... 5

2.1 Remote Sensing .............................................................................. 5 2.1.1 Definition and Methods of Remote Sensing ........................ 5 2.1.2 Platform ................................................................................ 7 2.1.3 Passive and Active Sensors System ..................................... 8

2.2 Optical Remote Sensing ................................................................. 9 2.2.1 Solar Irradiation ................................................................... 10 2.2.2 Spectral Reflectance Signature ............................................ 11 2.2.3 Interpreting Optical Remote Sensing Images ...................... 12

2.3 Synthetic Aperture Radar (SAR) Remote Sensing ......................... 13 2.3.1 SAR Principle ...................................................................... 14 2.3.2 Microwave Frequency ......................................................... 15 2.3.3 Polarization Wave ................................................................ 16 2.3.4 Incident Angles .................................................................... 17 2.3.5 SAR Signal Processing and Image Formation ..................... 18 2.3.6 Geometry Speckle Characteristics of SAR .......................... 19 2.3.7 Backscattered Radar Intensity .............................................. 20 2.3.8 Interpreting SAR Images ..................................................... 21

2.4 Image Processing and Analysis ...................................................... 21 2.5 Advanced Land Observing Satellite (ALOS) Imagery .................. 25

2.5.1 AVNIR-2 .............................................................................. 26

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2.5.2 PALSAR .............................................................................. 27 2.6 Tsunami .......................................................................................... 29

2.6.1 Definition and Characteristics of Tsunami .......................... 30 2.6.2 The 2010 Chile Tsunami Earthquake................................... 31

2.7 The Use Remote Sensing Technology for Tsunami Disaster Analysis ............................................................................ 33

CHAPTER III RESEARCH METHOD ............................................................ 35

3.1 Framework of Research .................................................................. 35 3.2 Research Scheme ............................................................................ 36 3.3 Research Area ................................................................................. 39 3.4 Data Source .................................................................................... 40 3.5 Instrument of Research ................................................................... 41 3.6 Data Analysis .................................................................................. 41

3.6.1 Damaged Areas Analysis of ALOS/AVNIR-2 Images........ 41 3.6.2 Damaged Area Analysis of ALOS/PALSAR Images .......... 42

CHAPTER IV RESULT .................................................................................... 52

3.1 Extraction of Tsunami Disaster Domain Using ALOS/AVNIR-2 Images ................................................................ 52 4.1.1 True and False Color Visualization ..................................... 53 4.1.2 NDVI Calculation ................................................................ 55 4.1.3 Boundary Value Determination, Division Processing and Classification ................................................................. 57 4.1.4 Small Area Removal ............................................................ 61 4.1.5 Calculation of the Tsunami Inundation ................................ 62

4.2 Extraction of Tsunami Disaster Domain Using ALOS/PALSAR Images ................................................................. 63 4.2.1 Pre-processing ...................................................................... 64 4.2.2 Analysis Processing ............................................................. 68 4.2.3 Post-Processing .................................................................... 73

CHAPTER V DISCUSSION ............................................................................. 75

5.1 Tsunami Inundation in Chile .......................................................... 75 5.2 The Extraction of Tsunami Damaged Areas .................................. 80

5.2.1 Tsunami Damaged Areas Extraction Using Optical Images of ALOS/AVNIR-2 ................................................. 81 5.2.2 Tsunami Damaged Areas Extraction Using SAR Images of ALOS/PALSAR .................................................. 83

5.3 Comparison of Image Extraction Results ....................................... 86 CHAPTER VI CONCLUSION ......................................................................... 88

6.1 Conclusion ...................................................................................... 88 6.2 Suggestion ...................................................................................... 89

REFERENCES .................................................................................................. 90

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LIST OF TABLE

Page Table 2.1 Types of Information in Optical Image ........................................... 12 Table 2.2 Characteristics and Specifications of the AVNIR-2 Instruments .... 26 Table 2.3 Definitions of Processing Levels of AVNIR-2 Products ................. 27 Table 2.4 ALOS/PALSAR Characteristics ...................................................... 28 Table 3.1 Lists of ALOS Data Used in the Study ............................................ 41 Table 5.1 Water Heights and Wave Arrival Times .......................................... 76

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LIST OF FIGURE

Page Figure 2.1 Data Collection by Using Remote Sensing .................................... 6 Figure 2.2 Electromagnetic (EM) Spectrum .................................................... 9 Figure 2.3 Solar Irradiation Spectra above the Atmosphere and at Sea-Level .................................................................................... 10 Figure 2.4 Reflectance Spectrums of Five Types of Land Cover .................... 11 Figure 2.5 Geometry’s Image for a Typical Strip-Mapping SAR Imaging System .............................................................................. 14 Figure 2.6 SAR Backscattered Intensity: (a) Long Wavelength Radar and (b) Short Wavelength Radar .................................................... 15 Figure 2.7 SAR Point Target Return ................................................................ 17 Figure 2.8 SAR Image Before and After Applying Speckle Noise Removal .......................................................................................... 19 Figure 2.9 Area of the Mask Processing Method ............................................ 24 Figure 2.10 Advanced Land Observing Satellite (ALOS) ................................. 26 Figure 2.11 PALSAR Observation Characteristics ........................................... 28 Figure 2.12 A Tsunami which is Generated by Earthquakes ............................. 31 Figure 2.13 The 2010 Tsunami Earthquake Location in Chile .......................... 33 Figure 3.1 Framework of Research .................................................................. 36 Figure 3.2 Flowchart of the Method of Tsunami Affected Region Extraction Using ALOS/AVNIR-2 ................................................ 37 Figure 3.3 Flowchart of the Method of Tsunami Affected Region Extraction Using ALOS/PALSAR ................................................. 39 Figure 3.5 An Example of Median Filter Process ............................................ 46 Figure 3.6 Tsunami Inundation’s Height (Run-Up Height) ............................. 48 Figure 3.7 An Example of the Expansion Process ........................................... 49 Figure 3.8 An Example of the Contraction Process ......................................... 49 Figure 3.9 An Example of the Single Closing Process: (a) Expansion Process and (b) Contraction Process ....................... 50 Figure 3.10 An Example of the Single Opening Process: (a) Expansion Process and (b) Contraction Process ....................... 50 Figure 4.1 ALOS/AVNIR-2 True-Color Composite Images: (a) Image before the Disaster (2007/2/24) and (b) Image after the Disaster (2010/9/4) .......................................... 53 Figure 4.2 ALOS/AVNIR-2 False-Color Composite Images: (a) Image before the Disaster (2007/2/24) and (b) Image after the Disaster (2010/9/4) .......................................... 54 Figure 4.3 Computed NDVI for ALOS/AVNIR-2 Images: (a) NDVI Image before the Disaster and (b) NDVI Image after the Disaster ................................................. 56 Figure 4.4 Segmenting Image Result of the NDVI Image after the Disaster in ....................................................................................... 58

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Figure 4.5 Band 4 Gray Scale Image of the ALOS/AVNIR-2 before the Disaster ........................................................................................... 59 Figure 4.6 Segmenting Image Result of the Image before Disaster ................ 59 Figure 4.7 Classification Image Results: (a) Classification Image Result before the Disaster and (b) Classification Image Result after the Disaster ............................................................................. 60 Figure 4.8 Image Results of the Small Area Removal Processing:

(a) Image Result before the Disaster and (b) Image Result after the Disaster ............................................................................. 61

Figure 4.9 Class Statistics Results ................................................................... 62 Figure 4.10 Area Calculation Image .................................................................. 63 Figure 4.11 ALOS/PALSAR Images: (a) Image before the Disaster (2009/3/11) and (b) Image after the Disaster (2010/3/14) .............. 64 Figure 4.12 Image Results of the Registration and Resize Processing .............. 65 Figure 4.13 Image Results of the Speckle Noise Removal Processing:

(a) Image Result before the Disaster and (b) Image Result after the Disaster ............................................................................. 66

Figure 4.14 Backscattered Image Results: (a) Image Results before the Disaster and (b) Image Results after the Disaster .......................... 67 Figure 4.15 The Absolute Difference’s Image of Images before and after the Disaster ..................................................................................... 68 Figure 4.16 Water Mask Using the AVNIR-2 Band 4 Grayscale Image before the Disaster .......................................................................... 69 Figure 4.17 Image Result after Water Mask Processing .................................... 69 Figure 4.18 Image Statistics before and after the Median Filter Processing ..... 70 Figure 4.19 The Binary Image Result of Water and Another Area ................... 71 Figure 4.20 The DEM Mask Image ................................................................... 72 Figure 4.21 The Image Result after Applying DEM Mask ............................... 72 Figure 4.22 The Image Result after the Small Region Removal Processing ..... 73 Figure 4.23 Image Statistics Calculation ........................................................... 73 Figure 5.1 Talcahuano Harbor after the Earthquake and Tsunami .................. 77 Figure 5.2 Damage Building Caused by the 2010 Chilean Earthquake .......... 78 Figure 5.3 The Damage Map of Concepcion and Talcahuano ........................ 79 Figure 5.4 The Inundation Map in Talcahuano ............................................... 80 Figure 5.5 The ALOS/AVNIR-2 Image Result of Tsunami Damaged Areas ............................................................................................... 80 Figure 5.6 Tsunami Damaged Areas Observed from QuickBird Image after the Disaster ............................................................................. 83 Figure 5.7 The ALOS/PALSAR Image Result of Tsunami Damaged Areas ............................................................................................... 84 Figure 5.8 Figure 5.8 Tsunami Damage Areas Image Extraction: (a) Damage Areas of the ALOS/AVNIR-2 Image and (b) Damage Areas of the ALOS/PALSAR Image .......................... 87

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LIST OF ABBREVIATIONS ALOS : Advanced Land Observing Satellite ASTER : Advanced Spaceborne Thermal Emission Reflectance Radiometer AVNIR-2 : Advanced Visible and Near Infrared Radiometer-Type 2 CCPO : Center for Coastal Physical Oceanography CF : Calibration Factor dB : Decibel DEM : Digital Elevation Model DN : Digital Number EM : Electromagnetic EMR : Emission of Electromagnetic Radiation GCP : Ground Control Point GIS : Geographic Information System H : Horizontal HH : Horizontal-Horizontal HV : Horizontal-Vertical IR : Infrared ITST : International Tsunami Survey Teams ITIC : International Tsunami Information Center JAROS : Japan Resources Observation Systems Organization JAXA : Japan Aerospace Exploration Agency Km : Kilometer Lidar : Light Detection and Ranging m : Meter Mw : Moment Magnitude NDVI : Normalized Difference Vegetation Index NIR : Near Infrared NGDC : National Geophysical Data Center PALSAR : Phased Array type L-band Synthetic Aperture Radar PRISM : Panchromatic Remote-sensing Instrument for Stereo Mapping ROI : Region of Interest S : South SAR : Synthetic Aperture Radar USGS : United States Geological Survey V : Vertical VH : Vertical-Horizontal VHR : Very High Resolution VV : Vertical-Vertical W : West