SEA SURFACE TEMPERATURE VARIABILITY IN THE SOUTHERN PART OF JAVA ISLAND AND THE LESSER SUNDA CORRESPONDING TO THE INDIAN OCEAN DIPOLE MODE (IODM).

12th Biennial Conference of
Pan Ocean Remote Sensing Conference
(PORSEC)
2014

"Ocean Remote Sensing for
Sustainable Resources"
04 – 07 November 2014, Bali-Indonesia

ISBN 978-602-72335-0-8

12th Biennial Conference of
Pan Ocean Remote Sensing Conference (PORSEC)
2014

"Ocean Remote Sensing for
Sustainable Resources"

04 – 07 November 2014, Bali-Indonesia
Scientific Committee:
Prof. Dr. Dan Ling Tang

Prof. Dr. Bonar P. Pasaribu
Prof. Dr. Made Sudiana Mahendra
Dr. Orbita Roswintiarti
Dr. Kristina Katsaros
Dr. Antony Liu
Dr. Masahisa Kubota

Editors:
Prof. Dr. Tasuku Tanaka
Dr. Gad Levy
Dr. James Gower
Dr. Ir. I Wayan Nuarsa
Dr. Wikanti Asriningrum
Ir. Wawan K. Harsanugraha, M.Si

YAMAGUCHI Univ. – Japan
NWRA – USA
DFO – Canada
UDAYANA Univ. – Indonesia
LAPAN – Indonesia

LAPAN – Indonesia

ISBN 978-602-72335-0-8
JAKARTA, March 2015

ii

12th Biennial Conference of
Pan Ocean Remote Sensing Conference (PORSEC)
2014

"Ocean Remote Sensing for
Sustainable Resources"

04 – 07 November 2014, Bali-Indonesia

All papers in this book have been selected by the scientific committee.
All rights reserved. No part of this book may be reproduced, downloaded,
disseminated, published, or transferred in any form or by any means, except
with the prior written permission of, and with express attribution to the

author.
The publisher makes no representation, express or implied, with regard to the
accuracy of the information contained in this book and cannot any legal
responsibility or liability for any errors that may be made.

ISBN 978-602-72335-0-8
JAKARTA, March 2015

iii

Preface
Since its establishment in 1990, the Pan Ocean Remote Sensing Conference
(PORSEC) has rapidly gained global status as one of the most prestigious
Remote Sensing Conference in the world, with a scope covering all world
oceans. PORSEC is an organization dedicated to helping developing nations
stimulate their science programs with focus on the applications of remote
sensing technology in Ocean Sciences. PORSEC has provided over a decade of
effort with scientists from over thirty countries participating in conferences
once every two years.
The Indonesian National University of Udayana, together with National

Institute of Aeronautics and Space (LAPAN), are privileged to host PORSEC
4, the Twelfth Bie ial Co fere e with the the e O ea Re ote “e si g
for “ustai a le Resour es i De pasar – Bali, Indonesia during November 4th7th, 2014.
The conference reviewed and discussed the state of ocean remote sensing and
will help scientists and students involved in ocean-atmosphere studies using
remote sensing techniques to benefit from interactions with the experts
participating from all over the globe. The conference also provide an
opportunity to showcase the research work carried out using remote sensing
techniques from various satellite missions and the applications of ocean
remote sensing for societal benefits.
The successful completion of the PORSEC 2014 Proceedings is the result of the
cooperation, confidence, and endurance of many people. All contributions are
greatly appreciated. It is impossible to overestimate the importance of their
efforts in helping us meet deadlines, their insights in editing, and their donation
of time.

Jakarta, March 2015
Editors

iv

Local Organizing Committee
PORSEC 2014
Steering:
Orbita Roswintiarti
National Institute of Aeronautics
and Space (LAPAN)

A.A. Raka Sudewi
Udayana University, Indonesia

I Made Suastra
Udayana University, Indonesia
Responsible Person:
Rokhis Khomarudin
National Institute of Aeronautics
and Space (LAPAN)

Made Budiarsa
Udayana University, Indonesia

Chair Person:
Made Sudiana Mahendra
Udayana University, Indonesia

Syarif Budhiman
National Institute of Aeronautics
and Space (LAPAN)

Co-Chair Person:
Maryani Hartuti
National Institute of Aeronautics
and Space (LAPAN)
Takahiro Osawa
Udayana University, Indonesia

Budiarsa Suyasa
Udayana University, Indonesia
Hamidah Yunus
Udayana University, Indonesia

Members:
Winanto
National Institute of Aeronautics
and Space (LAPAN)

Noer Syamsu
National Institute of Aeronautics
and Space (LAPAN)

Ketut Budiartawan
Udayana University, Indonesia

Gathot Winarso
National Institute of Aeronautics
and Space (LAPAN)
v

I Wayan Gede Astawa Karang
Udayana University, Indonesia

Nyoman Arto Suprapto
Udayana University, Indonesia
Teguh Prayogo
National Institute of Aeronautics
and Space (LAPAN)
Hanggar Prasetyo Kadarisman
Udayana University, Indonesia
Ety Parwati
National Institute of Aeronautics
and Space (LAPAN)

Anang Dwi Purwanto
National Institute of Aeronautics
and Space (LAPAN)
Ahcmad Supriyono
National Institute of Aeronautics
and Space (LAPAN)
I Made Sukawijaya
Udayana University, Indonesia
Komang Arya Purwanto

Udayana University, Indonesia
I Wayan Budiada
Udayana University, Indonesia

Rossi Hamzah
National Institute of Aeronautics
and Space (LAPAN)

Yennie Marini
National Institute of Aeronautics
and Space (LAPAN)

I Gede Nyoman Konsumajaya
Udayana University, Indonesia

Anneke K.S. Manoppo
National Institute of Aeronautics
and Space (LAPAN)

Abd.Rahman As-Syakur

Udayana University, Indonesia
I Ketut Budiartawan
Udayana University, Indonesia
Kuncoro Teguh Setiawan
National Institute of Aeronautics
and Space (LAPAN)
Ketut Sukadana
Udayana University, Indonesia

vi

Paper and Proceeding
Coordinator:
Wawan K. Harsanugraha
National Institute of Aeronautics and Space (LAPAN)
Members:
I Wayan Nuarsa
Udayana University, Indonesia
Wikanti Asriningrum
National Institute of Aeronautics

and Space (LAPAN)
Sartono Marpaung
National Institute of Aeronautics
and Space (LAPAN)
Emiyati
National Institute of Aeronautics
and Space (LAPAN)
Kuncoro Teguh Setiawan
National Institute of Aeronautics
and Space (LAPAN)
Yennie Marini
National Institute of Aeronautics
and Space (LAPAN)

Nanin Anggraini
National Institute of Aeronautics
and Space (LAPAN)
Syifa Wismayati Adawiah
National Institute of Aeronautics
and Space (LAPAN)
Hamdi Eko Putranto
National Institute of Aeronautics
and Space (LAPAN)
Udhi Catur Nugroho
National Institute of Aeronautics
and Space (LAPAN)
I Made Karsika
Udayana University, Indonesia
Putu Ari Ardiswana
Udayana University, Indonesia

Anneke K.S. Manoppo
National Institute of Aeronautics
and Space (LAPAN)

vii

Paper and Proceeding
Coordinator:
Wawan K. Harsanugraha
National Institute of Aeronautics and Space (LAPAN)
Members:
I Wayan Nuarsa
Udayana University, Indonesia
Wikanti Asriningrum
National Institute of Aeronautics
and Space (LAPAN)
Sartono Marpaung
National Institute of Aeronautics
and Space (LAPAN)
Emiyati
National Institute of Aeronautics
and Space (LAPAN)
Kuncoro Teguh Setiawan
National Institute of Aeronautics
and Space (LAPAN)
Yennie Marini
National Institute of Aeronautics
and Space (LAPAN)

Nanin Anggraini
National Institute of Aeronautics
and Space (LAPAN)
Syifa Wismayati Adawiah
National Institute of Aeronautics
and Space (LAPAN)
Hamdi Eko Putranto
National Institute of Aeronautics
and Space (LAPAN)
Udhi Catur Nugroho
National Institute of Aeronautics
and Space (LAPAN)
I Made Karsika
Udayana University, Indonesia
Putu Ari Ardiswana
Udayana University, Indonesia

Anneke K.S. Manoppo
National Institute of Aeronautics
and Space (LAPAN)

vii

CONTENTS
A. ORAL PRESENTATIONS
1 Habitat Model Development of Pacific Saury (Cololabis Saira) Using Satellite Remotely
Sensed Data in the Northwestern North Pacific

1-12

Achmad Fachruddin Syah, Sei-Ichi Saitoh, Irene Alabia, and Toru Hirawake

2 Cost-Effective Approach to Estimate Unreported Data: Rebuilding History of Lift-Net Fishing
in Kwandang Waters

13-20

Andhika Prima Prasetyo, Duto Nugroho, Lilis Sadiyah, and Rudy Masuswo Purwoko

3 The Use of Image Rotations on Multispectral-Based Benthic Habitats Mapping

21-30

Pramaditya Wicaksono

4 The Utilization of Landsat-8 for Mapping the Surface Waters Temperature of Grupuk Bay West Nusa Tenggara: with Implications for Seaweeds Cultivation

31-40

Bidawi Hasyim, Syarif Budiman, Arlina Ratnasari, Emiyati, and Anneke Manoppo

5 Multispectral Satellite Data for Mapping of Coral Reef Death Due to El Niño Southern
Oscillation (ENSO) in Western Sumatra

41-46

Munawaroh and Nurul Ihsan Fawzi

6 Spatial-Temporal Variability of Satellite-Derived Phytoplankton Size Classes in the South
China Sea

47-58

Hai Jun YE, Dan Ling TANG, and R.P.P.K. Jayasinghe

7 Morphological Characteristics of Antarctic Coast Based on the Laser Altimetry

59-62

Jieun Kim and Jaehyung Yu

8 Investigation of Coastal Sediment Spectrums Behavior Based on Moisture Content and
Mineralogy; a Case Study of South Korea

63-66

Haein Shin and Jaehyung Yu

9 40 Year Record of Antarctic Coastal Change from 1960s to 2000s Based on the Remote
Sensing Monitoring

67-70

Jaehyung Yu and Yongshik Jeon

10 Performance Multimodel Climate-Sytem Historical Forecast Project (CHFP) in
Characterize Feature and Impact of El Nino Modoki

71-78

Ida Bagus Mandhara Brasika and Nurjanna Joko Trilaksono

11 Shallow Sounding Bathymetric Using Multibeam Echosounder and Topographic Laser
Scanner

79-86

Nursugi, Tri Patmasari, dan Khafid

12 Impacts of Human Activities on the Evolution of Estuarine Wetland in the Yangtze Delta from
2000 to 2010

87-102

Lei Zhang Bingfang Wu Kai Yin ·Xiaosong Li· Kun Kia· Liang Zhu

13 New Land Accretion from 2000-2003 at Segara Anakan Lagoon, Southcoast of West and
Central Java

103-114

I Wayan Lugra, Deny Setyady, I.N. Astawa, G.M. Hermansyah, and P.H. Wijaya

14 Spatial Dynamics and Distribution of Live Coral, in Outer Zone, Spermonde Archipelago,
Indonesia

115-126

Nurjannah Nurdin, Khaerul Amri, Abd. Rasyid Djalil, Ilham Jaya, Agus, and M. Akbar
A.S.

15 The European Atlas of the Seas: Combining Conventional and Satellite Data for

127-136
viii

ApplicationsIn Fisheries and Aquaculture Management
Vittorio Barale, Jean Dusart, Michael Assouline, and Alberto Lorenzo-Alonso

16 Influence of the Asia Monsoon on the Red Sea Basic Ecosystem Dynamics

137-150

Vittorio Barale and Martin Gade

17 Three Dimensional Reconstruction of Rain Rates from X – SAR Measurements Using
Tomography

151-162

Marco Moscatelli and Gad Levy

18 Application of Multibeam Data for Characterizing Seabed Geology at Morotai Strait

163-170

Taufan Wiguna and Muhammad Irfan

19 Wave Characteristics of Indonesian Waters for Sea Transport Safety and Planning

171-186

Mia Khusnul Khotimah and Roni Kurniawan

20 Remote Sensing Applied to the Analysis of Spatial and Temporal Patterns of Dengue
Incidence Based on Ecological and Socio-Economic and Demographic Factors in Sri Lanka

187-194

Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam
Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, and Sinnathamby Noble
Surendran

21 Bigeye Tuna (Thunnus Obesus) Hotspots in the Eastern Indian Ocean Off Java

195-200

Mega Syamsuddin, Sei-Ichi Saitoh, and Toru Hirawake

22

Comparison of Sun Glint Correction Methods for Casi-1500 Data in Shallow Waters

201-208

Joo-Young Jeon, Sun-Hwa Kim, Chan-Su Yang, and Kazuo Ouchi

23 The Study on the Development of Satellite Data Processing System

209-216

Chen Yuanwei

24 Comparative Study of Phytoplankton Bloom in Indonesian Waters Using Aqua-Modis
Satellite Data
Rion S. Salman dan Ayufitriya

217-224

)

25 Spaceborne SAR Imaging of Coastal Ocean Phenomena in the China Seas

225-228

Xiaofeng Li and Feng Sha

26 Monthly Sea Surface Salinity Variation in Aru and Arafura Sea By Using Aquarius Satellite
Image Data

229-234

Yuwana Setiabudi Sriraharjo and Susanna Nurdjaman

27 Business Process Analysis for High Resolution Remote Sensing Data Acquisition and
Distribution

235-240

Andie Setiyoko and Rubini Jusuf

28 Using Satellite Remote Sensing and Catch Data to Characterize Potential Fishing Zones for
Skipjack Tuna in Bone Bay-Flores Sea During Northwest Monsoon

241-250

Mukti Zainuddin, Safruddin, M. Banda Selamat, Adam Malik, and Sei-Ichi Saitoh

29 Analysis of Total Suspended Solid Using Landsat 8 Imagery (Study of Case: Sampit Bay,
Indonesia)

251-256

Anang Dwi Purwanto and Syarif Budhiman

30 Monitoring Volcanic Activity of the Nishinoshima Island from Spaceborne SAR

257-260

Tadashi Sasagawa

31 Modeling Sensor Proton Magnetometer in Small Satellite

261-266

Sofian Rizal

32 Variability of Chlorophyll-a Distribution and Its Relation to the Wind Patterns in Lombok
Waters

267-272

Anneke K.S. Manoppo, Muhammad Riandy, Emiyati, Bidawi Hasyim, and Syarif
Budhiman

ix

33 An Evaluation of Theuse of SRTM Data to the Accuracy of Local Geoid Determination: A
Case Study of Yogyakarta Region, Indonesia

273-280

Bagas Triarahmadhana and Leni S. Heliani

34 Ocean Front Application on Fishing Ground Identification in the Sourthern Taiwan Strait

281-286

Yi Chang, Ming-An Lee, Tzu-Huang Chang, and Cheng-Hsin Liao

35 The Effect of Different DEM Accuracyon the Orthoimage Generation

287-292

Jali Octariady, Djurdjani, and Heri Sutanta

36 Blue Carbon Stock of Mangrove Ecosystem in Nusa Penida, Bali

293-300

Mariska A. Kusumaningtyas, August Daulat, Devi D. Suryono, Restu Nur Afi Ati, Terry
L., Kepel, Agustin Rustam, Yusmiana P. Rahayu, Peter Mangindaan, Nasir Sudirman,
and Andreas A. Hutahaean

37 Distribution and Sources of Oil Slicks in the Middle Adriatic Sea

301-308

Mira Morović, Andrei Ivanov, Marinko Oluić, Žarko Kovač, and Nadezhda Terleeva

38 New Mangrove Index as Degradation/Health Indicator Using Remote Sensing Data: Segara
Anakan and Alas Purwo Case Study

309-316

Gathot Winarso, Anang D. Purwanto, and Doddy M. Yuwono

39 The Improvement of the Sustainable Aquaculture Model for Kelp and Scallop in Southern
Hokkaido, Japan Using Satellite Remote Sensing, GIS and OGCM

317-322

Yang Liu, Sei-Ichi Saitoh, I. Nyoman Radiarta, and Toru Hirawake

40 Satellite Detection of Giant Colonies of PhaeocystisGlobosa in Coastal Waters off Viet Nam

323-328

Montes-Hugo M.A., Doan-Nhu H., and Nguyen-Ngoc L.

41 MCS Detection Using Lightning Recording and Satellite Imagery

329-336

I Putu Dedy Pratama, Pande Komang Gede Arta Negara, Pande Made, and Rony
Kurniawan
C

42 Analysis of Cloud Removal Method on Sea Area Using Landsat-8 Multi-Temporal

337-340

Danang Surya and Candra Yudi Prabowo

43 Accuracy Estimation and Validation of Offshore Wind Speed by Using Terra SAR-X

341-344

RyotaroAbo, Katsutoshi Kozai, Teruo Ohsawa, and Koji Kawaguchi

44 Suomi National Polar-Orbiting Partnership Satellite Data Processing System to Produce Sea
Surface Temperature

345-354

Budhi Gustiandi and Andy Indradjad

45 Bio-Physical Coupling in the Bay of Bengal – A Remote Sensing Perspective

355-362

Benny N. Peter, Mridula K.R., Mazlan Hashim, and Nadzri Reba

46 Analysis of Monthly Mean Surface Currents for Bali Waters Using OSCAR

363-372

Subekti Mujiasih and A. Rita Tisiana Dwi Kuswardani

47 Sea Surface Chlorophyll Fronts in the Taiwan Strait

372-376

Yi-Sin Fang, Tzu-Huang Chang, and Yi Chang

48

Shoreline Change Analysis of Gulf of Cambay Using GIS

377-380

Vivek Gouda and Robinu Rose Mathew

49 Seasonal and Inter-Annual Variability of the Coccolithophore Blooms in the Barents and the
Black Seas from Satellite Data

381-390

Oleg Kopelevich, Sergey Sheberstov, Vladimir Burenkov, and Svetlana Vazyulya

50 Observed the Indian Ocean Dipole 2011 from Satellite and In-Situ In West Java Sea Waters

391-394

Jonson Lumban-Gaol, Bonar P. Pasaribu, Djisman Manurung, Risti Endriani Arhatin,
Sripujiati, and Marisa Meiling

51 Satellite Altimetry and Hydrologic Modeling of Poorly-Gauged Tropical Watershed

395-404

Y. Budi Sulistioadi, Kuo-Hsin Tseng, C.K. Shum, Michael F. Jasinski, and Hidayat

x

52 Harmful Algal Bloom Phenomenon in Lampung Bay Base on Red Tide Analysis Using
SPOT-4 Image

405-408

Emiyati, Ety Parwati, and Syarif Budhiman

53 Acoustic Emission and Laser Breakdown of Water with Different Salinity

409-414

Alexey V. Bulanov

54 Squid Habitat Hotspots in Pelagic Waters of Western and Central North Pacific: Roles of
Eddies and Sub-Surface Features

415-420

Sei-Ichi Saitoh, Irene Alabia, Robinson Mugo, Hiromichi Igarashi, Yoichi Ishikawa,
Norihisa Usui, Masafumi Kamachi, Toshiyuki Awaji, and Masaki Seito

55 Extraction Method Development in Land and Ocean Salinity

421-428

Wiweka

56 Indonesian Multi-Scale Grid System for Environmental and Oceanic Data
Akhmad Riqqi and Ivonne M. Radjawan

429-434

57 Mapping of Total Suspended Matter Using Landsat 8 in Coastal Areas of Lombok Island

435-438

Emiyati, Anneke K.S. Manoppo, and Syarif Budhiman

58 Trend Analysis of Mean Sea Level at South China Sea Using Mann-Kendall Method

439-446

Moehammad Ediyan Raza Karmel

59 Visualization System of Monthly Average Sea Surface Temperature Modis Using KML in
Google Earth

447-452

Andy Indradjad and Yennie Marini

60 On the Use of Satellite-Measured Chlorophyll Fluorescence for Monitoring Coastal and
Ocean Waters

453-460

Jim Gower

61 Global Sea Level Rise: the Case for a Dam onCthe Strait of Gibraltar

461-468

Jim Gower

62 Compatibility Test of Windsat Data over Indonesian Monsoon Path

469-476

I Ketut Swardika

63 Extraction Model of Dissolved Oxygen Concentration Using Landsat Remote Sensing
Satelite Data. Case Study: Ringgung Coastal Waters

477-488

Muchlisin Arief

64 Oceanographic Characteristics Studies in North of Papua Waters Between 2010 to 2012
Using Modis Imagery

489-496

Amalia Hadiyanti and Retnadi Heru Jatmiko

65 Spatial Distribution and Interaction of Phytoplankton, Zooplankton and Fish Biomass at the
North of Papua

497-504

A. Hartoko and Subiyanto

66 Temporal and Spatial Changes of the Coastline and Coastal Wetlands in the Red River
Estuary, Vietnam from 1986 to 2013

505-514

Nguyen Tien Cong, Ngo DucAnh, and Nguyen Thi Thu Thuy

67 Development of Ocean Wave Spectrum Estimation from HF Radar

515-520

Yukiharu Hisaki Syah

68 A Numerical Simulation of Wave and Sediment Transport in the Balikpapan Bay, East
Kalimantan, Indonseia

521-526

Idris Mandang, Ashadi A. Nur, and Arya M. Fitroh

69 Numerical Simulations in Coastal Hydraulics and Sediment Transport: Application to
Mahakam Estuary, East Kalimantan, Indonesia

527-532

Ansorullah Jamal, Idris Mandang, and Pariwate Varnakovida

xi

70 The Effect of Different Atmospheric Correction on Bathymetry Extraction Using Landsat
Satellite Imagery

533-538

Kuncoro Teguh Setiawan, Yennie Marini, Achmad Supriyono, and Syarif Budhiman

71 Spatial Data Analysis and Remote Sensing for Observing Tsunami-Inundated Area

539-548

Abu Bakar Sambah and Fusanori Miura

72 Development of Method for Extracting Low-Level Tropospheric Moisture Content from
Ground Based GPS Derived Precipitable Water Vapor (PWV)

549-558

Aries Kristianto, Tri Wahyu Hadi, and Dudy Darmawan Wijaya

73 VIIRS Detection of Lit Fishing Boats

559-562

Christopher D. Elvidge, Mikhail Zhizhin, Kimberly Baugh, and Feng-Chi Hsu

74 The Assessment of Mangrove Ecosystem for Capture Fisheries Product

563-568

Dewayany Sutrisno, Yatin Suwarno, and Irmadi Nahib

75 Utilization of Satellite Remote Sensing Data for the Determination of Potential Fishing Areas
and Its Validation in the Strait of Bali

569-574

Nyoman Dati Pertami and Komang Iwan Suniada

76 Spatial Distribution Analysis of Albacore Tuna (Thunnus Alalunga) Using Argo Float SubSurface Temperature Related to Indian Ocean Dipole (IOD) Impact in South Java Indian
Ocean

575-582

Bambang Sukresno, Agus Hartoko, Budi Sulistyo, and Subiyanto

77 Sea Surface Temperature Measurement from TMI and Modis Data

583-588

Yennie Marini, Gathot Winarso, and Anneke K.S. Manoppo

78 Prediction of Coral Reef Damage Using Cellular Automata-Markov

589-596

Agus Aris, Nurjannah Nurdin, Vincentius P. Siregar, and Ibnu Sofian

79 Estimation of Sea Surface Temperature Distribution in Ekas Bay Using Landsat-8 Satellite
Imagery

597-604

Muhammad Ramdhan

80 Coastal Characteristics of Indonesia and Its Relation to the Tsunami Hazard

605-614

M. Priyatna, M. Rokhis Khomarudin, and Dini Ambarwati

81 Evaluation of Multitemporal Landsat Satellite Images to Identify Total Suspended Solid
(TSS) Alteration in Saguling Reservoir, West Bandung, Indonesia

615-622

Anjar Dimara Sakti, Soni Darmawan, and Ketut Wikantika

82 Sea Surface Temperature Variability in the Southern Part of Java Island and the Lesser
Sunda: Corresponding to the Indian Ocean Dipole Mode (IODM)

623-630

I Gede Hendrawan, I Wayan Gede Astawa Karang, I Made Kertayasa, and I G.A. Diah
Valentina Lestari

83 Laboratory Study of Cross-Polarized Radar Return at Gale-force Winds

631-636

Yu. Troitskaya, V. Abramov, A. Ermoshkin, E. Zuikova, V. Kazakov, D. Sergeev, and A.
Kandaurov

84

Satellite Observation of Large-Scale Coastal Change: A Case Study from Cigu Lagoon,
Taiwan

637-642

Tzu-Huang Chang, Yi Chang, Laurence Zsu-Hsin Chuang, and Ming-An Lee

85

Sea Surface Temperature and Sea Surface Chlorophyll in Relation to Bigeye Tuna
Fishery in the Southern Waters Off Java and Bali

643-654

Martiwi Diah Setiawati and Fusanori Miura

86 Mode 2 Internal Solitary Waves: Measurements of Surface Currents from Laboratory
Experiments and Numerical Simulations, and the Results of a SAR Simulator

655-662

Donald P. Delisi, Jinsong Chong, Xiangzhen Yu, Thomas S. Lund, and David Y. Lai

xii

87 The Climate Change Impact on Coralin Weh Island and Aceh Island Indonesia

663-670

A. Besse Rimba, Joseph Maina, and Fusanori Miura

88 Investigating the Effect of Rainstorm on Coastal Coral Reef Water -- A Case Study in Xuwen
Coral Reef Coast Region, South China

671-682

Weiqi Chen, Xuelian Meng, Shuisen Chen, Liusheng Han, and Siyu Huang

89 Satellite Remote Sensing in Fishery Forecast in India: Past, Present, and Challenges

683-690

Aishwarya Narain

90 Identifying of Change of Mangrove Forest and Mining Areas at the Coastal of Karimun Besar
Island

691-696

Tatik Kartika and Silvia Anwar

91 Basin Configuration Identification by Airborne Gravity in WesternTanjung, South Borneo

697-704

Ermin Retnowati, Dyah Pangastuti, Boko Nurdiyanto S., Arisauna M. Pahlevi, Gonata
Pranajaya and Thomas Cafreza Atarita

92 A DASH7 Based Monitoring System for Mariculture Environment

705-712

Yuvin Ha, Sang-Hwa Chung, Yun-Sung Lee, Ik Joo Jeong, Sung-Jun Lee, Jung-hoon Cha,
and Hyong-ki Yoon

93 Assessment and Mapping of Coastal Vulnerability to Sea Level Rise (Case Study at
Semarang Coastal Area, Central Java)

713-722

Husnayaen, Takahiro Osawa, and Ida Ayu Astarini

94 Detecting the Affected Areas of Mount Sinabung Eruption Using Landsat-8 Based on
Reflectance Change

723-734

Suwarsono, Hidayat, Jalu Tejo Nugroho, Wiweka, Parwati, and M. Rokhis Khomarudin

95 Detection of Seabed in Seribu Islands Seawaters

735-738

Sri Pujiyati, Kaisar Akhir, and Risti E. Arhatin

96 The Creation of Forest Base Probability ImageC in Coastal Area of East Kalimantan Indonesia
Using Canonical Variate Analysis

739-744

Ita Carolita and Tatik Kartika

97 Satellite Data for Water Clarity Mapping in Indonesia Lake Water

745-752

Bambang Trisakti, Nana Suwargana and I Made Parsa

98 Study on Seasonal Variability in Internal Wave Signatures in the Lombok Strait Area
Using SAR and Optical Sensor

753-766

I Wayan Gede Astawa Karang, Takahiro Osawa, Leonid Mitnik, and I Made Satria
Wibawa

B. POSTER PRESENTATIONS
01 Bathymetric Mapping of Shallow Water Surrounding Dongsha Island Using Quickbird Image

769-774

Li Dongling, Zhang Huaguo, and Lou Xiulin

02 Impacts of Typhoons on Hypoxia Off the Changjiang (Yangtze River) Estuary: Estimations
from Satellite Data

775-782

Jianyu Chen, Zhihua Mao, Fang Gong, and Kui Wang

03 Investigation of Whitening Event Using Hyperspectral Data in the Coastal Region of Jeju
Island, South Korea

783-788

Sun-Hwa Kim, Joo-Young Jeon, and Chan-SuYang

04 Vertical Structure in the North Pacific Subtropical Gyre Based on the Wind-Driven Circulation
Theory

789-796

Rina Tajima, KunioKutsuwada, and Kunihiro Aoki

xiii

05 Design and Construction of a Remote Sensing-Based Harmful Algal Blooms Monitoring
System

797-802

Qiankun Zhu, Bangyi Tao, Hui Lei, and Jianyu Chen

06 The Propagation and Sources Analysis of the Internal Waves in the Northwestern South
China Sea Based an Satellite Remote Sensing

803-808

Juan Wang, Jingsong Yang, Huaguo Zhang, Dongling Li, Lin Ren, and Gang Zheng

07 Acceleration Development Region Capture Fisheries Economy Oriented (A Case at Coast
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Atikah Nurhayatidan and Agus Heri Purnomo

08 Developing Fishing Grounds Prediction Model for Neon Flying Squid in the Central North
Pacific Using Satellite Remote Sensing and Vessel Monitoring System

817-820

Yang Liu, Sei-Ichi Saitoh, Hiroki Takegawa, and Toru Hirawake

09 Construction of Long-Term Data Set of Sea Surface Wind Speed/Stress Vectors by Multiple
Satellite Observations

821-828

Suguru Kameda and Kunio Kutsuwada

10 Evaluation of Offshore Wind Energy Resources by Using Scatterometer and RadiometerDerived Wind Speeds and WRF

829-832

Katsutoshi Kozai, Tsuguhiro Morita, and Teruo Ohsawa

11 Monitoring the Impact of Sea Surface Temperature Increase on Coral Bleaching in
Indonesian Waters

833-838

Rion S. Salman and Ayufitriya

12 Spectral Unmixing Applied to Meris Images of Berau Estuary Waters to Separate the Effects
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839-848

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C

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849-856

Wiwin Ambarwulan, W. Verhoef, and C. Mannaerts

14 Settlement Pattern of Bajoe Tribe in Indonesia Based on Remote Sensing Data Satellite
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857-862

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863-870

Suhana, Aninda W. Rudiastuti, and Gatot Rudiyono

16 Monitoring Changes on Mangroves Coasts Using High Resolution Satellite Images. A Case
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18 A Method of Evaluating Island Exploitation Degree Based on Multi-Scale Analysis of Remote
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881-886

Zhang Huaguo, Li Lihong, Shi Aiqin, Li Dongling, and Lou Xiulin

xiv

12th Biennial Conference of Pan Ocean Remote Sensing Conference (PORSEC 2014)
04 – 07 November 2014, Bali-Indonesia

SEA SURFACE TEMPERATURE VARIABILITY IN THE
SOUTHERN PART OF JAVA ISLAND AND THE LESSER
SUNDA: CORRESPONDING TO THE INDIAN OCEAN
DIPOLE MODE (IODM)
I Gede Hendrawan1,*), I Wayan Gede Astawa Karang1), I Made Kertayasa2),
and I G.A. Diah Valentina Lestari2)
1)

Department of Marine Sciences, Udayana University, Kampus Bukit Jimbaran,
Badung, Bali, Indonesia 80361
2)
Department of Physics, Udayana University, Kampus Bukit Jimbaran,
Badung, Bali, Indonesia 80361
*)

E-mail: hendra_mil@yahoo.com

ABSTRACT
The impact of Indian Ocean Dipole Mode (IODM) for the sea surface temperature (SST)
variability in the Southern of Java and Lesser Sunda has been investigated. The Aqua MODIS
satellite data has been used to investigating the SST distribution both spatially and temporally.
The Dipole Mode Index (DMI) was calculated from 2003 until 2011 and found that 2010 has an
indication as an IOD (Indian Ocean Dipole) year. It was coincide with the spatial change of
SST distribution in the Southern of Java and Lesser Sunda. The temporal change has been
investigating by wavelet transform, and found that the high spectrum indicated in 2010. It was
clearly found that in 2010 the SST variability in the southern part of Java Island and the Lesser
Sunda has a strong relationship with the IODM. Those relationship was confirmed through the
spatial, temporal and wavelet analysis methods.
Keywords: IODM, MODIS, SST, wavelet

1. INTRODUCTION
El-Nino Southern Oscillation (ENSO)
andthe Indian Ocean Dipole Mode (IODM)
are the largest earth climate phenomenon that
has a connection with the sea surface
temperature (SST) anomaly. Several
investigation regarding to the influence of
ENSO in the Indonesia seas has been
conducted, such as: the influence of ENSO
for the chlorophyll-a variability in the
southern of Java (Susanto and Marra, 2005),
the influence of ENSO for the upwelling in
Java and Sumatra Sea (Susanto et al., 2001),
and the influence of ENSO for the SST in the
Indonesian
Seas
(Nicholl,
1983).
Furthermore, some researches has been done
regarding to the IODM phenomenon, such
as: the dipole mode in the tropical area of the
Indian Ocean (Saji et al., 1999), the structure
of SST variability and surface wind in the

Indian Ocean during the IODM (Saji,
Yamagata, 2003), the influence of IODM for
the rainfall in Indonesia (Hermawan, 2007),
and the influence of IODM for the SST and
salinity in the Western of Sumatra
(Holliludin, 2009).
The IODM has an impact for the rainfall
variability in some countries, such as Africa
and Asia (Hu, Nita, 1996; Behera et al.,
2006; Harou et al., 2006). The SST
variability in the southern of Java and the
western of Sumatra is one of the key factors
for the IODM phenomenon, which is also
occurred simultaneously with the changing
of Indonesia season (Qu et al., 2005). The
period of IODM is more than a year
(interannual) (Saji et al., 1999 and 2003; Rao
et al., 2002) that could be influencing the
climate in Indonesia.
The SST in Indonesia Seas is the most
important point to determine the regional and
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04 – 07 November 2014, Bali-Indonesia

global climate. This is due to the complex
sea bottom topography of the Indonesian
seas, and also connecting the Pacific and the
Indian Ocean (Qu et al., 2005).From the
numerical model and the field observation
shows that a little change of SST in
Indonesia could give a high change on the
rainfall in the Indo-pacific (Miller et al.,
1992; McBride et al., 2003; Ashok et al.,
2001; Neale, Slingo, 2003). The SST
variability in Indonesia seas is also important
for the ecology point of view, since the
Indonesia Sea has a rich of the ocean
biodiversity. Therefore the investigation of
SST variability and its characteristics
become a substantial work. In this study, we
used the satellite data to make an
investigation of SST variability and its
characteristics in the southern of Java and the
lesser Sunda.
Remote sensing technology had been
widely used to observe the ocean resources.
The
Moderate
Resolution
Imaging
Spectroradiometer (MODIS) is one of the
satellite imaging that can be used easily to
make a periodic SST observation.
Furthermore, the temporal analysis of SST
data is done using wavelet transform, and
hence the period and the time of the
phenomenon can be analyzed.
1.1. Dipole Mode Index (DMI)
IODM signature are originally occurs in
the Indian Ocean. It could be due to an
increasing of SST in the western Indian
Ocean (50 W - 70 W and 10 S - 10 N), and
simultaneously decreasing of the SST in the
eastern part of Indian Ocean (90 W – 110 W
and 10 S - Equator) (Saji et al., 1999). The
IODM is recognized by determining the
Dipole Mode Index (DMI), which is the
difference of SST anomaly between the
western part and eastern part of Indian Ocean
(Saji et al., 1999). Saji, et al. (1999)
mentioned that the positive DMI (above 0.7)
is the indication of the positive IODM
phenomenon, whereas the negative of the
DMI (below -0.7) is indicating the negative
IODM phenomenon. The more positive the

IODM, the higher SST in the western Indian
Ocean will be. This makes the convection
increase around the western part of the
Indian Ocean. However, the eastern part of
Indian Ocean will experience drought
(including some areas in Indonesia). The
opposite phenomenon will occur during the
negative IODM.
1.2. Wavelet Transform
The wavelet transform is useful to analyze
time series data that contain non-stationary
power at many different frequencies
(Foufoula-Georgiou and Kumar, 1995;
Daubechies, 1990). Torrence, and Compo
(1997) proposed a Morlet Wavelet that used
as the mother wavelet (Equation 1).
Ψ

= π
η

/

eω
η

e

(1)

/
η

Where
is the non-dimensional frequency
and was taken to be 6 in this study to satisfy
the admissibility condition (Farge, 1992).
This is known as the scaled wavelet, which is
defined by:
/

=
′

Ψ

′

Ψ

(2)

Where s is the dilation parameter used to
change the scale, and n is the translational
parameters used as time shifting. The s-1/2 is
a normalization factor to maintain the total
energy of the scaled wavelet constant.
The continuous wavelet transform (CWT)
of a discrete sequence xn is a convolution of
xn with the scaled wavelet functions and
translated from Ψ 0(η) (Torrence and Compo,
1997):
=

1
′

′

′=0

Ψ

(3)

It is possible to calculate the wavelet
transform using equation (3), but it would be
simpler and easier if it done in Fourier space.
Hence, by using the convolution theorem, the
wavelet transform is the inverse of Fourier
transform of the product.
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12th Biennial Conference of Pan Ocean Remote Sensing Conference (PORSEC 2014)
04 – 07 November 2014, Bali-Indonesia

=

1

(4)
Ψ

=0

where the angular frequence is defined by:
=

>

(5)

Hence, the value of power spectum wavelet
|
| can be found from the wavelet
equation aboved.
2. Data and Method
The data used in this research is SST
derived from the Aqua MODIS satellite data.
This data can be downloaded from NASA
website (http://modis.gsfc.nasa.gov/) as a
level 3 satellite data. The eight years monthly
data from 2004 until 2011 were used for the
SST analysis.
SST Aqua MODIS satellite data in the
southern part of Java and Lesser Sunda are
averaged spatially. The average value of SST
in the western Indian Ocean and the eastern
Indian Ocean also calculated to determine
the DMI that will be used for IODM
analysis.
IODM is an interannual phenomenon
(Saji et al., 1999 and 2003, Rao et al., 2002,
etc.), while the period of SST in Indonesia is
less than one year. Therefore the monthly
SST data from Aqua MODIS is then filtered.
This should be done to remove the seasonal
changes of each variable in order to obtain a
more significant relationship between SST
and IODM.
After the seasonal effects of the SST had
been removed, the wavelet transform were
applied (Equation 1-5). The power spectrum
for each variable then used to determine the
relationship between IODM period and SST
variability in the study area.
3. RESULT AND DISCUSSION
3.1 Seasonal Characteristic ofSSTin the
Indonesia Seas
Seasonal characteristic of SST from 20032011 during rainy and dry season are shown

in the figure 1 and figure 2. The
characteristic of SST during rainy season
were determined by the averaged SST in
December-January-February (DJF) period.
While the June-July-August (JJA) data were
used to find the SST characteristic in dry
season. The SST in Indonesia during the
rainy season are shows warmer rather than
dry season. There is also a significant
difference along the southern of Java Island
until Arafuru and Banda Sea, which makes
the SST becomes colder in dry season. It
could be caused by the upwelling process
due to the monsoon (Wyrtki, 1961 and Qu,
2005). However, warmer SST during the
rainy season is caused by the downwelling
process.
2003-2004

2004-2005

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

2010-2011

Figure 1. SST Characteristics during rainy season
(December-January-February [DJF])

Beside the difference of SST condition,
the SST anomaly is occurred during the dry
seasons in 2007, 2008 and 2010 along the
southern of Java Island until Banda Sea
(Figure 1). It shows that the SST was
decreasing. However, the increasing of SST
was occurred during rainy season at 2005,
2009, and 2010 (Figure 2).
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12th Biennial Conference of Pan Ocean Remote Sens
ensing Conference (PORSEC 2014)
04 – 07 November 2014, Bali-Indonesia

2004

2005

2006

2007

nd 22006, and also end of
end of both 2003 and
he filtered SST anomaly
2011. There is also the
nificant anomaly in the
data that show a signif
could be caused by a
middle of 2010. It cou
oscillation effect.
strong interannual oscill
SST (degree celcius)

2003

2008

32
31
30
29
28
27
26
25
Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11

Year

Figure 3. SST Variability in the Southern part of Java
Sunda (bold line), and 1
Island and the Lesserr S
ash line)
standard deviation (dash
2010

2011

3

SST Anomaly (degree celcius)

2009

2
1
0

Jan-03Jan-04Jan-05Jan-06Jan-07
Jan-07Jan-08Jan-09Jan-10Jan-11

-1
-2
-3

Figure 2. SST Characteristics
cs during Dry Season
(June-July-August [JJA])

SST Anomaly

Year

Anomali SPL

Figure 4. SST Anomaly in Southern part of Java
Sunda (black bold line),
Island and the Lesserr S
(black dash line), 1 standard
Filtered SST anomaly (bla
ine)
deviation (gray dash line)

dex (DMI)
3.3 Dipole Mode Inde
3.2 SST Variability alon
along the Southern
part of Java Island
and and the Lesser
Sunda
The temporal variabilit
bility of SST from
2003-2011 along the southe
southern part of Java
and the lesser Sunda are show
shows in the figure
3. During 2003 and 2004, tthe SST indicated
were less than 1 standard
rd deviation during
the rainy season (DJF per
period). Meanwhile,
the SST was greater tthan 1 standard
deviation in 2011 during the dry season (JJA
period).
Further analysis of SST
T aanomaly is shown
tive anomaly were
in figure 4. The positive
occurred in the middle of 2005, early 2007
and end of 2010. Howeve
ever, the negative
anomalies were shown in the middle until

ode Index) is an IODM
DMI (Dipole Mode
from SST data (Saji et
index that calculatedd fro
ta used were 9 years
al., 1999). The data
monthly SST data dderived from Aqua
MODIS. Figure 5 iss show the DMI value
nd has an indication of
during 2003-2011 and
high DMI at end of 2004 until early of 2005,
end of 2006 and 2007, and also middle of
which are more than 1
2010 and end of 2011,, w
0.6oC). Figure 5 is also
standard deviation (0.6
ive IODM occurred in
show that the negative
2004- 2007 and 2010, while the positive
IODM occurred inn 2006, 2007 and 2011.

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12th Biennial Conference of Pan Ocean Remote Sens
ensing Conference (PORSEC 2014)
04 – 07 November 2014, Bali-Indonesia

-1,5

Year

-2,5

Figure 5. Dipole Mode Index (DM
(DMI) (black bold line),
and 1 standard deviation (dash
ash line)

3.4 Wavelet Transform

(ms-1)

The power spectrum ((PS) of DMIwith
95% confidence level (bold
old countur line) are
founded at midle of 2009
09 until 2011. The
period isaround 1 until 2 year (Figure 6a).
The IODM is clearly occur
curred in 2010 with
the period of 2 years.
ars. However, the
variability of SST shownn tthat the minimum
temperature is higher than
han normal condition
in the same year (Figure 3)
3). The SST in the
a) Standardize rainfall (monthly)
4
study
area is spatially incr
ncreasein 2009 and
the2 highest is occurred inn 2010 (Figure 1 gh).0 And the global wavelet
let spectrum (GWS)
-2
shown
that the IODM
DM wereoccurred
-4
periodically
with2006 time
period
eriod
around
12011until2012
2003
2004
2005
2007
2008
2009
2010
Time (year)
5 years globally (Figure
6b)
6b).

Period (years)

DMI

SPL JAWA-BALI-NT

2
4
8
16
32
2003

2006

2007

Time (year)

2008

2009

2010

2011

2012 0

2009

2010

2011

2012

(a)
SPL JAWA-BALI-NT

0.15 8
0.1 7
0.05 6
0 5
2003

4

2004

2005

2006

c) DMI Global Wavelet Spectrum

2007

Time (year)

2008

3

1

4

0

1

2

4
period (year)

8

16

32

(b
(b)
2004

2005

2006

2007
2008
Time (year)

2009

2010

2011

2012 0

(a)

d) 2-7 yr rainfall Scale-average Time Series

0.2
0.15
0.1
0.05
0
2003

2005

d) 2-7 yr rainfall Scale-average Time Series

2

32
2003

2004

0.2

2

8

2004

2005

2006

2007
2008
Time (year)

2009

2010

2011

2012

(b)

Figure 6. a. Power Spectrum
m of DMI, b. Global
Wavelet Spectrum (GWS) for DMI

Figure 7 shows the po
power spectrum of
SST in the southern partt of Java Island and

c) Global Wavelet JAWA-BA

1

1

16

2s-2)
Avg variance (m

(ms -1)

-0,5 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11

Period (years)

0,5

2)
Avg variance (C

1,5

Lesser Sunda. The period of SST variability
with 95% confidencee llevel are founded at
ime period of 1.5 year.
2003 to 2006 with tim
period in 2009 to 2011
Meanwhile, the time pe
ever the SST variability
is 1 to 4 years. Howeve
power spectrum for 2003
that shown by the powe
nciding with the DMI
to 2006 is not coinci
ight be caused by the
power spectrum. It might
annual phenomenon of the Pacific Ocean
oscillation-ENSO).
Beside
(El-nino southern oscill
a) Standardize SST (monthly)
of 4 that, the variabilityy oof SST has the similar
2
pattern
with the DMII in 2010. SST in the
va Island and Lesser
southern
part of Java
0
periodicity
with the DMI
Sunda
has
the
same
peri
-2
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
as shown in the GWS gr
graph.
Time (year)

Power (C2)

DMI (degree celcius)

2,5

Figure 7. Wavelet transform
rm in southern part of Java
1
2
3
4
5
Island
and
Lesser
Sunda
nda,
a) Power Spectrum of
2 -2
Power (m s )
SST, b) Global Wavelet
let S
Spectrum (GWS) for SST

In order to determ
rmine the relationship
bility and IODM in the
between SST variabilit
va Island and Lesser
southern part of Java
on coefficient between
Sunda, the correlation
the power spectrum of SST and DMI had
ure 8). The dot line in
been calculated (Figure
the figure 8 refers to the 95% confidence
correlation coefficient
level. Hence, the cor
above the confidencee llevel concluded as a
on. There is a positive
significant correlation.
correlation above the 95% confidence level,
significant correlation
which is show a si
ST in the southern part
between DMI and SST
nd Lesser Sunda. The
of Java Island and
587

2

4

Power (C2)

6

12th Biennial Conference of Pan Ocean Remote Sensing Conference (PORSEC 2014)
04 – 07 November 2014, Bali-Indonesia

Correlation Coefficient

significant positive correlations occurred in
the 1.5 to 1.7 years, 2.2 to 2.8 years, and 4.7
to 5 years’ time period. The result states that
SST in the southern of Java Island and
Lesser Sunda got a lot of impact from the
IODM during those periods. While a strong
negative correlation may indicate that the
annual variability of SST is caused by other
phenomenon.
1
0,5
0

-0,5 1,5

2,5

-1

3,5

4,5

Time Scale

Figure 8. Power Spectrum Correlation

4. CONCLUSION
The relationship between SST variability
and the IODM in the southern part of Java
Island and Lesser Sunda can be confirmed by
using the Aqua Modis Satellite data. It is
clearly shown in 2010 that SST in those
regions has a strong relationship with IODM
phenomenon.
This relationship is well
confirmed by spatial, temporal and even by
the wavelet method.
For further study, the numerical
simulation will be useful to find an impact
for the ecology and climate condition in
Indonesia, weather by the assimilation of
satellite data or the in situ data.
Acknowledgments
The authors are grateful to the Udayana
University who was supported under the
scheme of “Hibah Penelitian Unggulan
Universitas Udayana” with contract number:
21.20/UN14/LPPM/2012.
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