PROCEEDINGS OF IPI RESEARCH COLLOQUIUM 2017PROCEEDINGS OF IPI RESEARCH COLLOQUIUM 2017 OCTOBER 1-3,...

PROCEEDINGS OF IPI RESEARCH COLLOQUIUM 2017

OCTOBER 1-3, 2017

INSTITUTE OF CLIMATE CHANGE (IPI)

UNIVERSITI KEBANGSAAN MALAYSIA

eISBN 978-967-0829-83-8

Editors:

Rawshan Ara Begum

Fatimah PK Ahamad

Mohammad Rashed Iqbal Faruque

Sabirin Abdullah

Khairul Nizam Abd Maulud

Technical Committee:

Noridawaty Mat Daud

Farhanah Md Isa

Disclaimer: The authors of individual papers are responsible for technical, content and

linguistic correctness.

PUBLISHED BY INSTITUTE OF CLIMATE CHANGE (IPI)

Cetakan Pertama / First Printing February 2018

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Sidang Editor / Editorial

Rawshan Ara Begum

Fatimah PK Ahamad


Sabirin Abdullah

Khairul Nizam Abdul Maulud

Jawatankuasa Teknikal / Technical Committee

Noridawaty Mat Daud

Farhanah Md Isa

Rekabentuk oleh / Designed by

Noor Shuhaira Rejab

eISBN 978-967-0829-83-8

PREFACE

The Institute of Climate Change (IPI) Research Colloquium 2017 was held at the Felda

Residence Trolak, Perak, on 1-3 October, 2017 and organised by the Institute of Climate

Change (IPI), Universiti Kebangsaan Malaysia (UKM) in collaboration with the UKM-YSD

Chair in Climate Change. This is the first IPI Research Colloquium focusing on research

progress and articles of the IPI postgraduate students. It is also a continuation of the

ANGKASA Postgraduate Research Seminar and Colloquium from 2014 to 2016.

The IPI Research Colloquium provides an excellent opportunity for all the postgraduate

students, presenters, researchers, supervisors, evaluators and participants to meet, discuss and

share a broad range of issues in terms of research progress and presentation, thesis writing,

challenges and improvements as well as preparing and writing manuscripts for publication. The

proceedings include all the accepted articles consisting of full paper and abstract that were

presented in the IPI Research Colloquium 2017. The papers of the proceedings are arranged

according to the presentation sessions covering the research themes of climate change and

space science.

We would like to thank all the postgraduate students, presenters, participants, researchers,

supervisors, reviewers, evaluators, organising committee members and those who have

contributed to make this colloquium successful. We also acknowledge UKM-YSD Chair in

Climate Change for sponsoring the publication of the proceedings.

We are indeed very happy for the publication of the Proceedings of IPI Research Colloquium

2017. We believe the proceedings will contribute to the improvement and further development

of knowledge and intellectual in the fields of climate change and space science.

Thank you very much!

Best regards,

Editors

February 2018

CONTENTS

NO. TITLE & AUTHORS PAGE

NUMBERS

1 Possibility of UAV Application to Monitor Shoreline Changes 1 Abdul Aziz Ab Rahman


Othman Jaafar

2 Study on Coastal Vulnerability Index (CVI) for Selangor Coastal Area 4 Muhammad Afiq Ibrahim


Fazly Amri Mohd

Mohd Radzi Abdul Hamid

Nor Aslinda Awang

3 GIS-integrated Infrastructure Asset Management System 7 Muhammad Aqiff Abdul Wahid


Mohd Aizat Saiful Bahri

Muhammad Amartur Rahman

Othman Jaafar

4 Assessing of Shoreline Changes by using Geospatial Technique 12 Siti Norsakinah Selamat


Othman Jaafar

5 Heat Stress on Mangrove (Rhizophora apiculata) and Adaptation Options 16 Baseem M. Tamimi

Wan Juliana Wan Ahmad

Mohd. Nizam Mohd. Said

Che Radziah Che Mohd. Zain

6 Terahertz Meta-surface Absorber for Absorbing Application 20 Md. Mehedi Hasan


Mohammad Tariqul Islam

7 Labyrinth Resonator for Wideband Application 24 Md. Jubaer Alam



8 Design and Analysis of a Metamaterial Structure with Different Substrate

Materials for C Band and Ku Band Applications

28

Eistiak Ahamed


Mohd Fais Mansor

9 9th September 2011 Solar Flare to MAGDAS Reading 33

Norhani Muhammad Nasir Annadurai

Nurul Shazana Abdul Hamid

Akimasa Yoshikawa

10 Comparison of the Neural Network and the IRI Model for Forecasting TEC

over UKM Station

35

Rohaida Mat Akir

Mardina Abdullah

Kalaivani Chellappan

Siti Aminah Bahari

11 Variation of EEJ Longitudinal Profile during Maximum Phase of Solar

Cycle 24

39

Wan Nur Izzaty Ismail


Mardina Abdullah

Akimasa Yoshikawa

12 The Impact of High Environmental Temperature on Branchial

Ammonia Excretion Efficiency between Euryhaline and Stenohaline

Teleosts

42

Hon Jung Liew,

Yusnita A Thalib

Ros Suhaida Razali

Sharifah Rahmah

Mazlan Abd. Ghaffar

Gudrun De Boeck

13 Large Scale Wave Structure Prior to the Development of Equatorial

Plasma Bubbles

46

Suhaila M Buhari

Mardina Abdullah

Tajul Ariffin Musa

14 Determining the Probability of Sediment Resuspension in the East Coast of

Peninsular Malaysia through Wind Analysis

49

Shahirah Hayati Mohd Salleh

Wan Hanna Melini Wan Mohtar


Nor Aslinda Awang

15 A Review on Forest Carbon Sequestration as a Cost-effective Way to

Mitigate Global Climate Change

53

Asif Raihan

Rawshan Ara Begum

Mohd Nizam Mohd Said

Sharifah Mastura Syed Abdullah

16 Review of Methodology on Source Apportionment of PM2.5 near a Coal-

fired Power Plant using Multivariate Receptor Modelling

58

Ahmad Hazuwan Hamid

Md Firoz Khan

Mohd Talib Latif

17 Study of Maximum Usable Frequency (MUF) for High Frequency (HF)

Band at Equatorial Region in Malaysia

62

Johari Talib

Sabirin Abdullah

18 Performance Analysis of a Negative-permeability Metamaterial Inspired

Antenna with 1U Cubesat

65

Touhidul Alam

Farhad Asraf

Mohammed Shamsul Alam


Mengu Cho

19 Zonal Velocity Drift of Equatorial Plasma Bubbles Calculated over

Southeast Asia

68

Idahwati Sarudin


Mardina Abdullah

Suhaila M Buhari

20 Effect of Elevated Atmospheric Carbon Dioxide on Mangrove Growth in

Controlled Conditions

71

Baseem M. Tamimi

Wan Juliana Wan Ahmad

Mohd. Nizam Mohd. Said

Che Radziah Che Mohd. Zain

21 Observations of Lightning and Background Electric Field in Antarctica

Peninsula

75

Norbayah Yusop

Mardina Abdullah

Mohd Riduan Ahmad

22 Determination of the GPS Satellite Elevation Mask Angle for

Ionospheric Modeling the Ionosphere over Malaysia

78

Siti Aminah Bahari

Mardina Abdullah

Zahra Bouya

Tajul Ariffin Musa

23 A New Wide Negative Refractive Index Meta-atom for Satellite

Communications

82

Mohammad Jakir Hossain



24 Ionospheric Bottomside Electron Density Thickness Parameter over

Southeast Asian Sector

87

Saeed Abioye Bello

Mardina Abdullah


25 Assessing the Accuracy of Hydrodynamic Parameters using Statistical

Approaches

91

Fazly Amri Mohd


Othman A. Karim

Rawshan Ara Begum

26 Socio-economic Impacts of Climate Change in the Coastal Areas of

Malaysia

95

Mohd Khairul Zainal

Rawshan Ara Begum


Norlida Hanim Mohd Salleh

PRESENTERS PROFILE 100

PROCEEDINGS OF IPI RESEARCH COLLOQUIUM 2017, 1 – 3 OCTOBER 2017,

FELDA RESIDENCE TROLAK, PERAK, MALAYSIA

1

Possibility of UAV Application to Monitor Shoreline Changes

Abdul Aziz Ab Rahman1, Khairul Nizam Abdul Maulud1,2 and Othman Jaafar2

1Earth Observation Centre, Institute of Climate Change (IPI), Universiti Kebangsaan Malaysia, 43600 UKM, Bangi,

Selangor, Malaysia 2Department of Civil & Structural Engineering, Faculty of Engineering & Built Environment,

Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor Malaysia

*corresponding author, E-mail: [email protected]

Abstract

Unmanned Aviation Vehicles (UAV) are recently growing

up fast in the world market. Moreover, it is the first choice

for companies to complete their work especially in survey

work. In fact, conventional survey work is expensive and

takes more time for a complete project. It is used for

mapping and monitoring of air for coastal areas. The

findings show that UAV has been a key tool for conducting

topographic change monitoring works along the coast and

can do good results. This paper focuses on the literature of

the possibility of UAV to monitor the shoreline changes. In

addition, UAV images can generate into orthophoto and the

images also have their own projection because it is

geotagged due to GPS signals from satellites. Consequently,

the rate of physical changes either erosion or acceleration

can be determined using monitoring along coastal area

using this UAV. Hence, this paper presents to show and

prove that shoreline changes can be monitored by UAV

application.

1. Introduction

Generally, landscape changes can help to understand how

certain traits and elements exist and behave. Understanding

functions, relationships and rules can support landscape

management and sustainable development such as the

prevention is the effect of the devastating floods.

Furthermore, the coastal area is experiencing destruction due

to sea action and the causes of nature and humanity caused

by it. Changing topography on the beach and sand dunes

should be assessed, after severe and regular events, to build

a model that can predict the evolution of this natural

environment. This is an essential app for LIDAR airborne,

and conventional photogrammetry is also used for sensitive

monitoring of coastal areas (Gonçalves, & Henriques 2015).

According to Turner, Harley & Drummond (2016) UAV

beach engineering application is used here to illustrate the

practical use and potential benefits of this latest survey

technology. Over the last 2 years, the rapidly expanding

UAV survey has been successfully integrated into a four-

decade coastline surveillance program in Narrabeen Beach,

Australia. This has expanded the scope of the program to

include detailed measurements from the desert and coastal

erosion that covered the 3.5 km long dew on a spatial scale

and temporal resolution previously unprofitable. In fact,

Čermáková, Komárková & Sedlák (2016) mentioned that

Unmanned aerial vehicles are increasingly being used to

monitor small areas, e.g. Small water bodies (ponds). UAV

can yield faster results and usually have higher spatial

resolution. Therefore, this paper presents to show and prove

that shoreline changes can be monitored by UAV

application.

2. Review on UAV Application on Monitoring Shoreline Changes

All the methods were combined to display the possibility of

UAV application to monitor the physical changes of the

coast.

2.1. Beach topographical changes at the Ligurian Sea

This study was conducted at Region of Liguria, Italy which

is located at the north-western Mediterranean. Based on

Casella et al. (2016) writing state this region has been

monitored three times more than 5 months in autumn 2013-

2014 autumn (November 1, 2013, December 4, 2013, March

17, 2014) to get Digital Elevation Model (DEM) and beach

orthophotos. The coastal topography changes associated

with storm events and human activities are assessed in terms

of either increase or decrease of sediment and the transition

of dry wet boundaries that determine the coastline.

Moreover, the flying height was set up at 70m altitude and

the flight programmed by Microdropter OSD tool software

to cover the entire region coast. In addition, UAV pilots and

observer have the duty to control the mission and carry out

take-off and landing operations. It interfered with GPS

guided flights in the case of unwanted RPAS behaviour and

the most important are the pilot has the duty to follow the

flight from the land station and convey the change from the

designated path to the pilot (Casella et al. 2016).

2.2. The Structure from Motion Approach on Coastal Environment

Beach geomorphology requires accurate topographical

information on coastal systems called for the

implementation of coastal erosion simulation, flood



2

phenomenon, and coastal sediment budget assessment. For

such a study, the availability of topographic datasets is a

specific basis for systems characterized by complex

morphology. The presence of sand dunes should be carefully

considered because of their role in coastal defence as a

natural protective feature, providing sediment supply to the

shore and protecting the interior from storm surges (Mancini

et al. 2013).

This study stated that the unmanned aerial vehicle

(UAV) for reconstruction of the 3D coastal environment is

being investigated in this study. UAV images in the sandy

beach environment require additional verification

procedures. Tidal plates, beaches, and sewerage systems

show different differences in images obtained by air surveys

near the possibility of responding to the dominant grain size

or with the presence of coastal plants. This study was

successfully held at Ravenna, Italy on the North Adriatic

coast. The Ravenna coastline, stretching less than 40 km in

the direction of N-S, is characterized by the presence of a

natural site and sandy beach equipped, sometimes bordered

with pine forests, and proximate urban areas. Almost all of

these areas are affected by erosive trends as a result of

several factors, such as the reduction of strong river

sediment supply, the destruction of sand dunes system by

tourism-related pressure, the establishment of ports and

poles that affect sedimentation along the coast, land

subsidence, ineffective defensive structure, and rising sea

levels.

Despite, Mancini et al. (2013) also found that UAV

system used is the VTOL (Vertical Take Off and Landing)

hexacopter designed and produced by Sal Engineering (Sea

Air Land) and is equipped with calibrated Canon EOS 550D

digital cameras. The survey line was designed using an

orthophoto air at an average aviation height of 40 m and the

acquisition was automatically set at one shot per second.

Operating operations and landing operations are manually

guided by remote pilots. During the survey, flights are

automatically enabled by waypoints. Acquisition time

provides up to 10 overlapping images for any single land

feature and any attempt to visualize coverage of aerial

imagery for a limited area will result in a somewhat

confused figure.

Further, The NRTKs have been used on May 27, 2013.

The NRTK study has a threefold collection purpose.

Eighteen 3D Land Control Points (GCPs) consisting of

cubes (30×40×30 cm) with 20 cm wide board chess are

printed at the top, 126 Points of Authentication (VP) at a

surface level along five transects across the whole Dots, and

19 Vertical Targets (VTs) designed for georeferenced. The

GNSS-NRTK study performed by multiple frequency GRS1

(Topcon) for the mentioned datasets (GCPs, VPs, and VTs)

each produces RMS values less than 0.018 m and 0.029 m

for horizontal and vertical precision respectively. Horizontal

coordinates are referred to the UTM 33N Zone (ETRF00),

while the vertical values also referred to min sea level using

the ITALGEO2005 geoid model provided by the Italian

Institute of Geography (IGMI) (Teatini, Ferronato,

Gambolati, Bertoni, & Gonella, 2005).

Table 1: Hexcopter Specification (Mancini et al. 2013)

Manufacturer Description

Type Micro-drone Hexacopter

Engine Power 6 Electric Brushles

Dimension & Weight 100 cm, 3.3 kg (total

weight for all equipment

is approximately 5 kg)

Flight Mode Dual, automatic based on

waypoints or base on

wireless control

Endurance Standard 20 min (+5 min

safety

Camera Configurations Digital gimbal, Canon

EOS 550D (focal length

27 mm), res. 5184 ×

3456 Bi-axial roll and

pitch control

2.3. Delineation a Part of Shoreline of the Chosen Pond at Pohranov Pond, Czech Republic

The attractive area is close to the town of Pardubice, in the

Czech Republic. Case study studies part of Pohranov's beach

shoreline, close to Pohranov municipality. The pond size is

0.4 km2and it is surrounded by forests. This means that the

observation to collect the data is difficult. Satellite

Imagination does not provide data with the appropriate

resolution. Therefore, UAV represents a more appropriate

way of data collection in this case. The UAV provides data

in high contrast and lower costs are also lower. Tarot 690 is

one of UAV type was used for Pohranov pond monitoring. It

can be characterized as follows: vent tool; 6 gears; Average

impeller of 0.985 m; Height of 0.35 m, the maximum speed

of 70 km / h. This UAV has the following restrictions

(conditions where it cannot be used): temperature below -

10ºC; wind spinner from 10 m.s-1; mist with sight below 100

m; frozen creation on airscrew; drizzle, rain and snow. The

conclusion must be done several times in a few days to get a

short time series. The time horizons are selected according

to the weather conditions described above and cover longer

periods of time ie: 7. 7. 2015, 18. 7. 2015, 23. 8. 2015 and 2.

11. 2015. The flight altitude is 80 m (high installed in UAV

software before the flight) for all flights (Čermáková et al.

2016).

This article also mentioned that during the observation,

videos were collected by the UAV cameras are on the

spectrum only. Videos provided from UAV must be initially

processed to create an image of each observation. In

particular, the image must be selected and created from the

video. Software not available Free Video to JPG Converter

is used for this step. Combining all the collected images into

one picture is the next step. Image Composer Editor

(available for free) is used for this step. A Mosaicsgenerated

from the image cannot be distorted as only the central part is

selected for merging. The centre of the image cannot be



3

inferred. The resulting image represents our monitored area

and changes during the monitoring period. Figure 1 shows

the type of UAV used in this observation.

Figure 1: UAV Tarot 690 (dji, 2017)

3. Discussion of the Possibility of UAV Application

Based on the all methods were combined to display the

possibility of UAV application to monitor the physical

changes of the coast, show that UAV is capable for

monitoring coastal changes and it is sufficient to state that

using UAV is good enough to see the physical changes of

the coastal area. Various of UAV methods have been

utilised to monitor the shoreline changes such as based on

the previous literature show that all the images acquisition

was taken at range altitude from 40m to 80m. Furthermore,

show that within that range of altitude, after mosaicking

stage it will produce the orthophoto result to see the physical

changes of the coastal area. The orthophoto result represents

the monitored area. The result can be seen more clearly

when the UAV is used as a major tool to retrieve the data

compared to satellite images where the image is unclear.

Mancini et al. (2013) identified that the coastal change

monitoring method needs to set off some control points

which the Ground Control Point (GCP) to the coordinate x,

y and z to avoid distortion. As example, the study at the

Ravenna, Italy used the GNSS-NRTK to produce RMS

values less than 0.018m for the horizontal and 0.029m for

the vertical precision. Therefore, when the image was

georeferenced by the coordinates the images is easy to

process and it will be placed at exact location. The less RMS

values get the less distortion will affected to the results.

However, the study at Pohranov Pond, Czech Republic

did not use the method of placing GCP in coastal areas

because they already get the reference data from the State

Administration of Land Surveying and Cadastre (CUZK).

The data collection is focused on the video that was taken by

the UAV. The main disadvantage of this method is the

actual value of coordinate for georeferenced cannot get the

real value because there is no in situ observation to get the

real coordinate but still can use to process the data to get the

orthophoto.

Thus, since the possibility of UAV application to

monitor shoreline changes has been proved, I will choose

low cost UAV to monitor shoreline to see the physical

changes at coastal area.

4. Conclusion

In conclusion, this paper is showed and proved that

shoreline changes can be monitored by UAV application.

Based on all the previous study, using UAV for monitor the

shoreline changes is one of the most successful methods for

determining and see the physical changes on the shoreline

area. UAV application is possible to monitor shoreline

changes. Further research can be conducted by using more

high intense of UAV to monitor shoreline changes.

Acknowledgements

Praise be to Allah Almighty for this opportunity. This study

is supported by a Research Discipline Research Grant

Scheme (TRGS/1/201/UKM /02/5/1). The author also

wishes to thank the Earth Observation Centre, Institute of

Climate Change, UKM.

References

[1] Casella, E., Rovere, A., Pedroncini, A., Stark, C. P.,

Casella, M., Ferrari, M. & Firpo, M. 2016. Drones as

tools for monitoring beach topography changes in the

Ligurian Sea (NW Mediterranean). Geo-Marine Letters,

36(2), 151–163. doi:10.1007/s00367-016-0435-9

[2] Čermáková, I., Komárková, J. & Sedlák, P. 2016. Using

UAV to detect shoreline changes: Case study -

pohranov pond, Czech Republic. International Archives

of the Photogrammetry, Remote Sensing and Spatial

Information Sciences - ISPRS Archives, 2016–

Janua(July), 803–808. doi:10.5194/isprsarchives-XLI-

B1-803-2016

[3] Gonçalves, J. A. & Henriques, R. 2015. UAV

photogrammetry for topographic monitoring of coastal

areas. ISPRS Journal of Photogrammetry and Remote

Sensing, 104, 101–111.

doi:10.1016/j.isprsjprs.2015.02.009

[4] Mancini, F., Dubbini, M., Gattelli, M., Stecchi, F.,

Fabbri, S. & Gabbianelli, G. 2013. Using unmanned

aerial vehicles (UAV) for high-resolution reconstruction

of topography: The structure from motion approach on

coastal environments. Remote Sensing, 5(12).

doi:10.3390/rs5126880

[5] Turner, I. L., Harley, M. D. & Drummond, C. D. 2016.

UAVs for coastal surveying. Coastal Engineering, 114,

19–24. doi:10.1016/j.coastaleng.2016.03.011



4

Study on Coastal Vulnerability Index (CVI) for Selangor Coastal

Area

Muhammad Afiq Ibrahim1, Khairul Nizam Abdul Maulud1, 2, Fazly Amri Mohd2,

Mohd Radzi Abdul Hamid3, Nor Aslinda Awang3

1Institute of Climate Change, Universiti Kebangsaan Malaysia (UKM) 2Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (UKM)

3Coastal Management & Oceanography Research Centre, National Hydraulic Research Institute of Malaysia,

Ministry of Natural Resources & Environment, Selangor, Malaysia


Abstract

Sea level rise has high potential on changing and affecting

the ecosystem that already exist in the local area. This also

affects the local residential and local activities at the coastal

area. The rate of sea level rise is greater than the global rate

especially at low ground area. Thus, this research is to study

on coastal vulnerability index (CVI) for Selangor coastal

area. Selangor coastal area has been announced as one of the

area that is affected by erosion due to sea-level rise impact.

This area has been reported to be eroded for the past few

years until today and still on going. The only way to deal with

this is to do some adjustment and adaptation on the coastal

area so that the effect of sea-level rise can be minimized.

Using coastal vulnerability index (CVI) method, which is a

relatively simple and functional method that can be used to

estimate the vulnerability of the coastal area against erosion

due to of sea-level rise phenomena. In this study, six physical

parameters were taken count in coastal vulnerability index

calculation. By ranking the vulnerability of the coastal area,

it is easier to identify the areas that area comparatively more

vulnerable to sea-level rise changes.

1. Introduction

Climate change has causes the change on the environment

such as ice on rivers breaking up earlier, the shrunk of the

glaciers and also plant and animals ranges have shifted. This

will result on melting of ice, sea level rise and global

warming as shown in figure 1 below. The Intergovernmental

Panel on Climate Change (IPCC) has predicted that the

global temperature will rise from 2.5 up to 10 degrees

Fahrenheit over the next century [1]. The increases in global

temperature somehow give beneficial impacts on some area

and harmful ones in the others. As the global temperature

increase over time, the net annual cost also increases. Earth

ecosystem is disturbed because of the global climate change

that occurs regularly today. Humans and other living things

on Earth is threatened by the climate change that causes

many houses and habitats were destroyed and less place left

for living.

Climate change shows the difference on earth atmosphere

condition which is mainly consist of the sea, surface area that

is covered by ice and also all human activities [2]. The

physical impact of sea level rise is explained that sea level

rise leads to flood and also the movement of low-land and

humid-land on the Earth [3]. Due to this, the local community

live nearby coastal area is threatened and disturbance in

economic activities in that area. That’s why it is very

important to know the hydrodynamic behaviour of the sea

based on several aspects includes the beach structure,

sediment transportation and also the beach morphology

change and assessment. The effect of sea level rise from

global warming has cause the coastal area and nearby island

in Malaysia to be affected by flood, coastal erosion and

destruction of ecosystem at wetlands and swamp areas. The

flood incidence at Johor in 2007 might be one of the sea level

rise effect that may cause from the heating temperature in

Malaysia that destroy a large-scale settlement area and also

affecting the economic activities in the area.

2. Coastal Vulnerability Index (CVI)

Coastal vulnerability index (CVI) is a relatively simple and

functional method that can be used to estimate the

vulnerability to erosion of any coastal zone regarding the

future sea-level rise [5]. It is an index representative of six

physical variables to be related in a quantifiable manner that

can be easily understandable. The six physical variables

includes geomorphology, mean tidal range, sea-level rise

rate, erosion and accretion, mean height and significant wave

and also coastal slope. It combines the sensitivity of coastal

zone to changes and also the ability of the coastal to adapt

the changes made. Using numerical data that is arranged by

ranking, this method can highlight the areas where the

various effects of sea-level rise may be the greatest. The

geometric average is quite sensitive to small changes in

individual ranking factors but the square root is used to

reduce the extreme range. Thus, it is important to identify the

coastal vulnerability index of the coastal area before



5

executing any methods of coastal protection at a specific area

in order to prevent any erosion cases.

2.1. CVI Calculation

CVI value can be calculated using the following formula. By

multiplying all the parameters and divide into total number of

parameters then square root of the answer is the CVI value.

The formula can be represented as follows:

6

)*****( fedcbaCVI , (1)

where;

a = geomorphology

b = mean tidal range

c = sea-level rise

d = erosion and accretion

e = mean height and significant wave

f = coastal slope

3. Discussion

The discussion of this paper is focusing on the basic physical

parameters that is used for coastal vulnerability index in

Selangor coastal area. The following parameter are suitable

and has been identified to be used for coastal vulnerability

index study at Selangor coastal area. The parameters are

listed below.

3.1. Geomorphology

Geomorphology is the study of the nature and history of

landforms and the processes which create them. Initially, the

subject was committed to unravelling the history of landform

development, but to this evolutionary approach has been

added a drive to understand the way in which

geomorphological processes operate. In many cases,

geomorphologists have tried to model geomorphological

processes, and, more recently, some have been concerned

with the effect of human agency on such processes.

3.2. Mean Tidal Range

Tidal range is the difference between the high tide and the low

tide. The tidal range is the vertical difference between the

high tide and the succeeding low tide. Tides are the rise and

fall of sea levels caused by the combined effects of the

gravitational forces exerted by the Moon and the Sun and the

rotation of the Earth. The tidal range is not constant, but

changes depending on where the sun and the moon are. The

most extreme tidal range occurs when the gravitational forces

of both the Sun and Moon are aligned, reinforcing each other

in the same direction which is called the new moon or in the

opposite directions which is called the full moon. This type of

tide is known as a spring tide. During neap tides, when the

Moon and Sun's gravitational force are in a right angle to the

Earth's orbit, the difference between high and low tides is

smaller. Neap tides occur during the first and last quarters of

the moon's phases. The largest annual tidal range can be

expected around the time of the equinox, if accidental with a

spring tide.

Tidal data for coastal areas are published by the

Department of Survey and Mapping Malaysia (JUPEM). It is

based on astronomical phenomena and it is predictable. Storm

force winds blowing from a constant direction for a prolonged

time interval combined with low atmospheric pressure can

increase the tidal range, especially in narrow bays. Such

weather-related effects on the tide, which can cause ranges in

excess of predicted values and can cause localized flooding,

are not calculable in advance.

3.3. Sea-level Rise Rate

Sea level rise is an increase in the volume of water in the

world’s oceans which resulting in an increase in global mean

sea level. Sea level rise is due to global climate change by

thermal expansion of the water in the oceans and by melting

of ice sheets and glaciers on land. Sea level rise at specific

locations may be more or less than the global average

depending on the environment of the location. Sea level rise

is expected to be ongoing for centuries. Based on IPCC

Summary for Policymakers, AR5, 2014, indicated that the

global mean sea level rise will continue during the 21st

century, very likely at a faster rate than observed from 1971

to 2010. Sea level rises significantly influence human

populations in both coastal and island regions and also

affecting natural environments like marine ecosystems in the

area.

3.4. Erosion and Accretion

Erosion is the action of surface processes such as water flow

or wind that remove soil, rock, or dissolved material from one

location to another location. Natural rates of erosion are

controlled by the action of geomorphic drivers, such as

rainfall, bedrock wear in rivers, coastal erosion by the sea and

waves, glacial plucking, and mass movement processes in

steep landscapes like landslides and wreckage flows. The

rates of such processes act control the rate of erosion.

Processes of erosion that produce sediment or solutes from a

place contrast with those of deposition, which control the

arrival and emplacement of material at a new location. While

erosion is a natural process, human activities have increased

the rate at which erosion is occurring globally around the

world.

Accretion is the process of coastal sediment returning to

the visible portion of a beach or foreshore following a

submersion event. A sustainable beach or foreshore often

goes through a cycle of submersion during rough weather

then accretion during calmer periods. If a coastline is not in a

healthy sustainable state, then erosion can be more serious

and accretion does not fully restore the original volume of the

visible beach or foreshore leading to permanent beach loss.

3.5. Mean Height and Significant Wave

The wave height value in a forecast, and reported by ships and

buoys is called the significant wave height. The term

significant wave height is historical as this value appeared to

be well correlated with visual estimates of wave height from



6

experienced observers. It can be shown to correspond to the

average 1/3rd highest waves (H1/3).

3.6. Coastal Slope

Coastal slope is an indication of the relative vulnerability to

inundation and the potential rapidity of shoreline retreat

because low-sloping coastal regions should retreat faster than

steeper regions. The regional slope of the coastal zone was

calculated from a grid of topographic and bathymetry

elevations extending about 5 km landward and seaward of the

shoreline.

4. Conclusion

Based on the discussion that has been made, it is clearly seen

that by using the six physical parameters, which are

geomorphology, mean tidal range, sea-level rise, erosion and

accretion, mean height and significant wave and coastal slope

of coastal vulnerability index formula by Gornitz, more

accurate estimation can be obtained regarding the

vulnerability of the coastal area to erosion. It also combines

the sensitivity of the coastal area to changes and also allow

the ability of the coastal area to adapt with the new

conditions. Thus, all the physical parameters would be used

for coastal vulnerability index (CVI) at Selangor coastal area

for further research.

Acknowledgments

I would like to thank the National Hydraulic Research

Institute Malaysia (NAHRIM). I also would like to

acknowledge to Ministry of Education for supporting the

TRGS research grant (TRGS/1/2015/UKM/02/5/1).

References

[1] IPCC. 2013. IPCC Fifth Assessment Report (AR5). IPCC, s. 10-12.

[2] Md.Jahi, J. 2009. Pembangunan Pelancongan dan Impaknya terhadap Persekitaran Fizikal Pinggir Pantai.

Malaysian Journal of Environmental Management,

10(2), 18.

[3] Faour, Ghaleb, Fayad, Abbas, Mhawej, Mario. 2013. “GIS-Based Approach to the Assessment of Coastal

Vulnerability to Sea Level Rise: Case Study on the

Eastern Mediterranean” 1 (i): 41– 48.

[4] Gornitz, V., White, T. W. & Cushman, R. M. 1991. Vulnerability of the US to future sea level rise.

Proceedings of the 7th Symposium on Coastal and Ocean

Management, 2354–2368.

doi:10.1017/CBO9781107415324.004.



7

GIS-integrated Infrastructure Asset Management System

Muhammad Aqiff Abdul Wahid1, Khairul Nizam Abdul Maulud2,3, Mohd Aizat Saiful Bahri4,

Muhammad Amartur Rahman4, Othman Jaafar4

1Institute of Climate Change, Universiti Kebangsaan Malaysia, Malaysia 2Earth Observation Centre (EOC), Institute of Climate Change, Universiti Kebangsaan Malaysia, Malaysia

3Department of Civil & Structural Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia,

Malaysia 4Prasarana UKM, Universiti Kebangsaan Malaysia, Malaysia

*corresponding auhor, E-mail: [email protected]

Abstract

Infrastructure asset management is a core process in asset

management. An organisation is constantly striving for a

better infrastructure asset management to ensure the

effectiveness in decision making. This paper aims to

investigate how infrastructure asset management can be

integrated with geographic information systems (GIS)

technology. In the previous study, multiple questions were

asked to identify how GIS can be integrated with asset

management, the requirements and the challenges also. The

studies revealed that GIS and asset management can be

integrated with spatial and non-spatial information of the

assets in GIS environment. However, there are requirements

and challenges in the process, such as the data need to be

converted into digital and GIS format. The size of

geodatabase also will mostly be occupied and it is a

necessity to have big storage. GIS technology also needs to

have the ability to absorb new technology which means it is

customizable based on projects and operations. The paper

provides an in-depth overview of how GIS can be integrated

with infrastructure asset management and highlight the

importance of GIS technology in asset management. An

integrated pipeline management systems was develop as a

preliminary prototype. The advantage is that it can improve

the effectiveness of decision making and managing pipeline

network.

1. Introduction

Infrastructure assets such as sewers, water pipes, roads and

electricity lines are the supporting pillars of a society

specifically an organization such as a university.

Infrastructure asset is a multiplex structure with extremely

important and essential elements for an organization [1]. In

addition, [2,3,4] mentioned that economic growth also

depends on the imperative role of the infrastructure asset.

The important roles of infrastructure assets require massive

attention from the management of an organization such as

policy makers, decision makers, asset managers and also

down to technical staff and users.

Investment in the development of the infrastructure

assets for a university is focusing on the maintaining the

good environment. Education institution needs to provide a

very calm and productive environment for their community

to enhance the learning process and to produce the next

generation that can benefit the country. Thus, infrastructure

asset management plays a vital role to support the needs of

the university’s community. The infrastructure assets also

should be uses and pass to many generations. Taken

together, managing asset is not a simple task. It takes a great

responsibility and many decisions can be wrong without

fully recognizing the complexity, diversity, and social and

technological evolution of the system [1]. Furthermore, a

great responsibility comes with great challenges. One of the

purposes of managing infrastructure asset is to extend its life

value. Without a proper method or tools, the inefficiencies

will lead to many negative decisions, profit loss and lastly

the investment becomes a waste.

At the same time, emerging new technology, science and

mathematics are influencing our approaches and

understanding in designing and analyzing infrastructure. The

public is getting aware the importance of good management

practice and its change the philosophy of long term

management responsibility [1,5]. In addition, new

technology such as Intelligent Transportation Systems (ITS),

Supervision, Control, and Data Acquisition (SCADA) and

Geographic Information System (GIS) signal the start of a

new understanding of future management system. This

paper briefly discusses the advantages of GIS technology in

infrastructure asset management as a decision support tool.

2. Methodology

This study was conducted to customise web applications

using ArcGIS Online – WebApp Builder to visualise the

information of pipeline infrastructure in UKM and also to

integrate the information of pipeline infrastructure with GIS

geodatabase. The study will cover UKM, Bangi area. The

study is divided into four phases as a guideline and each

phase needs to be done according to the guideline in order to

ensure the objectives can be achieved. Figure 1 shows the

workflow of the study.

Database design and application design is important

phase where all the spatial and non-spatial data are link

together. Then, the application needs to be able to

understand the database environment and able to translate

the data into a display in the application. Both of database

and application development used desktop and online

application of ESRI’s software.



8

Figure 1: System development framework

3. GIS in Asset Management

Spatial and information system capabilities of GIS

technology becomes an obvious solution to assist in the

management of infrastructure asset [6]. The capabilities to

answer questions about location, patterns, trends and

conditions that is GIS [7]. Many well-known that GIS can be

viewed as a software package, which is used to collect,

store, manipulate, analyze and display output data [8].

In theory Information Technology (IT) in asset

management have three major roles. IT is utilized in

collection, storage, and analysis of information spanning

asset lifecycle processes. Secondly, IT provides decision

support capabilities through the analytic conclusions from

analysis of data. Thirdly, IT provides an integrated view of

asset management through processing and communication

of information and thereby allow for the basis of asset

management functional integration [9]. The minimum

requirements for asset management at the operational and

tactical levels is to provide functionality that facilitates;

knowing what and where the assets that the organization own and is responsible for are

knowing the condition of the assets

establishing suitable maintenance, operational and renewal regimes to suit the

assets and the level of service required of them by present and future customers

reviewing maintenance practices

implementing job/resources management

improving risk management techniques

identifying the true cost of operations and maintenance, and

optimizing operational procedures [10].

Taking the point of knowing what and where the location

of the assets is where GIS comes to be acknowledged the

transformation of GIS technology from desktop-based

solution to the enterprise system will give the chance for an

organization to use spatial application in asset management

and services. A system with spatial integration is capable to

analyses a complex data structure based on spatial location,

such as visualize data using a map using various relation to

show the proximity, adjacency, and others spatial

relationship [11]. Asset management system with integration

of GIS technology is best suited for spatial asset

management. In addition, GIS technology plays an

important role in asset management within utility, power,

government, transportation, telecommunication, and much

more in asset intensive industry by providing the additional

tools for collecting and updating data with spatial location

[11].

The impact of GIS is increasing as the users and the

organization is keen to know the status of the asset but also

the location of the asset. Furthermore, many previous studies

of GIS integration to computerized maintenance

management systems (CMMS) have concluded that the

system integration will only benefit the user such as:

providing maps of utility with the work orders; tracing water

pipeline infrastructure prior to fieldwork; planning travel

roads for work crews; and scheduling maintenance of

infrastructure assets [12]. The integration of GIS with the

process of asset management will be a very effective

geospatial solution [11]. The process of planning and

making decisions will be better and also it will improve the

productivity and the customer relation will become more

convenient.

4. GIS-Integrated Infrastructure Asset Management

The key challenge to achieving effective infrastructure asset

management is to improve the effectiveness of decision

making. However, effective infrastructure asset

management seems to be more challenging since: the

function of infrastructure assets is complex; a standard is

needed to define failure and benefits of the assets; and these

standards are hard to quantify or measure [13]. At the same

time, the challenges faced from the complexity caused by

technical, economic, environmental, political and social

factors [14]. Over the years, the expectations in terms of

reliability, safety and availability of the infrastructure

networks also have steadily increased [15]. The crucial

assessment here is infrastructure asset management is a

method of a process to help improve the decision making.

The complexity faces in infrastructure asset management

have continually caused public agencies or an organization

to continually allocated large budgets for the maintenance,

renovation and reconstruction work. However, this situation

has effected many agencies. These agencies are unable to

guarantee a performance level that meets the expectations

of the public because of budgetary constraints [16]. The

new approach has emerged in asset management for public

agencies which to achieve more value with fewer resources

[17]. While these approaches clearly pointed out different



9

kind of models, numbers and decisions focus, there are

three general areas of decision making can be identified:

decisions with regard to the infrastructure objectives of the public agencies;

decisions with regard to the performance-related situation of the agency’s infrastructure; and

decisions with regard to the interventions applied by the agency to the infrastructure [16].

Another approach to improve the decision making is to

integrate infrastructure asset inventory data and spatial data

by using GIS technology. This approach will not only

improve the data access but the management capability with

the information that will make the decision effective.

4.1. Requirements and Challenges

The main purpose of a GIS-integrated infrastructure asset

management system is to maintain an accurate, updated, and

reliable data on the current infrastructure assets. Moreover,

the systems enable users to efficiently access this data to

make future predictions and decisions of the infrastructure

performance, to plan maintenance operations and

maintenance budget [18]. The goal requires as such

requirements:

modeling and management of infrastructure physical, functional, and performance data as well as gathering

condition data in a timely and effective manner

interoperation and data exchange between different function-specific software tools

modeling, management, and coordination of maintenance operations and effective communication of

accurate and timely information

the ability to customize the system to specific project or organization policies and to accommodate various

operations that reflect industry practices [19].

Each of these requirements has its own challenge to be

addressed. Firstly is the data, probably the most crucial

challenge that needs to be sort before the others. The size,

complexity, and the nature of data present several challenges

that the integrated system needs to address. An efficient data

gathering, analysis, and management techniques are the key

to develop successful GIS-integrated infrastructure asset

management system. Furthermore, the integrated system

should also support different modes of data access and

exchange such as centralized geodatabase, application-to-

application file exchange, and Intranet/Extranet access

[18,19].

To support the integration and interoperability of legacy

software tools a standard module need to be established.

This important implication in reducing the systems

implementation and maintenance time and cost [20]. It is

important not to spend money for a new tools or technology

when you can just upgrade current one by reused its in other

ways. By using this module also will not impact the

operation of the systems in overall.

Infrastructure asset management is not a single

operation, it is a multi-disciplinary process that involves a

lot of different operations but with the same purpose.

Although, it is very important to manage the inter-dependent

operations in a coordinated manner. Integrated systems

should enable the efficient flow of information among

various activities such as efficient access, sharing,

management, and tracking of documents. Infrastructure asset

management team needs to share information to organize

their tasks [18,19].

The integrated systems also should have a modular

architecture to cope with future modification, extension, and

technology improvement. Furthermore, another major

design consideration is the necessity to separate the

responsibilities between the function-specific toolset and

other framework components. Tools would provide users

with the functionality to perform specific tasks, while the

integrated systems components would provide the

functionality to integrate and manage different processes.

5. Implementation of an Integrated Pipeline Management Systems

A preliminary prototype has been developed on an

integrated pipeline management systems to support the

maintenance management of the National University of

Malaysia, Bangi as shown in Figure 2. The integrated

systems implemented several requirements as described in

the previous topic. Modelling and management of

infrastructure data in timely and effective manner. Second,

the data exchange between different software also can be

achieved. Thirdly, effective and accurate timely information

also can be shared among the management and

stakeholders. Lastly, the ability to customize the systems to

accommodate various operations and projects.

Figure 2: GIS-integrated pipeline management system.

As for the GIS-integrated pipeline management systems,

ESRI software which is ArcGIS has been chosen as a

medium application to integrate all the spatial and non-

spatial information. Moreover, a web GIS application will

be used to access all the pipeline information. The

integrated web GIS applications should provide an

informative solution to the users. Combining the database

that keeps all the information of the infrastructures and a

geodatabase that contain the spatial information of the

infrastructures into one and can access in one application.

ArcGIS Online technology is a convenient method to

use for publishing spatial data online [20]. It is a

collaborative, cloud-based platform that allows members of



10

an organization to use, create, and share maps, apps, and

data, including authoritative basemaps published by ESRI.

Through ArcGIS Online user will get access to ESRI’s

secure cloud, and use it to manage, create, store, and access

data as published web layers, and because ArcGIS Online is

an integral part of the ArcGIS system, user can use it to

extend the capabilities of ArcGIS for Desktop, ArcGIS for

Server, ArcGIS apps, and ArcGIS Web APIs, and ArcGIS

Runtime SDKs.

The applications already provide many templates that

can be used for the web applications and the user also can

choose to build new applications using Web AppBuilder.

Web AppBuilder offers the user more choices in

configuring the appearance, settings and functionality of the

web application. Furthermore, the web application using

visual and compositional themes offer in the Web

AppBuilder and following widgets layer list, attribute table,

print, zoom slider, measurement, home, scalebar, coordinate

and filter are added to provide more options for the user.

Once the web applications are ready it has an option where

it can be shared among the organization members. Only an

authorized member will have an access to the web

application because of the data security issues.

GIS-integrated asset management system is becoming

more of necessity in asset management, generally.

Infrastructure assets information which is previously stored

using conventional methods such as in paper form, paper

maps, CAD drawing and standard database are not efficient

anymore. However, this information can be used by

converting them into a geospatial data format. Converting

these information into digital based in not an easy task and

might take big size of data storage. Furthermore, a

geodatabase is created to store all the information. Spatial

data and attribute data are connected to each other in the

geodatabase. ESRI’s software such as ArcGIS is an

application to create, manage, edit, manipulate, visualize

and publish geospatial data.

The published service would be used in ArcGIS Online

and act as a medium to customise a web map application.

The web-map application is capable to provide and

visualize the spatial and non-spatial information of each

infrastructure asset. In addition, assets information can

easily be shared among the university management and with

the advantage of GIS mapping the information can easily be

interpreted by everyone.

6. Conclusion

Asset management is already existed a long time ago.

Although, the method is difference to what exists today, the

purpose of asset management is still the same. It is to have

an inventory of the assets and to make sure the investment

will only gain profit in the future. GIS capabilities in

providing a good platform for the user to customize and

configure the applications based on the user needs is a

privilege for the user to integrate it with infrastructure asset

management.

The process of storing, editing, manipulating and

visualizing the information of the infrastructure asset

becomes more convenient and efficient. Moreover, users are

able to access the updated data and share it among the

members of the organization. A good infrastructure asset

management will always benefit the organisation in many

ways. It would be a great help to management in making

better planning and decisions for the better future of the

organisation and its customers.

Acknowledgements

The authors acknowledge and thankful for the financial

support given by the Universiti Kebangsaan Malaysia Top

Down Grant through TD-2016-012.

References

[1] A.C. Lemer, Progress Toward Integrated Infrastructure-Assets-Management Systems: GIS and

Beyond. APWA International Public Works Congress

NRCC/CPWA Seminar Series “Innovations in Urban

Infrastructure, (410), 7–24. 1998.

[2] E. Too, Infrastructure asset: developing maintenance management capability. Facilities, 30(5/6), 234–253,

2012.

[3] L. Hardwicke, Australian infrastructure report card. Barton, ACT: Engineers Australia. 2005.

[4] M.V.D. Mandele, W. Walker, S. Bexelius, Policy development for infrastructure networks: concepts and

ideas, Journal of Infrastructure Systems, 12(2), pp. 69–

76, 2006.

[5] R. Haas, W.R. Hudson, L. Falls, Pavement Asset Management. Pavement Asset Management, 2015.

[6] G. M. Baird, Leveraging your GIS, Part 1: Achieving a low-cost enterprise asset management system. Journal,

American Water Works Association, 102(10), 16–20.

2010.

[7] D.I. Heywood, S. Cornelius, S. Carver, An introduction to geographical information systems, Harlow, England

; N.Y. : Prentice Hall, 2011.

[8] P.A. Burrough, and R.A.McDonnell, Principles of Geographical Information Systems, Oxford University

Press, Oxford, p.333, 1998.

[9] N.A.J. Hastings, Physical asset management. Physical Asset Management, 2010.

[10] A.Haider, Governance of IT for engineering asset management. Business Transformation through

Innovation and Knowledge Management: An

Academic Perspective - Proceedings of the 14th

International Business Information Management

Association Conference, IBIMA 2010, hlm.Vol. 1, 77–

95, 2010.

[11] J. Campbell, A.K.S.J. Jardine, McGlynn, Asset management excellence: optimizing equipment life-

cycle decisions. Dekker Mechanical Engineering,

2011.

[12] J. McKibben, D. Davis, Integrating GIS, computerized maintenance management systems (CMMS) and asset



11

management. 22nd Annual ESRI International User

Conference, 2002.

[13] R. Dekker, Applications of maintenance optimization models: a review and analysis. Reliability Engineering

& System Safety, 51(3), 229–240, 1996.

[14] R.I. Godau, The changing face of infrastructure management. Systems Engineering, 2(4), 226–236,

1999.

[15] G. Arts, W. Dicke, L. Hancher, New Perspectives on Investment in Infrastructures, WRR Amsterdam

University Press, Amsterdam, 2008.

[16] D. Schraven, A. Hartmann, G. Dewulf, Effectiveness of infrastructure asset management: challenges for

public agencies. Built Environment Project and Asset

Management, 1(1), 61–74, 2011.

[17] F.L. Moon, A.E. Aktan, H. Furuta, M. Dogaki, “Governing issues and alternate resolutions for a

highway transportation agency’s transition to asset

management”, Structure and Infrastructure

Engineering, Vol. 5 No. 1, pp. 25-39, 2009.

[18] M.R. Halfawy, D. Pyzoha, T. El-Hosseiny, An integrated framework for GIS-based civil infrastructure

management systems. Canadian Society for Civil

Engineering - 30th Annual Conference: 2002

Chellenges Ahead, June 5, 2002 - June 8, 2002,

hlm.Vol. 2002, 83–92, 2002.

[19] M. Halfawy, Integration of Municipal Infrastructure Asset Management Processes: Challenges and

Solutions. Journal of Computing in Civil Engineering,

22(3), 216–229, 2008.

[20] P. Seamann, Web mapping application of Roman Catholic Church administration in the Czech lands in

the early modern period. Geoinformatics FCE CTU

16(1), 2017.



12

Assessing of Shoreline Changes by using Geospatial Technique

Siti Norsakinah Selamat1, Khairul Nizam Abdul Maulud1&2, and Othman Jaafar2

1Earth Observation Centre, Institute of Climate Change, Universiti Kebangsaan Malaysia 2Department of Civil and Structural Engineering, Faculty of Engineering and Built Environment,

Universiti Kebangsaan Malaysia


Abstract

The changing of the shoreline position has become a major

problem that involve coastal zones around the world.

Therefore, analysing and understanding of shoreline

changes are importance task to address the issues of

shoreline changes. This study focuses on determination

analysis rate of shoreline changes using the geospatial

technique in 1993 to 2014. To archive our objectives multi

temporal data and high spatial resolution imagery used as

investigation data. The rate of shoreline changes was

computed using Digital Shoreline Analysis System (DSAS)

technique, where end point rate (EPR) has been used in this

study to determine the rate of shoreline changes for short

term analysis. Approximately 348 transects along Bagan

Pasir was created with 25 meter interval. Results illustrated

the average rate of shoreline changes between 0.01 to -

33.28 m/year during 1993 and 2006. From 2006 to 2014,

the rate of changes existed from 0.01 to 46.64 m/year. The

research proved that DSAS method can be an effective way

to determine the rate of shoreline changes.

1. Introduction

Climate change issues are the main problem that are often

discussed around the world. According to the [1] climate

change is a weather changing process that is complicated

and time consuming. Generally, climate change is not a

change of weather because the weather naturally changes

daily and even changes every hour. Climate change is a

weather pattern that has changed dramatically in recent

years and long term effects. These phenomena influenced by

two major factors that are natural changes and human

activities that contribute to the increase of greenhouse gases.

Therefore, critical natural disasters such as rising sea levels,

floods, landslides, coastal erosion, drought, forest fires and

haze due to the effects of climate change.

Human activity is a major factor contributing to climate

change from the mid-20th century [2]. Climate change can

also be attributed to the rise in global temperatures, known

as global warming. The phenomenon of global warming has

risen and is forecast to increase over time. Ice melting in the

Arctic is a major factor that causes sea level rise and poses a

threat especially to countries with high population rates and

socio-economic activities on coastal areas. Globally there

are about 400 million people living in the 20 meter sea level

and within 20 km of the beach [3] and stated these

phenomena seriously amplify risks to coastal populations

[4].

Nowadays, National development has been rising over

the years. Regarding that, coastal zones were recognized as a

centre of economy and tourism for the coastal country. The

increase in coastal populations indirectly contributes to the

development of coastal development. Malaysia has also

faced this situation. Hence monitoring coastal zones is

crucial for protecting and maintaining the environment so as

not to be affected by the development of coastal

development [3].

Shoreline change is one of the most dynamic processes

in coastal areas. Shoreline changes occurred caused by two

major phenomena such as natural phenomena and human

activities. In [5], it is found that natural change was due to

the process of unification between waves, currents, tides and

streams that often caused conflicts in the process of erosion.

Besides that shoreline is known as the main component

when determining the territorial boundaries of an area, but

unfortunately these zone is considered fragile area and easy

to change. Therefore, the mapping of shoreline changes

becomes an important process for analysing the history of

change and overcoming these problems.

Shoreline changes studies have been widely studied by

many authors such as [6], [7], [8], and [9]. Traditionally,

shoreline changes have been assessed by survey measuring,

where field measurements are needed to clarify data [10]

and [11]. However, rising technology help overcome this

problem. Geographical Information System (GIS) and

Remote Sensing technology able to cover a wide area and

capable to solve this problem efficiently. It can be proven by

the study conducted by [12], [13], and [14] which proves the

study using this approach is very useful and valuable.

The study area corresponds to the west coast of

Malaysia. It is located in Bagan Pasir, Selangor. These coast

categories as the muddy coast and recognized as density

populated area. Other than that, this area also knows as a

centre of economic for communities. Figure 1 illustrated the

condition of Bagan Pasir coastal area.



13

Figure 1: Location of study Area

This study explores the analysis of shoreline changes

using DSAS approach to investigate erosion and accretion

phenomena and calculate the rate of shoreline changes that

have occurred. The main goals of this study to analysis the

shoreline change over the year and compare patterns of

changes for short term changes.

2. Materials and Methods

This paper focuses on determination shoreline changes using

multi-resolution and multi-temporal data. The study adopted

a methodology for extraction shoreline position and

determine the rate of changes is that used by several authors

[12], [14], and [15]. This methodology is based on three

stage of data process which is extraction shoreline position,

DSAS processing and analysis rate of shoreline changes.

2.1. Data Sources

In this study, SPOT 5 and topographic maps datasets

acquired from 1993 to 2014 were used to determine the rate

of shoreline changes along Bagan Pasir area. Table1 shows

the data sources used for determination of shoreline changes.

Projection systems used in this study are Rectified Skew

Orthomorphic (RSO) in meter unit.

Table 1: Data sources used for this study

Type of data Year Scale/Resolutio

n

Topographic map 199

3

1: 50 000

SPOT 5 200

6

2.5 meter

SPOT 5 201

4

2.5 meter

2.2. Shoreline Extraction

The shoreline dataset from 1993 to 2014 was extracted

using ArcGIS 10.4 software by using manual digitizing

technique.

2.3. Shoreline Analysis

DSAS V4.4 is an extension of ArcGIS 10 software, was

developed by United States Geological Survey (USGS)

[16]. The DSAS provided five statistical methods to

determined rate of changes such as shoreline changes

envelop (SCE), Net Shoreline Movement (NSM), End Point

Rate (EPR), Linear Regression Rate (LRR), and Least

Medium of Square (LMS). This approach can calculate the

rate of shoreline change either short term or long term

changes. In addition, users can choose any method to

address their research objectives because every method has

their own advantages and disadvantages to calculate the

change. In this study used EPR calculation to determined

rate of shoreline changes. The EPR method is an effective

operation to determine short-term changes. This method

consider dividing the distance movement of shoreline by the

time between the older and the most recent time to

calculated rate of changes.

DSAS tool computes the rate of shoreline changes using

four steps: (1) shoreline preparation, (2) baseline creation,

(3) transect generation, and (4) computation rate of

shoreline changes by [16]. In order to determine the rate of

shoreline changes, 348 transects perpendicular to shoreline

were generated with 25 meter interval. The erosion and

accretion were calculated by using the difference between

older and most recent shoreline. At the end of this study, the

rate of erosion and accretion were categorized into six

classes as shown in Table 2.

Table 2: EPR shoreline classification [15]

Rate of shoreline

changes (m/year)

Shoreline classification

> -2 Very High Erosion

> -1 to < -2 High Erosion

> -1 to < 0 Moderate Erosion

0 Stable

> 0 to < 1 Moderate Accretion

> 1 to < 2 High Accretion

> 2 Very High Accretion



14

3. Results and Discussion

Shoreline analysis was conducted for two different periods

which are from 1993 and 2006 and then from 2006 and

2014. The results of the present study show in table 3,

evaluation rate of shoreline changes using EPR method for

short term changes analysis. Based on the results obtained

from year 1993 and 2006 show the highest erosion rate of

33.28 meters per year, while the highest accretion rate only

14.00 meters per year. Minimum readings for erosion rate

also exceed the accretion rate where the erosion rate is 0.06

meters and the accretion rate is 0.01 meters per year. It may

be seen in 13 years, shows that erosion phenomena exceed

those accretion phenomena. Figure 2 illustrated map of EPR

classification based on the rate of changes that occurred

along 1993 and 2006.

Table 3: Rate of shoreline changes using EPR method

1993 - 2006 2006 -2014

Erosion Accretion Erosio

n Accretion

Maximum 33.28 14 39.56 46.64

Minimum 0.06 0.01 0.01 0.01

Mean 11.7 6.09 13.16 9.26

Other than that, these results also show the rate of

changes that occurred along 2006 and 2014. The rate of

erosion changes from year 2006 and 2014 varied between

0.06 to 33.28 meters per year, while rates of accretion

changes fluctuate between 0.01 to 46.64 meters per year.

Here, the rate of erosion Here, the higher rate of erosion

was recorded is 39.56 meter while the accretion rate as high

as 46.65 meters per year. Based on these results shows both

rates of changes are significantly high recorded. Figure 3

represented map of shoreline classification based on EPR

calculation rate of changes between 2006 and 2014.

Based on these results, the rate of shoreline changes

during year 2006 and 2014 get the highest erosion rate

where applicable 39.56 meters per year compared with the

highest erosion during year 1993 and 2006 is 33.28 meters

per year. While, the highest rate of accretion occurred

during the year 2006 and 2014 compared with 1993 and

2006 where is 46.64 meters and 14.00 meters per year

respectively.

Figure 2: Classification rate of shoreline changes between

1993 and 2006

4. Conclusion

Bagan Pasir was known as high population density area

along the coast. It is also recognized as an economic centre

for some communities working in the fishing industry. The

historical investigation of shoreline changes is an important

task to determine the movement of shoreline for every year.

Monitoring of shoreline changes is easily and effectively

through GIS approach. This study provided the most

valuable information on the rate of shoreline changes

occurring at Bagan Pasir coastal area through DSAS

computation technique. This study has investigated the

changes according to two time period which are from 1993

and 2006 and then from 2006 and 2014. Based on the

analysis, Bagan Pasir experienced more erosion compared

with accretion phenomena. The findings showed that 1993

and 2006 indicated facing the higher erosion phenomena

compared with accretion which is 94.84% and 5.17%

respectively. Meanwhile, for 2006 and 2014 indicated the

same thing where the phenomena erosion still higher than

accretion phenomena with 68.43% and 31.57% respectively.

It may be seen along 21 years, shows that erosion

phenomena exceed that accretion phenomena occurred at

Bagan Pasir area. Therefore, further research and monitoring

are needed to emphasize the problem so that the erosion

phenomenon can be reduced.



15

Acknowledgements

The authors gratefully acknowledge to the Earth

Observation Centre, Institute of Climate Change, UKM for

sharing the satellite data. This study was supported by the

research grants of Trans Disciplinary Research Grant

Scheme (TRGS/1/2015/UKM/02/5/1) and Research

University Grant (AP-2015-009).

References

[1] Johnston. A, Slovinsky. P, & Yates K. L, Assessing the vulnerability of coastal infrastructure to sea level rise

using multi-criteria analysis in Scarborough, Maine

(USA). Ocean and Coastal Management, 95, 176–188,

2014.

[2] Reyes. S. R. C, & Blanco. A. C, Assessment of coastal vulnerability to sea level rise of Bolinao, Pangasinan

using remote sensing and geographic information

systems. International Archives of the

Photogrammetry, Remote Sensing and Spatial

Information Sciences, 39(B6), 167–172, 2012.

[3] Rasuly. A, Naghdifar. R, & M. Rasoli, International Society for Environmental Information Sciences 2010

Annual Conference Monitoring of Caspian Sea

Coastline Changes Using Object-Oriented Techniques,

2(5), 416–426, 2010.

[4] Gornitz. V, Couch. S, & Hartig, E. K. Impacts of sea level rise in the New York City metropolitan area. In

Global and Planetary Change (Vol. 32, pp. 61–88),

2001.

[5] M. Ekhwan, Hakisan Muara dan Pantai Kuala Kemaman , Terengganu : Permasalahan Dimensi

Fizikal dan Sosial Erosion in the Estuary and Coastal

Area in Kuala Kemaman , Terengganu : A Physical and

Social Dimension Setback, 69, 37–55, 2006.

[6] Chen. L. C, & Rau. J. Y, (1998). Detection of shoreline changes for tideland areas using multi-temporal

satellite images. Detection of Shoreline Changes for

Tideland Area Using Multi-Temporal Satellite Image,

19(17), 3383–3397, 1998.

[7] Lipakis. M, Chtysoulakis. N, & Kamarianakis. Y, Shoreline extraction using satellite imagery.

BEACHMED-e/OpTIMAL - Beach Erosin Monitoring.

2008.

[8] Khairul. N. A. M, & Rafar. R. M, Determination the Impact of Sea Level Rise to Shoreline Changes Using

GIS, International Conference on Space Sciences and

Comunication (IconSpace), 0–5, 2015

[9] Fitton. J. M, Hansom. J. D, & Rennie. A. F, Ocean & Coastal Management A national coastal erosion

susceptibility model for Scotland, 132, 80–89, 2016.

[10] Pujotomo. M. S, Coastal changes assessment using multi spatio-temporal data for coastal spatial planning

parangtritis beach yogyakarta Indonesia, 2009.

[11] Mills, J. P, Buckley. S. J, Mitchell, H. L, Clarke, P. J, & Edwards. S. J, A geomatics data integration

technique for coastal change monitoring, 2005.

[12] Anand. R, Chandrasekar. B. N, & Magesh. S. K. N. S, Shoreline change rate and erosion risk assessment

along the Trou Aux Biches – Mont Choisy beach on

the northwest coast of Mauritius using GIS-DSAS

technique. Environmental Earth Sciences, 75(5), 1–12,

2016.

[13] Erener. A, & Yakar. M, Monitoring Coastline Change Using Remote Sensing and GIS Technologies, 30,

310–315, 2012.

[14] Moussaid. J, Ait. A, Zourarah. B, & Maanan. M, Using automatic computation to analyze the rate of shoreline

change on the Kenitra coast, Morocco, 102, 71–77,

2015.

[15] Kermani. S, Boutiba. M, Guendouz. M, Guettouche. M. S, & Khelfani. D, Ocean & Coastal Management

Detection and analysis of shoreline changes using

geospatial tools and automatic computation : Case of

jijelian sandy coast ( East Algeria ). Ocean and Coastal

Management, 132, 46–58, 2016.

[16] Thieler. E.R, Himmelstoss. E.A, Zichichi. J.L, and Ergul. A, Dsas 4.0. Digital Shoreline Analysis System

(DSAS) Version 4.0—An ArcGIS Extension for

Calculating Shoreline Change, 2009.



16

Heat Stress on Mangrove (Rhizophora apiculata) and Adaptation Options

Baseem M. Tamimi1, Wan Juliana Wan Ahmad1, Mohd. Nizam Mohd. Said1, Che Radziah

Che Mohd. Zain2

1School of Environmental and Natural Resource Sciences, Faculty of Science and Technology,

Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia 2School of Bioscience and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia,

43600 Bangi, Selangor, Malaysia


Abstract

Global climate change has shown to have a significant impact

on critical ecosystems, that in turn has led to elevated CO2

and temperatures that accompany changes in many abiotic

factors, including mangrove forests, facing challenges in

their habitat. This study was conducted to investigate the

morphological and physiological attributes of the mangrove

Rhizophora apiculata in response increased air temperature

for the selection of tree species that are able to adapt to

climate change. The seedlings were grown in controlled

growth chambers with temperature of 38°C, CO2 at 450 ppm

and controlled condition for three months. The plants were

watered with two litres of saline water of 28 ppt every 48

hours. Thus, after two weeks the mangrove recorded positive

results for all parameters to high temperature. The

differences in temperature resulted in significant differences

and negative interaction between CO2 and increased

temperature that led to serious damage to all samples

compared to controlled samples, and decreased growth and

photosynthesis rates. These results suggested that low levels

of photosynthetic capacity may be attributed to the decreased

CO2 fixative reaction system and photosynthetic pigment

contents.

1. Introduction

Elevated atmospheric carbon dioxide concentration (CO2)

and concomitant increasing temperatures are changing the

global environment [1], due to these factors being

determinants in the photosynthetic rates in plants, any

changes they present in the atmospheric composition and

climate will significantly affect planetary ecosystems [2].

Over the last century, atmospheric CO2 concentration has

increased from 280 to 360ppm as previous studies have

indicated making this an eminent and undeniable global

environmental change (GEC), with the current rate of

increase averaging at 1.5 µmol mol–1 year–1 [3]. It’s expected

that CO2 concentrations can reach 700ppm by the end of the

century as global population and economic activity increases,

leading to warmer global temperatures [4]. Recent model

projections suggest a global mean surface air temperature

increase of 1 to 4.5°C by 2100 AD [5] and the 0.3 to 0.6°C

rise of mean annual surface air temperature over the last

century shows the clear effect of recent atmospheric changes

to projected increase in temperature [6]. However, important

details in (a) diurnal and seasonal patterns, (b) frequency,

timing and duration of extremes (e.g. high or low

temperatures, late or early frosts), and (c) climatic variability

can be obscured by these broad mean annual changes in

temperature predictions [7]. One example is that recent

scenarios predict most warming in mid- and high-northern

latitudes in late autumn and winter, and little or none (or even

a cooling in mid-latitudes) in summer [5], which could affect

growing season length. Indeed, there is already evidence of a

change in growing season length [8]. Another example is the

strong evidence that, over land, the increase in night time

minimum temperature has been about twice the increase in

the maximum [6]. Plant growth will be greatly affected by the

continuing changes in diurnal cycles compared to an even

change in temperature over 24 hours but these broad global

mean temperature predictions obscure aspects critical to

natural and managed ecosystems.

The conservation and restoration of mangroves and

associated coastal ecosystems play important roles in climate

change adaptation strategies. Mangroves are not only

valuable in climate change mitigation efforts, but they are

also influential in adaptation to changing climates [9]. Due to

the affect mangroves have in adapting to climate change,

more investments should be funneled to its development

plans as climate change adaptation is a growing concern in

most international development agendas [7]. Thus, the

objective o

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