The comparison of bathymetric estimation from three high resolution satellite imagery

 

The Comparison of Bathymetric Estimation from Three High
Resolution Satellite Imagery
Samsul Bachri
Institute Technology of Bandung (ITB)

Muhammad Banda Selamat
Bogor Agricultural University (IPB)

Vincentius P Siregar
Hasanuddin University (UNHAS)

Sam Wouthuyzen
LIPI

ABSTRACT
This study was using three high resolution satellite imagery to estimate bathymetric condition at
shallow water coral reef environment around Pulau Panggang, Jakarta. The Worldview 2 supply 2
m spasial resolution with 8 spectral band, whereas Quickbird 2 produce 2.44 m spatial resolution in
4 spectral band and ALOS produce 10 m spasial resolution with also 4 spectral band. Red band of

ALOS and Quickbird have high correlation with sand depth and the lowest are blue bands. Among
this bands, Quickbird red band is the highest and its blue band is the lowest. Worldview visible
bands may have low sand depth correlation because of noise from ripple wave during acquisition.
This study shown that, Quickbird image is proven able to map water depth variation up to 8 metre
at reef flat and lagoon area of Panggang island, Jakarta with RMSe is 1.1 metre. The result also
shown an opportunity to implement this approach to bathymetric mapping of shallow water area at
remote small islands.

Keywords :bathymetric estimation, high resolution imagery

1

Introduction

Water depth (bathymetry) is an important
factor to solve various coastal studies such as
wave and current modelling, erosion, shoreline
stability, sedimen propagation, port construction,
thermal dispersion and maintenance of
navigation routes. Collecting bathymetric data

at a remote small islands are an expensive, time
consuming and sometimes extremely difficult to
conduct. For various reasons like wide area
coverage, data dependency on depth and
repetition, satellite images can be used to
determine shallow water depth on these sites.
Sometimes ground truth at selected locations is
still needed to validate the bathymetric model
produced by satellite imagery.
Depth water images acquired by remote
sensing satellites consist of reflectance from
water column and also atmosphere. Considering
the case of water bodies, there will be significant
change in the reflectance due to various
parameters including water depth, dissolved
matter and sea bed characteristics. Assuming the
other two parameters uniform, it is obvious that
the intensity of reflected electromagnetic energy
will vary inversely with water depth. However,
water depth variations are not easily

distinguished from bottom color differences.
Surface reflection effects add another element of
confusion to the interpretation of the images.

 

The recent satellite imaging development
promising a great challenge on this bathymetric
mapping. Considering a new spectral band
(ranging around ultraviolet to blue wave spectral
region - called “coastal” band) on worldview 2 it
hoping that visible satellite imaging may be use
as an alternative to bathymetric mapping works
on low to middle accuracy levels.
The main goal of this study is to evaluate
the ability of two high resolution satellite image
(eg Worldview and Quickbird) to on water
depth mapping. The evaluation will based on
depth penetration of visible bands of each
satellite.

2

Background Theories

Lyzenga (1978) studies on mapping water
depth conclude that the ratio algorithms for
water depth and bottom features mapping are
relatively simple and give acceptable results in
many situations. The ratio algorithm can be
develop to shallow water radiance model that
involves effects of scattering in the atmosphere,
reflection at the water surface as well as the
components originating in the water itself.
Jupp (1988) develop depth zones theories
based on a depth of penetration threshold for
each band. Threshold values are determined
from the maximum deep-water radiances, and for
Landsat TM only six water depth zones or depth
values can be derived. Although in some areas

 
dark substrates such as sea-grasses may be
misinterpreted as deep water, the technique is
probably the most reliable for navigation
purposes.
Bierwirth, et.al (1993) develop an
algorithm to derived both substrate reflectance
and water depth simultaneously. Their aim was
to derive substrate reflectance factors in each
band processed and, as a by-product, produce a
continuous grey-scale depth image. At that stage
of research, their assumed relatively clear water
and only minor variations in the concentration of
water column materials. The water attenuation
coefficients were determined by regressing
known bathymetric data against Landsat
radiances. They assume that water column
conditions were constant over the scene. The
method was successfully tested in the Hamelin

Pool area of Shark Bay, Western Australia. The
errors are greatest for dark substrates which will
resolve as deeper than true.
The studies on shallow water depth
mapping were done using Quickbird images
(Lyons et al. 2011), IKONOS (Stumpf et al. 2003;
Lyzenga et al. 2006), SPOT (Melsheimer & Liew
2001; Lafon et al. 2002; Kao et al. 2009) and
Landsat (Lyzenga 1981). The method used for
bathymetric mapping may classified into two
categories, empirical (Lyzenga 1978; Jupp 1988;
Lafon et al. 2002; Gao 2009) and analytic /
invertion (Dierssen et al. 2003; Su et al. 2008;
Dekker et al. 2011). The common band use were
blue and green band.
The fundamental principle behind using
remote sensing to map bathymetry is that
different wavelengths of light will penetrate
water to varying degrees. When light passes
through the water, it becomes attenuated by

interaction with water column. The intensity of
light, Id, remaining after passage length p
through water is formulated as:
= .
eq.1

I0= intensity of the incident light and
k= attenuation coefficient, which varies with
wavelength

if vertical pathway of light from surface to
bottom and back is assumed then p may be
substituted by the term of 2d. where d is water
depth. Then equation 1, may linierize by natural
logarithm:
=

−

eq.2

Red light has a higher attenuation coefficient
than green or blue, therefore it does not
penetrate further than a few centimeter. The
depth of penetration is depent on water turbidity.
Dissolved materials in water will affects the
depth of penetration because they scatter and
absorb light, and so increase attenuation.

 

According to Benny and Dawson (1983),
there are three assumptions to implement their
algorithm: i) light attenuation is an exponential
function of depth (equation 1), ii) water quality
(the attenuation coefficient, k) does not vary
within an image, iii) the color (reflective
properties or albedo) of the substrate is constant.
Assumption (ii) may or may not be valid for any
image but has to be made unless supplementary

field data are collected at the time of image
acquisition. Assumption (iii) is certainly not true
for many areas and will cause dense sea grass
beds to be interpreted as deep water.
Corrections to the final bathymetry chart could
be made if a habitat map exists.
Even
Jupp’s
method
had
same
assumptions as Benny and Dawson’s, but
actually he made quiet different step to map
water depth from satellite images. Jupp’s method
may implement by doing these steps : 1) the
calculating depth of penetration (DOP) zones, 2)
the interpolating depths within DOP zones, and
3) the calibrating depth within DOP zones.
Lyzenga’s method applies water column
correction to compensate the effect of variable

depth (bathymetry) from different substrate. a
transformation using natural logarithms will
linearise the effect of depth on bottom
reflectance. Theoretically, each bottom type
should be represented by a parallel line, the
gradient of which is the ratio of the attenuation
coefficients for each band ( / ). It may say, for
one of bottom type (e.g. sand), all pixels must lie
along the same regression line. Those pixels
further up the line have greater reflectance and
are found in shallower water. Those pixels
nearest the y-intercept are found in deeper water.
The y-intercept can be used as an index of
bottom type. Relative depth can be inferred by
the position of a pixel along a line of gradient
/ . Depth varies along the line so that the
shallowest (brightest) pixels have the highest
values, the deepest (darkest) pixels the lowest.
Once the gradient / is known, the axes of the
bi-plot can be rotated through the angle θ, so

that the new y-axis lies parallel to
/ .
Positions of pixels along this new y-axis are
indicative of depth.
Water depth calculated by an image is
depth beneath a temporary water surface. This
depth will depend on the height of the tide at the
time of satellite overpass. Field depth data will
also have been collected at different times of the
day, at different points in the tidal cycle. Image
and field depths must be unificated by reducing
to depth datum. This tidal datum is normally
calculated from the Lowest Astronomical Tide
(LAT) level (the lowest point that the tide ever
recedes to).
Similarly, the depth of water, z, measured
in the field with an echo-sounder is equal to the
depth below datum plus tidal height. The tidal

 
height for each depth recording, must therefore
be calculated and subtracted from the measured
depth to give the depth of water below datum.
Thus it is essential to record the time when each
calibration depth is measured so that it can be
corrected to datum later.

3

15. 2008

Table 2. Sensor characteristics of Worldview,
Quickbird and ALOS AVNIR 2 satellites
(modificated from Digital Globe, 2010
and JAEA, 2008)
Spectrum

Methodology

The data for this study were collecting at
Panggang island and its vicinity. The island may
reach by boating around half an hour heading to
the north from Jakarta. The equipments used
during survey (January, 2012) were:
1 unit GPS MAP Sounder (freq. 50 kHz
and 200 kHz)
1 unit Automatic Data Logger +
software
1 unit laptop core2 duo
1 unit boat with 5 HP outboard engines
1 unit tide pole
1 unit steel chain with rope for
transducer calibration
1 unit digital camera for documentation
Due to sea wave characteristics, some corrections
must be apply to water depth measured. These
corrections are: 1) equipment default correction,
this value obtained by transducer calibration, and
2) tide correction, which obtained by tidal
observation coincident with sounding work. The
relationship between depth measured, depth
corrected and its corrected values is shown in
Figure 1.

Figure 1.

AVNIR 2

Corrections to Depth Measured

Three different satellite images were use
for this study. The images description are shown
at Table 1 and 2. The visualization of natural
composite image from three satellites are shown
in Figure 2.

Wave length (nm)
Worldview 2

Quickbird 2

AVNIR 2

Coastal
Blue

400 - 450
450 - 510

430 - 545

Green

510 - 580

466 - 620

420 –
500
520 –
600

Yellow

585 - 625

Red
Red
Edge
Near IR
Near IR

630 690
705 745
770 895
860 1040

Bands

Worldview
2
Quickbird 2

8

Spatial
Resolution
2.07 m

4

2.44 m

ALOS

4

15 m

 

715 918

760 –
890

Digital Number data require either dark pixel
subtraction or some other form of atmospheric
correction. All infrared bands removed and land
areas masked out.
1) choose an area of deep water with properties
we believe to be typical for the area
2) Calculate the maximum, minimum and mean
deep water pixel for each band. Let the
minimum in band i be Li deep min, the maximum
Li deep max and the mean Li deep mean
3) if a pixel value in band i, Li, is > Li deep max
then some light in band i is being reflected
from the seabed to the sensor. The depth is
therefore less than the maximum depth of
penetration, denoted by zi for band i. If, for
the same pixel, Lj, is > Lj deep max , then the
depth of that pixel is between zi and zij.
4) a few error pixels will have higher values in
some band, which should not happen in
theory. They may be coded to zero and
filtered out of the final depth image.

Acquisition
October 19,
2011
September
28. 2008
September

610 –
690

Creating Depth of Penetration (DOP)
Zones (Jupp, 1988)

Table 1. Satellite images used in this
study
Satellite

590 710

(a)

 
=

−

eq. 5

Calibration of DOP zones
1) Depth data typically consist of echo sounder
readings at a series of positions. Calculate
which sites lie within each DOP and plot
frequency distribution histograms of known
depths in each DOP
2) Jupp indicates that the point of intersection
between histograms is the best decision
value for the depth separating each DOP
zone.
3) new values of Zj, ki and Ai are calculated and
equation 5 written to assign depths to each
pixel in each DOP

(b)

Accuracy Assessment
(c)
Figure 2. Natural composite images of study
area: a) ALOS AVNIR, b) Quickbird 2
and c) Worldview 2

4

Interpolating DOP Zones
1) DOP images then may be used to make DOP
zone masks for all bands. All pixels within
DOP zone 1 coded to a value of 1 and all
other pixels in the image to 0, and repeating
with other DOP zones.
2) Multiply the original image by each DOP
zone masks. Data in pixels outside the DOP
zone will be recorded to 0.
3) Estimate Li max and Li min for each DOP zone i.
Xi min and Xi max can then be calculated since
Lideepmean is known. The Ai can then be
calculated from equation 3 and 4.
−
=
eq. 3
−
=

+

eq. 4

4) Using equation 5 to assign depth for each
pixel in each DOP. This will produces
separate interpolated DOP depth images.
These are added together to produce a depth
image for the area of interest.

 

Simple regression between depth pair of
data could be implement to estimate how
accurate this method in water depth mapping.
The regression equation also will portray the
level of confidence of the final bathymetric map
for area of interest.

Result and Discussion

Geomorphic zonation at coral reef
environment usually associated to depth profile.
Hence it presentation is spatially easy to detect
by moderate satellite resolution such Landsat,
SPOT and ASTER. According to Mumby and
Harborne (1999) geomorphic zone has clear
boundary between them due to depth differences
so it is easy to identified by using visible band
combination from satellite images. Blanchon
(2011) could recognize reef flat, reef lagoon, reef
front and reef slope from high resolution
Quickbird satellite image.
The crossectional and top view of coral
reef environment at Panggang island is shown at
Figure 3. The water depth profile is provided by
echo sounding and already reduced to tidal
datum. From this figure we could recognize
some geomorphic zonation, such as reef crest,
reef flat and lagoon. Note the lagoon is almost 15
metre depth, whereas reef flat depth is only
around 1 to 2 metre.

 

Figure 2. Geomorphic zonation of Panggang reef waters
It is obvious that bottom substrate like
Red band of ALOS and Quickbird have
sand have good relationship with depth variation.
high correlation with sand depth and the lowest
Common substrates in reef environment are
are blue bands. Among this bands, Quickbird red
sand, seagrasses and coral reef. We evaluate
band is the highest and its blue band is the
sand relationship with waterdepth by extracting
lowest.
From this fact we may get a brief
its correspondence digital value from ALOS,
description that if use Jupp’s algorithm to predict
Quickbird and worldview images. Figure 3
bathymetry from ALOS images, we may have
shows us that, even Worldview has great spatial
three DOP (depth penetration zone) because its
resolution compare to ALOS and Quickbird, but
three bands have good relationship with sand
in this case
it has very low coefficient
depth. Meanwhile, if use Quickbird image, we
determination hence not representative to
only have two DOP wich are from green and red
bathymetric image processing.
bands only.

 

 

Figure 3. Digital number comparison of sand depth from band 1, 2 and 3 of ALOS
(a, b, c), Quickbird (d, e, f) and Worldview (g, h, i) respectively
We re-evaluate worldview image due its
low sand depth correlation value and found that
the image also record ripple wave during
acquisition. So this noise may affected every
digital number of visible bands we use and
contribute to low value of sand depth correlation.
Considering to sand depth correlation
values, we decide to use Quickbird image to
produce bathymetric image by implement Jupp’s
algorithm. The Jupp’s algorithm paremeters are
shown at Table 2. The DOP (depth penetration
values) of band 2 is actually acting as boundary
level for depth more than 2 metre, whereas DOP
of band 3 was use for delineating depth area less
than 2 metre. Ki and Ai coefficient are needed to
solve depth estimation by using equation 5. The
result of Jupp’s algorithm implementation is
shown in Figure 5.

 

Table 2. Summary of Jupp Parameters for
Quickbird image
band
Parameters
2
3
DOP 2

42 - 53

DOP 3
Parameters

8 - 131
band
2

3

ki

0.114536

0.034657

Ai

5.045528

1.386294

 

Figure 5. Bathymetric image from Quickbird

Figure 6. Tracing bathymetric contour from Quickbird bathymetric image
data set. This means if we get a value say 2
To measure the accuracy of this
meter from bathymetric image, then we should
bathymetric map, some point was carried out on
note that the real value maybe around 1 to 3
both field depth values and bathymetric image.
meters depth. The predicted water depth profile
The pair of depth values then plotted in to
shown in Figure 7b, where it gives a more clear
cartesian diagram to get a general formulation of
explanation about the accuracy of bathymetric
the regression. The determination coefficient
image. The root mean square error (RMSe) for
describes the reliability of the model, the bigger
each pair of water depth (image and field) is
the value the more reliable is (Figure 7a).
around 1.1 metre for a maximum 9 metre depth.
In statistical view, this model is able to
describe almost 78 percent of any values given in

(a)

(b)

Figure 7.
The final product from Jupp’s algorithm is
this methodology can be very valuable for
not just bathymetric image as shown in Figure 5.
bathymetric mapping especially in surf zone area
By draping its raster image to bathymetric
where conventional method is hard to
countour (Figure 6) then we get some kind of
implement.
digital bathymetric terrain model (Figure 8). So
then we may say that for the sake of simplicity,

 

 

Figure 8. Digital bathymetric terrain model of Panggang island

5

Conclusion

In clear shallow water coral reef areas (e.g
remote small island), the optic sensor of satellite
imagery promising an opportunities as a source
of bathymetric mapping technology. This study
shown that, Quickbird image is proven able to
map water depth variation up to 9 metre at reef
flat and lagoon area of Panggang island, Jakarta.
Eventough the RMSe is 1.1 metre, but the potray
of bathymetric terrain may give a valuable
information for some application such as sea
current modelling, predicting fish juvenil
migration along seagrass and coral reef habitat.
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Sea-Floor Reflectance and Water Depth
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Blanchon P. 2011. Geomorphic zonation. Di dalam:
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Dierssen HM, Zimmerman RC, Leathers RA, Downes
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0

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2008

SEMINAR PROCEEDING
International Seminar and Workshop on Hydrography

Roles of Hydrography in Marine
Industry and Resources Management

Batam Island, 27-29 August 2013

Committee
Steering Committee
Head of Geospatial Information Agency, Dr. Asep Karsidi, MSc
Head of National Land Agency, Hendarman Supandji, S.H., M.H., C.N.
Head of Hydro-Oceanographic Office, Laksma TNI Aan Kurnia, SSos
Head of Indonesian Surveyor Association, Ir. Budhy Andono Soenhadi, MCP
Head of Indonesian Hydrographic Society, Prof. Dr.-Ing. Sjamsir Mira

Reviewer and Scientific Committee
Prof. Dr. Widyo Nugroho SULASDI (Bandung Institute of Technology)
Prof. Dr. Hasanuddin Z. Abidin (Bandung Institute of Technology)
Prof. Dr. Razali Mahmud (University of Technology Malaysia-Malaysia)
Prof. Dr.-Ing. Delf Egge (Hafen City University, Hamburg, Germany)

Organizing Committee
Chair
Co-chair
Finance
Secretary
Co-secretary

:
:
:
:
:

Dr. Ir. Samsul Bachri, M.Eng
Ir. Tri Patmasari, MSi
Sylvia Nayoan
Ir. Nanang Henky Suharto
Wiria Indraswari, SE

Sponsorship
Publication
Security and Permit

:
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:

Ir. Fuad Fachrudin
Ir. Syartoni Kamaruddin
Kol. Laut Daryanto
Letkol. Laut Nurriyadi

Coordinator of Seminar
Publication

:
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Dr.rer.nat. Wiwin Windupranata, ST., MSi
Agung Pandi Nugroho, ST.
Sella Lestari, ST, MT
Auzan Kasyfu Ambara
Intan Hayatiningsih, ST, MSc
Alifiya Ikhsani
Apriliyana

Design
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:
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Coordinator of Exhibition

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Renny Rachmalia, ST.

Coordinator of Workshop
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Kol. Laut. Trismadi
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iii

Organizer and Sponsor
Main Organizer
Indonesian Surveyor Association, Ikatan Surveyor Indonesia (ISI)
Indonesian Hydrographic Society, Masyarakat Hidrografi Indonesia (MHI)
Geospatial Information Agency, Badan Informasi Geospasial (BIG)
National Land Agency, Badan Pertanahan Nasional (BPN)
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Co-Organizer
Bandung Institute of Technology, Institut Teknologi Bandung (ITB)
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Gold Sponsor

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iv

Dear Hydrographers and Distinguished Guests,
It is my great pleasure to have this opportunity to welcome many participations from countries all over the
world. I am very pleased to be grateful for all of you to the International seminar and Workshop on
Hydrography on behalf of the organising committe and all those who have constributed to this Seminar and
workshop.
It was December 2012, when the Indonesian Surveyor Association (ISI) and Indonesian Hydrographic Society
(MHI) began to initiate the first International Hydrography Seminar in Indonesia, since then the various
preparations for the Seminar have progressed steadily, especially through the hard work of the Organising
committee.
The objective this seminar is to share and perceive the development of science, technology as well as human
resources on hydrography in the world. Futhermore, workshop is intended to develop the capacity of human
resources on the ability of Hydrography.
Our Seminar’s theme : “ the roles of Hydrography for marine Industry “ was selected partly due to the
significant important for Indonesia which is an Archipelagic country, and has abundant marine resources.
I am sure that our Seminar and Workshop will constribute to a substantial progress in approaching the goals
of sustainable development marine Industry in the local and global scale, one of the central problems of
contemporary hydrography.
This event is organized by ISI and MHI incorporate with Geospatial Information Agency (BIG), HydroOceanographic Office (DISHIDROS), Bandung Institute of Technology (ITB) and National Land Agency
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We sincerely this Seminar and workshop will be a forum for productive discussions and learning by all
participations.
With the great success of seninar and workshop on Hydrography 2013, I sincerely wish that you have an
enjoyable stay in Batam of Riau Islands Province and have nice time in this wonderful country

Samsul Bachri,
Chair of the Organising Committee

v

Dear All Participans,
First of all, I would like to thank to the Mighty God, Allah SWT and all supporting organizations and
institutions which make this INTERNATIONAL SEMINAR AND WORKSHOP ON HYDROGRAPHY
(ISWH 2013) happen. The event is organized by Indonesian Surveyor Association (ISI) and Indonesian
Hydrographic Society (MHI) together with Geospatial Information Agency (BIG), Hydro-Oceanographic
Office (DISHIDROS), Bandung Institute of Technology and National Land Agency (BPN). It is an honour for
ISI and MHI to organize the first event of hydrographic-related seminar in Indonesia. The seminar is intended
to identify development of science, technology as well as human resources in hydrography in the world,
particularly Indonesia and ASEAN region to support sustainable development planning and maritime
industry.
As it is defined by International Hydrographic Organization (IHO), hydrography is the branch of science
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dynamics of water bodies. Hydrography plays an important role in any aspect of maritime and coastal
development. It is related to basic knowledge of the geographical, geological and geophysical features of the
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Hydrography is the key to progress on all maritime activities, normally of great national economic
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defence and security, tsunami flood and inundation modelling, coastal zone management, tourism and marine
science.
Indonesia, with 17,508 islands, 81,000 km of coastline, and 3.1 million km2 of maritime area is the largest
archipelagic country in the world. Based on the United Nations Convention on the Law of the Sea 1982,
Indonesia has a sovereign right to utilize and manage the Exclusive Economic Zone (EEZ) as large as 2.7
million km2. Its coastal and marine area has a huge number of both renewable as well as unrenewable
resources. In order to utilize and manage the marine and coastal resources properly, it is required to have an
appropriate geospatial data infrastructure for planning, execution, and evaluation, which are regulated by law
and public policy.
Bathymetry, seabed features, as well the currents, tides and certain physical properties of the sea water are
types of marine and coastal geospatial information. Related to the Geospatial Information, Indonesian
Government has produced a National Law Nr. 4/2011 about Geospatial Information to assure availability of
and access to responsible and accurate geospatial information as well as to establish expediency of those
geospatial information.
As the official Geospatial Information Agency in Indonesia, Geospatial Information Agency (Badan Informasi
Geospasial-BIG) has deliver a National Act Planning through an inter-governmental agencies and
departments coordination meeting to support efficient and effective spatial decision support system for
national sustainable development planning.
In July 2002, the revised Chapter V of the IMO Safety of Life at Sea (SOLAS) Convention entered into force.
Under the new Regulation 9, the Contracting Governments of SOLAS are now required to provide and
maintain Hydrographic Services and products.
Many charts which were adequate a decade ago, may have to be recompiled using new survey data, collected
to a higher degree of accuracy and providing improved coverage. This deficiency may not be limited to
sparsely surveyed waters of developing nations, but may also apply to the coastal waters of major industrial
states. The advent of accurate satellite navigation, has made poorly positioned historical data an even greater
problem for navigators. Fortunately, new survey technologies have improved the precision to which modern
hydrographic surveys can be conducted.
Hydro-Oceanographic Office (DISHIDROS) is IHO member and representative office in Indonesia since 18
October 1951 who is responsible and the only institution to produce nautical chart for ship navigation in
Indonesia. It has missions to support surface and underwater information for national security and military
purpose, to increase product quality based on international standards and rules to ensure ship navigation
safety, to contribute to marine environmental protection and maritime boundary delineation, to maintain up to
date, high quality and integrated hydro-oceanographic information.

vi

Indonesian Surveyor Association (ISI) is a professional organization for surveyors which was established on
27 June 1972. It has a long history on supporting geodetic, surveying, mapping and geospatial information
projects in Indonesia. ISI was created based on the same vision of surveying and mapping experts to place the
human resources development as the key component for development of geospatial information science and
technology. Since 2008, Indonesian’s hydrographer society created an official organization to support
hydrographic science and technology development as well as an exchange and discussion media for all
hydrographic survey experts and companies in Indonesia. This organization was initiated by Prof. Dr. Ing.
Sjamsir Mira and is named as Masyarakat Hidrografi Indonesia (MHI) or Indonesian Hydrographic Society.
Finally, I would like to great all participants of ISWH2013. Citing the Indonesian Navy motto, Jalesveva
Jayamahe, ON THE SEA WE ARE GLORIOUS, I wish you to have a very nice seminar and workshop event
Cibinong, 17 August 2013
Head of Indonesian Surveyor Association
Ir. Budhy Andono Soenhadi, MCP

vii

TABLE OF CONTENTS
Page
Ship Detection based on Synthetic Aperture Radar Technique

Agustan
Rubby Sidik Agustino

1

Mapping of Coastal Vulnerability Index on Coastal Erotion In The
Perspective of Eeconomy (Study Area: Kecamatan Muara Gembong,
Kabupaten Bekasi)

Aldila Pradhana, S.T.
Dr. rer. nat. Wiwin
Windupranata, M.Si.
Dr. Ir. Dwi Wisayantono, M.T.

9

The Spatio Temporal Dynamic of Diffuse Attenuation Coefficient In
The Tropical Berau Estuary, East Kalimantan Indonesia

Wiwin Ambarwulan
Widiatmaka

21

Mapping Multi Coastlines With Multi-Tidal Imageries

Fahmi Amhar
Habib Subagio
Tri Patmasari

29

Identification Problem of Marine Cadastrein Indonesian Archipelagic
Perspective

Yackob Astor
Widyo Nugroho SULASDI
S. Hendriatiningsih
Dwi Wisayantono

33

The Comparison of Bathymetric Estimation from Three High
Resolution Satellite Imagery

Samsul Bachri
Muhammad Banda Selamat
Vincentius P Siregar
Sam Wouthuyzen

43

The Progression of Multi-Dimensional Water Column Analysis in a
Processing Environment

Corey M. Collins
Andrew Hoggarth
Matthew Holland

51

Variability of Sea Surface Temperature and Sea Surface Salinity in the
Ambon Bay and its Relation to ENSO/IOD and Monsoon

Corry Corvianawatie*
Mutiara Rachmat Putri
Sri Yudawati Cahyarini
Willem Merpy Tatipatta

55

The Calculation of Erosion and Sedimentation Rate in Coastal Zone
Using Satellite Imageries (Case Study: Kecamatan Muara Gembong,
Kabupaten Bekasi, West Java)

Dianlisa Ekaputri, S.T.
Dr. rer. nat. Wiwin
Windupranata, M.Si.
Dr. Agung Budi Harto, M.Sc.

61

Reconstructing Disrupted Water Level Records in A Tide
Dominated Region Using Data Mining Technique

Hidayat
Fajar Setiawan
Unggul Handoko

71

Initiative on Implementation of 3D Cadstre In Indonesia

Sri Karina, ST, DEA
Deni Santo, ST
Dr. Trias Aditya
Dr. Eka Djunarsjah, MT

77

Geomatics Roles In Capacity Building For Hydrographic Mapping at
Prigi Beach

Khomsin
Yuwono
Akbar Kurniawan

89

The Coastal Platform Morphodynamics Characteristics Belang Bay,
North Sulawesi Province

Joyce Christian Kumaat
Sontje Tonly Boy Kandoli
Agnes Tenly Moningkey

93

Evaluation of Warm Water (thermal) dispersion using a numerical
model at the Binceta Coast (North Sulawesi) in PLTU Development

Mahatma Lanuru

97

RV Baruna Jaya Marine Data Processing and Information
Management

Imam Mudita
Fineza Ilova
Ratna Juwita

107

Study On The Other Possible Applications of The Aavailable Tie
Points of The Basepoints In Indonesia

Rorim Panday
Sri Handoyo

117

ix

Natural to anthropogenic influence of environmental change of
Jakarta Bay: seismic reflection and sediment coring studies

Haryadi Permana
Rina Zuraida
Susilohadi
Kresna Tri Dewi
Nugroho Dwi Hananto
Mustaba Ari. Suryoko
Nazar Nurdin
Eko Saputro
Adi C. Sinaga
Septriono Hary. Nugroho

125

Marine Geoscientific Survey for Possible Extend of Indonesia Legal
Continental Shelf Beyond 200 M at North Papua – Indonesia :
A Preliminary Results

Catur Purwanto
Nugroho D. Hananto
Mustafa Hanafi
Hersenanto C. Widi
Rahadian
Rainer A. Troa
Tumpal Bernhard
Bisma J. Zakaria
Ronald D. Michel
Andi Wisnu
LKI 2013 Expedition Team

131

20071Pseudo 3D Sesmic Methods Using 2D Seismic Multichannel
Data Taken From Offshore Karawang, West Java

Trevi Jayanti Puspasari, SSi
Dr. Udrekh
Sumirah, S.Si

135

Study The Changes of SSH Value Using Altimetry Satellite In The
NKRI’S Outermost Islands
(Case Study: Fani Island)

Dika Ayu Safitri
Muhammad Taufik
Yuwono

139

The Study of Sea Bottom Morphology and Bathymetric Mapping
Using Worldview-2 Imagery

Iwan E. Setiawan
Doddy M. Yuwono
Vincentius P. Siregar
Gatot H. Pramono

143

People and The Environmental Change: Impact and Aadaption
Model

Dewayany Sutrisno

151

Designing of Decission Support System For Maritime Boundary
Management In South China Sea

Trismadi
S. Sutisna
K.B. Seminar
Machfud

159

Hydrodynamic Condition of Kapuas Kecil River, Pontianak Based On
Simulation Model

Iswiati Utamiputeri
Mutiara Rachmat Putri
Zainal Arifin

171

x