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Developing a near-seamless tidal datum by integrating tidal
and satellite altimetry data with a Digital Elevation Model for
maritime boundary delimitation
Mohd Faizuddin Abd Rahman
a
, Ami Hassan Md Din
a,b
, Mohammad Hanif Hamden
a
,
Mohd Razali Mahmud
a
and Abd Wahid Rasib
a
a
Geospatial Imaging and Information Research Group (G12RG), Faculty of Built Environment and Surveying,
Universiti Teknologi Malaysia, Skudai, Johor, Malaysia;
b
Geoscience and Digital Earth Centre (INSTeG),
Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
ABSTRACT
The delimitation of maritime boundaries plays a signicant role in
preserving the country’s sovereignty and jurisdiction. The maritime
baseline was established based on the combination of maritime
basepoints, which represents the Lowest Astronomical Tide (LAT)
along the coast. However, the current approach still relies on the
limited and sparsely distributed tide gauge stations for the deter-
mination of LAT. Therefore, this study aims to develop the
Peninsular Malaysia Near-Seamless Tidal Datum (PMNSTD) by inte-
grating tide gauge, satellite altimetry, and Tide Model Driver (TMD)
data. PMNSTD was further integrated with Digital Elevation Models
(DEM) for the delimitation of maritime boundaries. This study
methodology includes data acquisitions of 12 tide gauge stations
along the coast of Peninsular Malaysia, satellite altimetry data for
TOPEX, Jason-1, Jason-2, and GEOSAT Follow-On (GFO) from Radar
Altimeter Database System (RADS), TMD, and TerraSAR-X add on for
Digital Elevation Measurement 30 m (TanDEM-X) data. The tide
gauge, satellite altimetry, and TMD data encompass 23 years of
tidal observation data from 1993 to 2015. For the derivation of
the tidal datum, the tide gauge and satellite altimetry data were
analysed using harmonic analysis in UTide, whereas, for the TMD
data, the tidal datum was determined based on tidal prediction. For
compatibility in data integration, the derived Lowest and Highest
Astronomical Tide (LAT and HAT) from tide gauge, satellite altime-
try, and TMD data were referenced to the Mean Sea Level (MSL),
denoted as LATmsland HATmsl respectively. Next, the LATmsland HATmsl
was interpolated using Inverse Distance Weighting (IDW) to
develop the PMNSTD (LATmsland HATmsl ) using ArcGIS. The statistical
assessment indicates that the PMNSTD (LATmsl and HATmsl) estab-
lished from the integration of tide gauge, satellite altimetry, and
TMD has a better agreement with the Department of Survey and
Mapping Malaysia (DSMM) tide gauges with a Root Mean Square
Error (RMSE) and Standard Deviation (STD) of 0.228 m and 0.175 m
for LATmsl, as well as 0.159 m and 0.079 m for HATmsl. Next, the
ARTICLE HISTORY
Received 31 March 2023
Revised 7 July 2023
Accepted 1 August 2023
KEYWORDS
Tide gauge; satellite
altimeter; tide model driver;
LAT; MSL; HAT; PMNSTD;
LAT
msl
; HAT
msl
; TanDEM-X
CONTACT Mohd Faizuddin Abd Rahman mfaizuddin4@live.utm.my; Ami Hassan Md Din amihassan@utm.my
Geospatial Imaging and Information Research Group (G12RG), Faculty of Built Environment and Surveying, Universiti
Teknologi Malaysia, Skudai, Johor 81310, Malaysia
INTERNATIONAL JOURNAL OF REMOTE SENSING
https://doi.org/10.1080/01431161.2023.2248562
© 2023 Universiti Teknologi Malaysia
PMNSTD (LATmsl) was integrated with TanDEM-X using ArcGIS and
SURFER for the delimitation of maritime boundaries. The reliability
assessment illustrated a signicant improvement in the continua-
tion of 201 maritime basepoints in comparison to the 95 maritime
basepoints by the DSMM. In conclusion, the proposed approach has
shown a continuous, consistent, and wider establishment of the
country’s maritime baseline for the Peninsular Malaysia region.
1. Introduction
Traditionally, data from the tide gauge station were used to establish a localized tidal
datum such as the Lowest Astronomical Tide (LAT), Mean Sea Level (MSL), and Highest
Astronomical Tide (HAT) along the coast. Recently, with the advancement of the Global
Navigation Satellite System (GNSS) for real-time positioning and satellite altimeter for
bathymetry derivation, there has been a signicant improvement in hydrographic survey-
ing technique (Chénier, Abado, and Martin 2018; Dodd and Mills 2011; Hamden and Din
2018). Such advancement hence leads to the development of a continuous tidal datum
along the coast by integrating the tide gauge and satellite altimetry data for bathymetry
determination, as well as GNSS for positioning, in which all the derivation of tidal datum
will refer to a similar local reference surface such as the MSL, or the global reference
surface, for example, the World Geodetic System 1984 (WGS84) ellipsoid, respectively
(Dodd and Mills 2012; Elhassan 2015).
The satellite altimeter has been evolving since 1975 and currently, there are a total of
13 satellite missions that have been operating from 1985 to 2022 such as TOPEX/
Poseidon, Jason-1, Jason-2, Jason-3, GEOSAT Follow On (GFO), ERS-1, ERS-2, ENVISAT-1,
Cryosat-2, SARAL, and Sentinel-3A and Sentinel-6 (Li et al. 2022; Nab et al. 2023).
Accordingly, a satellite altimeter has three long-term scientic objectives which are
observing the circulation of the global oceans, monitoring the volume of the polar ice
plate and observing the variation in the sea level globally and locally (Abdullah et al. 2016;
Hamlington et al. 2019; Idris, Deng, and Andersen 2014). Hence, due to their vast coverage
for data acquisition, satellite altimeter has been considered as an additional approach in
monitoring regional sea levels (Falck, Tomasella, and Papa 2021).
The integration of the tidal datum and Digital Elevation Model (DEM) started back in
2009, through the development of the Bringing Land and Sea Together (BLAST) project by
the European Union as part of the Interreg North Sea Region Programme (Verfaillie et al.
2012). The BLAST project took around 3 years, starting in 2009, and was nally completed
in 2012. Its establishment comprises a collaboration between 17 partners from seven
countries, including governmental organizations, universities, and private companies (Els
et al. 2011). The ideas of the establishment of BLAST are to unite the land and sea datum
by referring the vertical and horizontal data to a similar reference surface such as the
Geodetic Reference System 1980 (GRS80) or WGS84 ellipsoid which is accessible any-
where through the GNSS observation (Els et al. 2011; Wolden 2010). A similar study was
also conducted by (Rahibulsadri et al. 2014) which uses the integration of the LAT, the
topographic and bathymetric Light Detection and Ranging (LIDAR), and satellite imagery
from SPOT-5 as a reference datum in the establishment of a marine cadastre for the
2M. F. ABD RAHMAN ET AL.
Malaysian region. In addition, there is also a study by (Dewi et al. 2022) that developed the
Digital Elevation Bathymetry Model (DEBM) which consists of tide gauge station,
Indonesian National Bathymetry Data (INBD), Single Beam Echosounder (SBES), Satellite-
Derived Bathymetry (SDB), and National Digital Elevation Model (DEMNAS) data. The
establishment of DEBM is to update the position of maritime basepoints and baselines
for maritime boundary delimitation, especially for the area with a lack of tidal datum
information (Dewi et al. 2022).
The delimitation of maritime boundaries plays a signicant role in preserving the
sovereignty and jurisdiction of coastal states (Kastrisios and Tsoulosa 2017). Its determina-
tion will justify the country’s rights, allowing the coastal states to prevent any illegal
infringements and trespassing by foreign vessels (Hasan et al. 2019; Qiu and Firestone
2020). The maritime baseline is established through the combination of basepoints along
the coast that signies the LAT for the area (Abd Rahman 2018). The United Nations
Convention on the Law of the Sea (UNCLOS) has established several maritime zones
applicable to all coastal states with their respective distances from the coast (Ahmed 2017;
Friedman 2021; Jagota 2021). In Malaysia, there are recent incidents related to the
country’s maritime zone infringement. For example, during China’s aggressive action in
deploying their military in the Sabah and Sarawak coastal region (Aida 2022) and the
dispute between Malaysia and Singapore in which a Malaysian sherman was chased
away by Singapore Police Force (SPF) when they claimed that the Malaysian sherman has
trespassed their maritime boundary (Noh 2022).
Hence, this study focuses on developing a Peninsular Malaysia Near-Seamless Tidal
Datum (PMNSTD) along the coast which comprises an integration derived tidal datum
(LAT and HAT) from tide gauge, satellite altimetry, and Tide Model Driver (TMD) data with
respect to (w.r.t.) MSL denoted as LATmsl and HATmsl . The PMNSTD (LATmsl) was then
further integrated with the TanDEM-X for the delimitation of maritime boundaries. The
following data integration to establish the PMNSTD (LATmsl) and its integration with
TanDEM-X is capable of improving the current conventional approach of only using tide
gauge stations for the determination of the country’s maritime basepoint. Furthermore,
its development is expected to align with two of the United Nations (UN) Sustainable
Development Goals (SDGs) number 9 and 14, which emphasizes building resilient infra-
structure, promoting inclusive and sustainable industrialization as well as fostering inno-
vation, and striving for conserving and sustaining the use of the oceans, seas, and marine
resources for sustainable development, respectively.
2. Problem statements
Changes in sea level along the coast have been monitored using tide gauge stations over
the last 38 years. Currently, there are 19 continuously operating DSMM tide gauges in
Malaysia. Accordingly, Malaysia has a maritime area of 55,629 km2 compared to 329,960
km2 of the land area (NHC 2016; Said 2018). Hence, by only relying on 19 tide gauge
stations to monitor the variation of sea level along 55,629 km2 Malaysian’s coast is
insucient as there will be an area without any tidal datum information due to its location
situated far from the tide gauge stations. According to (Parvazi et al. 2015), the tidal
datum is only applicable in coastal regions near the tide gauge stations. In addition, it is
INTERNATIONAL JOURNAL OF REMOTE SENSING 3
barely accurate in oshore locations in which the distance is more than 10 km away from
tide gauge stations (Parvazi et al. 2015). Hence, it is really important to have a system of
sea-level information that is continuous and also accurate both spatially and temporally.
Thus, integrating the tide gauge, satellite altimetry, and TMD data can lead to a consistent
and continuous network of tidal datum information along the coast of Malaysia.
In relation to the development of continuous tidal datum using geodetic-based
approaches, many countries have begun to develop their continuous tidal datum for
their respective regions. It started with the Bathymetry with reference to the Ellipsoid
(BATHYELLI) by France in 2005 (Pineau-Guillou 2009; Pineau-Guillou and Dorst 2013),
Vertical Oshore Reference Frame (VORF) by the collaboration between the United
Kingdom and Ireland in 2009 (Ilie et al. 2013), Continuous Vertical Datum for Canadian
Water (CVDCW) by Canada in 2010 (Robin et al. 2014, 2016), Netherlands Vertical
Reference Frame (NEVREF) by the joint eorts between the Netherlands and Belgium in
2018, Saudi Continuous Chart Datum (SCCD) by the Kingdom of Saudi Arabia in 2019 (El-
Diasty, Al-Harbi, and Pagiatakis 2019) and Malaysia Vertical Separation Model (MyVSEP) by
(Hamden 2022). Despite the previous model for continuous tidal datum yielding an
acceptable result in terms of vertical and horizontal accuracy, there are still several
limitations that can further be improvised in the upcoming future.
The rst issue is regarding the utilization of an insucient number of tide gauge
stations that are sparsely located along the coast (Pineau-Guillou 2009; Pineau-Guillou
and Dorst 2013; Slobbe, Klees, and Gunter 2014). Since the characteristic of the tide is site-
specic, approximately within tens of kilometres, resulting in an inaccurate tidal datum
determination for the area situated further from the tide gauge stations (Parvazi et al.
2015). Moreover, only depending on the extrapolation of tidal datum using a limited
number of tide gauges is still insucient to produce an accurate tidal datum. Such is due
to the propagation of errors during the extrapolation process from a limited and sparsely
distributed known point, which will further continue to increase as the distances increase
(Li et al. 2022). The second issue is regarding the reference surface for the integration of
the derived tidal datum (Hamden 2022). Accordingly, the derived tidal datum from the
tide gauge refers to the zero-tide gauge. On the other hand, the derived tidal datum from
satellite altimetry refers to the TOPEX ellipsoid for the TOPEX class satellite mission, or the
WGS84 ellipsoid for the ERS-class satellite mission (Cipollini et al. 2017). Hence, to develop
a consistent and near-seamless tidal datum based on the integration between the tide
gauge, satellite altimetry, and TMD data, the derived tidal datum must be referenced to
a similar reference surface. Such can be accomplished by either referring the derived tidal
datum to a global reference surface, such as the WGS84 or GRS80 ellipsoid, or a local
reference surface, such as the MSL (El-Diasty, Al-Harbi, and Pagiatakis 2019; Hamden 2022;
Slobbe, Klees, and Gunter 2014).
The third issue is regarding the integration of a tidal datum with the coastal DEM for
only one single location (Dewi et al. 2022; Rahibulsadri et al. 2014). According to (Keysers,
Quadros, and Collier 2015), DEM data are often collected in relation to geometric or
physical height systems. On the other hand, the tidal datum comprised the Lowest
Astronomical Tide (LAT), MSL, or the Highest Astronomical Tide (HAT) was referenced to
the zero-tide gauge (Lee et al. 2017; Yu and Gao 2017). Such discrepancies result in
inconsistencies between the tidal datum and the elevation from the DEM, making it more
dicult to integrate both datasets. Hence, a solution that can eciently connect the
4M. F. ABD RAHMAN ET AL.
elevations of all correlated vertical reference surfaces for the tidal datum and the DEM is
known as vertical datum unication (Ihde et al. 2017). Moreover, for a consistent and
reliable integration between the tidal datum and the coastal DEM, the study should be
conducted along the country’s coastal line (Muslim and Foody 2008). Accordingly, bring-
ing the tidal datum and coastal DEM together will create a new and innovative solution
for the harmonization of land and sea data (Nahavandchi and Sjoberg 1998). Furthermore,
its integration will also improve maritime safety, coastal zone management, and future
planning in the context of climate change. Hence, the approach of integrating the derived
tidal datum from tide gauge stations and satellite altimetry with the coastal DEM should
be conducted in the upcoming future via vertical datum unication and applied to the
delimitation of maritime boundaries (Amjadiparvar, Rangelova, and Sideris 2016; Sánchez
and Sideris 2017).
The fourth issue is an improper delimitation of maritime boundaries in the current
approach. Accordingly, the determination of 158 maritime basepoints for Malaysia was
still questionable as there is no justication for its period of observational data for
determining the LAT (DSMM 2022). In addition, it is impossible to establish 158 maritime
basepoints along the coast of Malaysia based just only on the sparsely distributed 19
DSMM tide gauge stations. Therefore, a proper delimitation with a known location for
tidal observation, as well as a sucient period of tidal observation (at least 18.6 years) is
essential as it can contribute to the valid and legal rights and claims of the coastal states
(Hasan, Karim, and Maulud 2008). Otherwise, it might lead to maritime disputes between
states, for example, in terms of overlapping claims between two or more countries (Hasan
et al. 2019; Qiu and Firestone 2020). Several cases that occurred in Malaysia in the
previous years include the maritime delimitation at Batu Puteh Island in 2008 (Ong and
Perono Cacciafoco 2022) and the maritime delimitation at Sipadan and Ligitan Islands in
2002 (Zukri, Victoria, and Apriliyanto 2019). Besides, there is also the ongoing overlapping
claim in the South China Sea (SCS), especially in the Spratly Island, which involves the
conict between six countries: Malaysia, China, Vietnam, the Philippines, Taiwan, and
Brunei (Regilme 2018). The incident shows the importance of the establishment of a valid
country’s maritime baseline [55][56].
Accordingly, on the 27th of July 2022, through the collaboration of the Prime Minister’s
Department, Attorney General, Department of Surveying and Mapping Department
Malaysia (DSMM), National Hydrographic Center (NHC), Royal Malaysian Navy (RMN),
and Department of Minerals and Geosciences Malaysia (DMGM) has successfully sub-
mitted 158 maritime basepoints to the Division for Ocean Aairs and the Law of the Sea
(DOALOS) and the United Nations (UN). It comprises 95 basepoints in Peninsular Malaysia,
16 basepoints in Sarawak, and 47 basepoints in Sabah as shown in Figure 1 (DSMM 2022).
The interconnection of all 158 maritime basepoints serves as the maritime boundary for
the Malaysia region.
Thus, based on all the previous and current issues involving the approach in
establishing a continuous tidal datum based on tide gauge and satellite altimetry, as
well as the importance of a proper maritime boundary delimitation, this study aims
at developing the PMNSTD (LATmsl and HATmsl) using tide gauge, satellite altimetry,
and TMD data. Its integration aims at establishing a near-seamless tidal datum
surface along the coast of Peninsular Malaysia, especially at the location without
any tidal datum information due to its position located far from the DSMM tide
INTERNATIONAL JOURNAL OF REMOTE SENSING 5
gauge stations and satellite altimeter track. In addition, the establishment of the
PMNSTD (LATm sl and HATmsl) also improves the current approach of the previous
MyVSEP model (Hamden 2022) which only utilizes tide gauge and satellite altimetry
data. Moreover, this study also proposes an improvement in the delimitation of the
country’s maritime boundaries using geodetic-based approaches. The integration of
the PMNSTD (LATmsl) and the DEM helps to determine the low-water line along the
coast, thus, minimizing the dependency on the limited and sparsely distributed
DSMM tide gauge stations for the establishment of the country’s maritime
basepoints.
3. Research methodology
This study is divided into four phases in which Phase 1 highlights the literature reviews,
identication of the study area, as well as the data acquisition stages. On the other hand,
Phase 2 focuses on the derivation of tidal datum from the tide gauge, satellite altimetry,
and TMD data. In addition, the TanDEM-X data were also acquired during this phase. Next,
Phase 3 focuses on the integration of the tide gauge, satellite altimetry, and TMD to
develop the PMNSTD (LATmsl and HATmsl) using Inverse Distance Weighting (IDW) inter-
polation. Next, the PMNSTD (LATmsl) was integrated with TanDEM-X. Lastly, Phase 4
accentuates the assessment of the reliability of the integration between the PMNSTD
(LATmsl) and TanDEM-X for maritime boundary delimitation. A conclusion was drawn
based on the results of the ndings.
3.1. Study area
The study area is on the east and west coast of Peninsular Malaysia ranging between (1°
N < Latitude < 7° N) and (99° E < Longitude < 105° E). Figure 2 illustrates the proposed
locations for data acquisition.
Figure 1. The current maritime baseline for the Malaysia region (DSMM 2022).
6M. F. ABD RAHMAN ET AL.
3.2. Data acquisition
The data acquisition for this study is divided into four which are the tide gauge data from
DSMM, satellite altimetry data for TOPEX, Jason-1, Jason-2, and GFO from RADS, tidal
datum prediction using TMD, and TanDEM-X data.
3.3. Tide gauge data from 12 tide gauges stations of DSMM
The DSMM tide gauges station data used in this study were obtained from the
University of Hawaii Sea Level Center (UHSLC) website. The tide gauge data of 12
stations in Peninsular Malaysia were selected for a duration of 23 years, starting
from 1993 to 2015. According to (Yasuda 2018), the minimum period of tidal
observation for a stable tidal datum determination is 18.6 years as it presents the
time taken for the moon to make a complete oscillation around the earth.
Therefore, since this study uses 23 years of tidal observation data for tide gauge,
satellite altimetry, and TMD, respectively, hence, it complies with the condition
stated by (Yasuda 2018). The tide gauge data were processed using harmonic
analysis using UTide in MATLAB based on 11 tidal constituents (K1,O1,P1, Q1;M2,
S2, N2, K2, M4, MS4, and MN4Þ. The details are illustrated in Table 1.
Figure 2. Study area.
INTERNATIONAL JOURNAL OF REMOTE SENSING 7
3.4. Satellite altimetry data from RADS
The satellite altimeter used in this study consists of non-sun synchronous satellite missions
which are TOPEX class (TOPEX, Jason-1 and Jason-2) and GFO mission as shown in Table 2.
The satellite altimetry data in this study were extracted from the Radar Altimeter Database
System (RADS) through http://rads.tudelft.nl/rads/status.shtml. The non-sun synchronous
satellite mission was chosen in this study due to its compatibility with harmonic analysis.
For this study, as it shares a similar orbit, the TOPEX class satellite mission was combined to
create a single time-series datum encompassing 23 years of tidal observation from 1993 to
2015. Thus, similar to the tide gauge data, the combination of the TOPEX class mission also
complies with the requirement of 18.6 years period of tidal observation for a stable tidal
datum determination as stated by (Yasuda 2018). On the other hand, due to its dierent
orbit from the TOPEX class satellite mission, the GFO satellite mission cannot be combined
with the TOPEX class mission. However, also due to its compatibility with harmonic analysis,
the GFO mission was utilized as additional satellite altimetry data to ensure a denser data
coverage for the tidal datum determination. The satellite altimetry data were processed
using harmonic analysis using UTide in MATLAB based on 11 tidal constituents (K1,O1,P1,
Q1;M2, S2, N2, K2, M4, MS4, and MN4). On the other hand, the satellite altimeter track for the
TOPEX class and GFO satellite mission are illustrated in Figure 3.
3.4.1. Merging the TOPEX class mission for SSH time series formation
In order to merge the TOPEX, Jason-1, and Jason-2 data into a single time series, the
temporal oset must be carefully considered. TOPEX began its operations in
September 1992 and nished in August 2002. On the other hand, the Jason-1 mission
Table 1. Tide gauge stations used in this study.
No Location Tide Gauge Station
Latitude
(°)
Longitude
(°) Period of Data Observation
1 East Coast
of Peninsular
Malaysia
Geting 6.233 102.100 1993–2015
2 Cendering 5.317 103.183 1993–2015
3 Tanjung Gelang 3.967 103.433 1993–2015
4 Tioman 2.800 104.133 1993–2015
5 Tanjung Sedili 1.933 104.117 1993–2015
6 Johor Bahru 1.467 103.800 1993–2014
7 West Coast
of Peninsular
Malaysia
Langkawi 6.433 99.767 1993–2015
8 Penang 5.417 100.350 1993–2015
9 Lumut 4.233 100.617 1993–2015
10 Port Klang 3.050 101.350 1993–2015
11 Tanjung Keling 2.217 102.150 1993–2015
12 Kukup 1.333 103.450 1993–2015
Table 2. A list of multi-mission satellite altimeters used in this study.
No Satellite Altimeter Phase Mission Period Cycle
1 TOPEX A 25 September 1992–11 August 001–364
B 20 September 2002–8 October 2005 369–481
2 Jason-1 A 15 January 2002–26 January 2009 001–260
B 10 February 2009–3 March 2012 262–374
3 Jason-2 A 4 July 2008–2 October 2016 000–303
B 13 October 2016–17 May 2017 305–327
4 GEOSAT Follow-On (GFO) A 7 January 2000–17 September 2008 37-223
8M. F. ABD RAHMAN ET AL.
was a continuation of the TOPEX mission which started on January 2002 to January 2009.
Afterwards, Jason-2 was launched in July 2008 to replace Jason-1 and concluded its
mission in October 2016. Currently, Jason-3, which was launched in February 2016 to
replace Jason-2, is still operational (Yang et al. 2020). Moreover, Sentinel-3A was also
launched in 2016 and it uses a similar orbit to the TOPEX class satellite mission and is still
ongoing (Heslop et al. 2017; Kittel et al. 2021). Hence, in this study, the formation of the
SSH time series for the TOPEX class satellite mission begins with TOPEX, followed by
Jason-1, and nally ended with Jason-2. Since the TOPEX SSH data end date has been
determined, thus the starting date of the Jason-1 SSH time series that overlaps with the
near-end TOPEX SSH data is truncated (Ainee 2016; Hamden et al. 2021). A similar
approach was also utilized between Jason-1 and Jason-2 SSH time series. The methodol-
ogy used to merge the TOPEX and Jason-1 SSH time series is illustrated in Figure 4
(Hamden 2022; Hamden et al. 2021).
Furthermore, Figure 4 also depicts the data overlap between the Jason-1 SSH time
series and the TOPEX SSH time series at TS1 and TS2. Because the TOPEX data ends
precisely at TS2, the Jason-1 SSH time-series data are shortened from TS1 to TS3. Thus, to
maintain the regular time intervals between the TOPEX and Jason-1 SSH time series, the
temporal oset between points TS2 and TS3 is roughly 10 days. This suggests that the
Jason-1 SSH data is a straight continuation of the TOPEX SSH time series. On the other
hand, the GFO mission (Phase A) is a standalone mission with no time-series consistency
Figure 3. Satellite altimeter track for TOPEX class and GFO for the Peninsular Malaysia region.
INTERNATIONAL JOURNAL OF REMOTE SENSING 9
with the TOPEX class mission. Hence, it is not appropriate to merge the SSH time series of
the GFO satellite mission with the TOPEX class mission. However, since the GFO satellite
mission is also a non-sun synchronous satellite, making it compatible with harmonic
analysis, therefore the GFO satellite mission was also utilized as additional satellite
altimetry data. The addition of the GFO satellite mission also leads to a denser coverage
for tidal datum determination. Still, for an accurate formation of SSH time series, the
along-track TOPEX class (Phase B) and GFO (Phase A) undergo an adjustment known as
the crossover oset by using TOPEX class (Phase A) as a reference orbit.
Such adjustment is essential to reduce the orbital track errors and the discrepancy in the
satellite orbit frame between the TOPEX class (Phase A) with the TOPEX class (Phase B) and
GFO (Phase A), respectively. Theoretically, a satellite altimeter travelling on a repeating orbit
will arrive at the same location after one complete cycle. Nonetheless, the ground tracks do
not exactly correspond to each other for each cycle. For each cycle, the orbit tracks may
move within 1 km to 2 km (Ablain et al. 2017). The SSH time series is created by extracting
the SSH of each cycle at discrete times. The rst cycle of each satellite altimetry along-track
point is used as the reference for future cycles. In order to determine the closest satellite
altimetry locations from the reference track, a radius of 7 km is drawn from each point
(Ainee 2016; Hamden 2022). The time series is formed by selecting the SSH points from the
following cycles within a 7 km radius circle. Such is because the interval of the 1-hertz
satellite altimetry footprint is approximately 7 km apart. As a result, the satellite altimetry
points lying outside the circle are dened as outliers and thus removed from the SSH time
series. Further discussion regarding the acceptance of satellite altimetry points within a 7 km
radius and the generation of TOPEX class SSH time series can be found in (Hamden 2022).
3.4.2. Derivation of tidal datum for satellite altimetry data through tidal analysis
and prediction
The amplitude and phase of 11 tidal constituents, K1,O1,P1, Q1;M2, S2, N2, K2, M4, MS4,
and MN4 are estimated based on the SSH time series from the TOPEX class and GFO
satellite missions using harmonic analysis in UTide. The TOPEX class mission is
Figure 4. Schematic diagram of merging TOPEX and Jason-1 SSH times series. TS1 to TS3 is the
truncation of Jason-1 SSH time series data during the formation of the TOPEX class time series (Ainee
2016).
10 M. F. ABD RAHMAN ET AL.
truncated to create a time series of 23 years of tidal data for a stable determination of
the tidal datum. (Byun and Hart 2019) agreed that the determination of the tidal
datum using at least 18.6 years of observational data for tidal prediction is sucient. In
addition, (IHO 2018) stated that the LAT and HAT may be determined over a minimum
period of 18.6 years, by utilizing the tidal constituents derived from at least 18.6 years
of tide gauge data or other approaches to produce an accurate tidal datum.
3.5. Tidal datum prediction using tide model driver (TMD)
TMD is a MATLAB package developed by Earth and Space Research (ESR) and Oregon
State University (OSU) for accessing the tidal constituents for high-latitude tidal analysis
and prediction. The tidal constituent was used in making predictions of tidal height and
currents (Ningsih et al. 2011; Puntel de Oliveira and Junqueira 2017). It consists of two
signicant functions. First, a graphical user interface (GUI) for browsing tide elds, selec-
tion of study areas, and determining a specic coordinate and duration of time for tidal
predictions of a specic variable. Secondly, it comprises a set of programming codes for
accessing tidal elds (Padman, Erofeeva, and Howard 2022; Puntel de Oliveira and
Junqueira 2017). It was generally used to model the tides using the resolution medium
(1/40 × 1/40) for the global region (Padman, Erofeeva, and Howard 2022; Ramdhan 2011).
Accordingly, TMD was utilized to derive the tidal datum (LAT, MSL, and HAT) within the
same period of observation data with tide gauge and satellite altimetry data, which is
from 1993 to 2015 (23 years). The derivation of the tidal datum using TMD was based on
11 tidal constituents (K1,O1,P1, Q1;M2, S2, N2, K2, M4, MS4, and MN4Þ. Figure 5 shows the
coordinate of the 377 points and its location, respectively, imported into the ArcGIS
working layer to be integrated with the tide gauge and satellite altimetry data.
3.6. Integrating the tide gauge, satellite altimetry, and tide model driver (TMD)
data using IDW interpolation
The two approaches for integrating the tidal datum from the tide gauge, satellite
altimetry and TMD data, either by using the reference ellipsoid or the oset of MSL. In
this study, the integration of all three datasets was performed based on oset, using the
MSL as a reference surface, denoted as LATmsl and HATmsl . Accordingly, the location of 12
DSMM tide gauge stations is shown in Table 1. On the other hand, the satellite altimetry
data for TOPEX, Jason-1, and Jason-2 for Phase (A and B), as well as GFO (Phase A) are
illustrated in Figure 3. In addition, the 377 points of tidal prediction using TMD are shown
in Figure 5 The integration of all tidal datasets is illustrated in Figure 6.
The integration of the derived tidal datum from tide gauge, satellite altimetry data, and
TMD was conducted in ArcGIS. The tide gauge, satellite altimetry, and TMD-derived tidal
datum (LATmsl and HATmsl) in point-based were further interpolated using IDW to estab-
lish the PMNSTD (LATmsl and HATmsl). The determination of LATmsl and HATmsl for the tide
gauge, satellite altimetry and TMD-derived tidal datum are based on Equation 1 and
Equation 2,
LATmsl ¼LAT MSL (1)
INTERNATIONAL JOURNAL OF REMOTE SENSING 11
HATmsl ¼HAT MSL (2)
Consequently, the reliability of the PMNSTD (LATmsl and HATmsl) still needs to be assessed.
Therefore, in this study, the PMNSTD (LATmsl and HATmsl) was assessed statistically in
terms of their standard deviation (STD) and Root Mean Square Error (RMSE) by comparing
the PMNSTD (LATmsl and HATmsl) established from the combination of tide gauge and
satellite altimetry data with the PMNSTD (LATmsl and HATmsl ) established from the
combination of tide gauge, satellite altimetry, and TMD data. The statistical assessment
was based on the oset of PMNSTD (LATmsl and HATmsl) with the oset from the DSMM
tide gauge (LATmsl and HATmsl). In addition, a comparison of the two combinations was
conducted to identify the rate of improvement of the PMNSTD (LATmsl and HATmsl ) with
the addition of TMD data discussed in section 4.4.1.
3.7. TerraSAR-X add-on for digital elevation measurement 30 m (TanDEM-X) data
The open-source DEM used in this study is the TanDEM-X. It is an earth observation radar
mission comprises an SAR interferometer developed by practically twin satellites moving
in an adjacent orbit. Its establishment is the world’s most comprehensive, consistent,
high-precision, and full DEM surface dataset. The mission was generally a common eort
by the German Aerospace Centre DLR and the European Aeronautic Defence and Space
Figure 5. 377 points to be predicted using TMD.
12 M. F. ABD RAHMAN ET AL.
(EADS) Astrium. The project was launched in 2010 and based on the aggregation of the
interferometrically synthetic aperture radar bistatic X-band data acquisition techniques,
aimed at creating a globally homogeneous digital surface model. The mission successfully
gathered interferometric data between 90° north and 90° south utilizing two satellites
TerraSAR-X and TanDEM-X in the X-band that operated in near helix formations (Abd
Rahman et al. 2022). TanDEM-X comes which 0.4-arc second for 12 m and 1-arc second for
30 m spatial resolution, respectively. To encourage opening up the phase for dual-
baseline, the coverage of all landmasses is performed twice (Pa’suya et al. 2019).
TanDEM-X is generally utilized in the science of the earth, involving ecological science
and for resistance purposes, for example, topography, oceanography, earth’s monitoring,
urban planning, and navigation. The mission successfully gathered interferometric data
between 90° north and 90° south utilizing two satellites TerraSAR-X and TanDEM-X in the
X-band that operated in near helix formations (Yap et al. 2019). The vertical and horizontal
data of TanDEM-X is the ellipsoidal heights of WGS84. The data acquisition for the
TanDEM-X satellite is illustrated in Figure 7.
Accordingly, the horizontal and vertical data is WGS84. Hence, to make
a consistent comparison of orthometric height, H between the PMNSTD (LATmsl ), in
this study, the ellipsoidal height, h extracted from Global Mapper for TanDEM-X was
Figure 6. Integration of 12 DSMM tide gauges, 492 satellite altimetry points, and 377 TMD data in
ArcGIS.
INTERNATIONAL JOURNAL OF REMOTE SENSING 13
referenced to Malaysia’s local precise gravimetric geoid, MyGEOID. The determina-
tion of orthometric height, H for TanDEM-X is as stated in Equation (3) (Pa’suya et al.
2019)
HTanDEMx¼hTanDEMXNMyGEOID (3)
where HTANDEM is the orthometric height for TanDEM-X, w.r.t MyGEOID, hTanDEMX is the
ellipsoidal height w.r.t. WGS84 for TanDEM-X and NMyGEOID is the geoid height from
MyGEOID. The processes of extracting the ellipsoidal height, h for 101 coordinates
along the coast of Peninsular Malaysia are illustrated in Figure 8.
3.8. Integrating the PMNSTD LATmsl
ð Þ and TanDEM-X
Firstly, only the PMNSTD (LATmsl ) was utilized due to the determination of the country’s
maritime baseline based on the low-water line along the coast. Furthermore, to integrate
the LATmsl and the TanDEM-X, it is essential that the vertical datum must refer to a similar
reference surface, where for this study, the selected reference surface is the MSL.
Accordingly, the vertical datum for the PMNSTD (LATmsl) refers to the MSL as stated in
Equation 1. As for TanDEM-X, even though it refers to MyGEOID based on Equations (3);
however, since MyGEOID approximately represents the MSL for the Malaysian region, thus
allowing the integration with the PMNSTD (LATmsl) to be conducted. The conceptual
framework for this study is illustrated in Figure 9.
The data integration of the LATmsl and TanDEM-X was performed in ArcGIS. However,
there are still slight dierences between the MSL derived from tide gauge, satellite
altimetry, and TMD in comparison to MyGEOID, respectively. The separation is known as
Mean Dynamic Topography (MDT) for the ocean area, also known as vertical datum bias
(VDB) for the land area, as illustrated in Figure 9 The MDT or VDB represents the
dierences between the derived MSL from tide gauge, satellite altimetry or TMD with
MyGEOID. However, for this study, the dierences between MSL derived from tide gauge,
satellite altimetry, and TMD and MyGEOID are neglected.
Figure 7. TanDEM-X satellite (Abd Rahman et al. 2022).
14 M. F. ABD RAHMAN ET AL.
3.9. Assessment of the reliability of the PMNSTD LATmsl
ð Þ and TanDEM-X for
maritime boundary delimitation
After the PMNSTD (LATmsl) and the TanDEM-X have been integrated, and its reliability was
assessed for the delimitation of maritime boundaries. In this study, the integration of
Figure 8. Extraction of ellipsoidal height, h for TanDEM-X using Global Mapper.
Figure 9. The conceptual framework for integrating the PMNSTD (LATmslÞand TanDEM-X.
INTERNATIONAL JOURNAL OF REMOTE SENSING 15
PMNSTD (LATmsl) and the TanDEM-X was compared with the existing maritime baseline of
DSMM for Peninsular Malaysia. Accordingly, there are a total of 95 maritime basepoints,
which represent the LAT along the coast of Peninsular Malaysia as submitted to the
Division for Ocean Aairs and the Law of the Sea (DOALOS) on the 22nd of July 2022.
Figure 10 shows the formation of the current maritime baseline by connecting all 95
basepoints.
The formation of the proposed maritime baseline through the integration of LATmsl
and TanDEM-X starts by rst extracting the grid of 10 km intervals from the interpolation
of LATmsl in MATLAB. However, unlike the DSMM’s maritime baseline which uses the LAT,
this study, on the other hand, uses the LATmsl to represent the low-water line along the
coast of Peninsular Malaysia. In addition, the 10 km grid intervals were selected for the
grid formation, the validity of a tidal datum is only within a 10 km radius (Parvazi et al.
2015). Figure 11(a) shows the process of extracting the latitude, longitude and LATmsl from
the interpolation of LATmsl in MATLAB. On the other hand, Figure 11(b) the formation of
a 10 km grid for the Peninsular Malaysia region in ArcGIS. Afterwards, the coordinates with
the smallest values of LATmsl of the grid were connected to form a continuous maritime
baseline for Peninsular Malaysia as illustrated in Figure 11(c). Finally, the proposed
maritime baseline was compared with the current DSMM maritime baseline for the
Peninsular Malaysia region.
Figure 10. The current maritime baseline of Peninsular Malaysia.
16 M. F. ABD RAHMAN ET AL.
4. Results and discussion
4.1. Derivation of tidal datum for tide gauge stations
Accordingly, the tidal datum was determined based on 11 tidal constituents (K1,O1,P1, Q1;
M2, S2, N2, K2, M4, MS4, andMN4Þusing UTide. For compatibility in data integration with
Figure 11. (a) interpolation of LATmsl in MATLAB and (b) extracting the grid of 10 km intervals from
MATLAB into ArcGIS (c) connecting the LATmsl with the lowest values along the coast to construct the
proposed maritime baseline.
INTERNATIONAL JOURNAL OF REMOTE SENSING 17
the satellite altimetry and TMD data, the derived LAT and HAT from the tide gauge were
referenced to their derived MSL, denoted as LATmsl and HATmslbased on Equation 1 and
Equation 2. The LATmsl and HATmsl for tide gauge data is illustrated in Figure 12.
4.2. Derivation of tidal datum from satellite altimetry data
Accordingly, similar to the tide gauge data, the LAT and HAT derived from the
satellite altimetry data were also referenced to MSL, denoted as LATmsl and HATmsl
as shown in Equation 1 and Equation 2. Such adjustment is due to the dierent
reference surfaces for the tide gauge which refers to the zero-tide gauge and the
satellite altimetry data refers to the TOPEX ellipsoid, respectively. Hence, by using
the MSL as a common reference surface, the tidal datum derived from the tide
gauge and satellite altimetry can be integrated. The derived tidal datum LATmsl and
HATmsl for satellite altimetry data was interpolated using the IDW interpolation
technique as illustrated in Figure 13.
Figure 12. LATmsl and HATmsl from tide gauge data.
18 M. F. ABD RAHMAN ET AL.
4.3. Derivation of tidal datum from tidal prediction using TMD
The TMD was used to derive the tidal datum for 377 coordinates within 0–20 km from the
coast of Peninsular Malaysia. Similarly, for its integration with the tide gauge and satellite
altimetry data, the derived tidal datum, LAT, and HAT from TMD were also referenced to
the MSL, denoted as LATmsl and HATmsl as shown in Equation 1 and Equation 2. The
derived tidal datum LATmsl and HATmsl for TMD data was also interpolated using the IDW
interpolation technique as illustrated in Figure 14.
Figure 13. (a) LATmsl and (b) HATmsl, respectively, for satellite altimetry data using IDW interpolation.
INTERNATIONAL JOURNAL OF REMOTE SENSING 19
4.4. Development of the PMNSTD ðLATmsl and HATmslÞ
Once the tidal datum from tide gauge stations, satellite altimetry, and TMD has been
determined and referenced to a similar reference surface, the tidal datum (LATmsl and
Figure 14. (a) LATmsl and (b) HATmsl for TMD data using IDW interpolation.
20 M. F. ABD RAHMAN ET AL.
HATmsl) can nally be integrated using the IDW interpolation in ArcGIS. Hence, the near-
seamless tidal datum, LATmsl and HATmsl for Peninsular Malaysia was established.
However, the accuracy of the PMNSTD ðLATmsl and HATmsl) must be assessed statistically
in terms of its STD, and RMSE with the DSMM tide gauge (in-situ) prior to the integration
with the TanDEM-X. For this study, two assessments were made. The rst assessment was
Figure 15. PMNSTD (a) LATmsl and bð ÞHATmsl from the combination of tide-gauge, satellite-altimetry,
and TMD-derived tidal datum.
INTERNATIONAL JOURNAL OF REMOTE SENSING 21
for the PMNSTD ðLATmsl and HATmsl) established from tide-gauge and satellite-altimetry-
derived tidal datum, as illustrated in Figure 13, while the second assessment was for the
PMNSTD ðLATmsl and HATmsl established from tide-gauge, satellite-altimetry, and TMD-
derived tidal datum. Such assessments were conducted to show the rate of improvement
by using TMD as additional bathymetry data. Figure 15 illustrates the PMNSTD
(LATmsl and HATmsl) based on the integration of tide gauge, satellite altimetry, and TMD-
derived tidal datum.
4.4.1. Statistical assessment of the PMNSTD ðLATmsl and HATmslÞwith DSMM tide
gauge stations
Upon its establishment, the reliability of the PMNSTD (LATmsl and HATmsl) were then assessed
statistically based on the oset of LATmsl and HATmsl in terms of their STD, and RMSE prior to
the integration with TanDEM-X. The statistical assessments for both versions of PMNSTD
(LATmsl and HATmsl) were compared with the DSMM tide gauge stations. Accordingly, the
statistical assessment was conducted to determine which combination shows a better agree-
ment with the nine tide gauges station of DSMM (excluding Johor Bahru, Tanjung Keling, and
Kukup due to poor coverage of satellite altimetry data). The statistical analysis for PMNSTD
(LATmsl and HATmsl) with nine DSMM tide gauge stations is illustrated in Tables 3 and 4,
respectively.
For the statistical assessment of the PMNSTD (LATmslÞ, the result has indicated a better STD
of 0.175 m and RMSE of 0.228 m for the PMNSTD (LATmslÞestablished from tide-gauge,
satellite-altimetry, and TMD-derived tidal datum in comparison to the PMNSTD (LATmslÞ
established from tide-gauge and satellite-altimetry-derived tidal datum, which demonstrates
an STD of 0.334 m and RMSE of 0.410 m. A similar outcome was achieved for PMNSTD (HATmsl)
established from tide-gauge, satellite-altimetry, and TMD-derived tidal datum which demon-
strates an STD of 0.079 and RMSE of 0.159 m in comparison to the PMNSTD (HATmsl)
established tide-gauge and satellite-altimetry-derived tidal datum with an STD of 0.272 m
and RMSE of 0.368 m, respectively. Accordingly, the rate of improvement for the PMNSTD
(LATmsl and HATmsl) established from tide-gauge, satellite-altimetry, and TMD-derived tidal
datum is 44% and 57%, respectively, in comparison to the PMNSTD (LATmsl and HATmsl)
established from tide-gauge and satellite-altimetry-derived tidal datum.
4.5. Integrating the PMNSTD ðLATmslÞand TanDEM-X
Based on the result in Tables 3 and 4, it can be indicated that the accuracy of PMNSTD (LATmslÞ
has a good agreement with the DSMM tide gauge stations. Next, the PMNSTD (LATmsl) was
integrated with TanDEM-X for the delimitation of maritime boundaries. The main objective of
integrating the PMNSTD (LATmsl) and TanDEM-X is to determine the location of the proposed
maritime basepoint along the coast of Peninsular Malaysia. Accordingly, the PMNSTD (LATmsl)
refers to the MSL, whereas the orthometric height, H of TanDEM-X refers to MyGEOID (Halim
et al. 2019; Pa’suya et al. 2019), in which MyGEOID is also an approximation of the MSL for the
Malaysian region. The result after the PMNSTD (LATmsl) was integrated with TanDEM-X for the
Peninsular Malaysia region using ArcGIS as illustrated in Figure 16.
In addition, as a way of highlighting the undulation of the PMNSTD (LATmsl) and the
elevation of TanDEM-X, both datasets were processed using SURFER to produce a three-
dimensional (3D) model of PMNSTD (LATmsl) and TanDEM-X. Accordingly, the PMNSTD
22 M. F. ABD RAHMAN ET AL.
(LATmsl) and TanDEM-X data were interpolated using the IDW interpolation technique. The
range for TanDEM-X is between 0.000 m and 2172 m whereas the range for the PMNSTD
(LATmsl) is within −0.377 m to −3.049 m. Hence, due to the range of the orthometric height,
H for the TanDEM-X layer is positive, whereas the range of elevation values for PMNSTD
(LATmsl) layer is negative, resulting in the IDW interpolation of TanDEM-X dominating and
hiding the IDW interpolation of the PMNSTD (LATmsl) if both datasets were integrated in
a single layer [75]. Therefore, the most preferable solution to display the result of the integra-
tion is by presenting the IDW interpolation of PMNSTD (LATmsl) and TanDEM-X, respectively, as
two separate layers as illustrated in Figure 17.
Accordingly, the objective of integrating the PMNSTD (LATmsl) and TanDEM-X was to
pinpoint the location of the proposed maritime basepoint to establish a new maritime baseline
for Peninsular Malaysia. However, the elevation from TanDEM-X only covers up to the coastal
(Abd Rahman et al. 2022; Halim et al. 2019; Pa’suya et al. 2019) and not the oshore area for
which the location for the proposed maritime basepoint was established. Therefore, it is not
Table 3. Statistical assessment of PMNSTD (LATmslÞwith DSMM tide gauge stations.
Tide
Gauge
In-Situ
(m)
PMNSTD (LATmsl ) from
TG and SALT
(m)
PMNSTD (LATmsl ) from
TG and SALT
- In Situ
(m)
PMNSTD (LATmsl ) from
TG, SALT & TMD
(m)
PMNSTD (LATmsl ) from
TG, SALT & TMD
- In Situ
(m)
Cendering −1.318 −0.978 0.340 −1.219 0.099
Geting −0.666 −0.610 0.056 −0.415 0.251
Lumut −1.480 −1.230 0.250 −1.527 −0.047
Penang −1.642 −1.003 0.639 −1.194 0.448
Langkawi −1.800 −1.970 −0.170 −1.526 0.274
Port Klang −2.869 −1.821 1.048 −2.476 0.393
Tioman −1.793 −1.337 0.456 −1.563 0.230
Tanjung
Gelang
−1.793 −1.030 0.763 −1.629 0.164
Tanjung
Sedili
−1.284 −1.185 0.099 −1.463 −0.179
STD 0.334 STD 0.175
RMSE 0.410 RMSE 0.228
Table 4. Statistical analysis for PMNSTD (HATmsl) with DSMM tide gauge stations.
Tide
Gauge
In-Situ
(m)
PMNSTD (HATmsl ) from
TG and SALT
(m)
PMNSTD (HATmsl )
from TG and SALT
- In Situ
(m)
PMNSTD (HATmsl ) from
TG, SALT & TMD
(m)
PMNSTD (HATmsl ) from
TG, SALT & TMD
- In Situ
(m)
Cendering 1.363 1.154 −0.209 1.315 −0.048
Geting 0.963 0.534 −0.429 0.730 −0.233
Lumut 1.359 1.062 −0.297 1.360 0.001
Penang 1.427 1.073 −0.354 1.199 −0.228
Langkawi 1.717 1.309 −0.408 1.511 −0.206
Port Klang 2.948 1.958 −0.990 2.465 −0.483
Tioman 1.618 1.357 −0.261 1.513 −0.105
Tanjung
Gelang
1.826 1.388 −0.438 1.742 −0.084
Tanjung
Sedili
1.299 0.973 −0.326 1.133 −0.166
STD 0.272 STD 0.079
RMSE 0.368 RMSE 0.159
INTERNATIONAL JOURNAL OF REMOTE SENSING 23
possible to pinpoint the location of the proposed maritime basepoint on TanDEM-X on the
coast. Nonetheless, the proposed maritime basepoint can still be established as the position of
the maritime baseline is located at the oshore region and not anywhere near the coastal area.
Thus, for this study, the alternative approach is to only use PMNSTD (LATmsl) to establish the
proposed maritime baseline. Accordingly, the methodology for establishing the new maritime
baseline for Peninsular Malaysia using PMNSTD (LATmsl) is illustrated in Figure 11.
4.6. Reliability assessment of utilising PMNSTD ðLATmslÞfor maritime boundary
delimitation
The reliability of utilizing the PMNSTD (LATmsl) for the delimitation of maritime boundaries
was assessed with the current DSMM maritime baseline. For the assessment, only the 95
maritime basepoints along Peninsular Malaysia were used to assess the reliability of the
maritime baseline established by utilizing the PMNSTD (LATmsl). The maritime baseline
(red line) established by the DSMM by connecting 95 maritime basepoints for Peninsular
Malaysia is illustrated in Figure 18.
Instead of the conventional approach of using LAT (derived from 18.6 years of tidal
observation) from the 12 DSMM tide gauge stations, this study uses the combination of
PMNSTD (LATmsl) along the coast of Peninsular Malaysia to establish the proposed
Figure 16. Integrating the PMNSTD (LATmsl) and TanDEM-X.
24 M. F. ABD RAHMAN ET AL.
maritime basepoints. As illustrated in Figure 11, the proposed maritime baseline is
established using only the PMNSTD (LATmsl) by continuously connecting the LATmsl with
the lowest values within the 10 km grid. Accordingly, a total of 201 points were selected to
construct the proposed maritime baseline. Hence, the establishment of the proposed
maritime baseline (green line) by connecting the 201 points of PMNSTD (LATmsl) along the
coast of Peninsular Malaysia is illustrated in Figure 19.
For the rst comparison, the maritime baseline using PMNSTD (LATmsl ) and the
DSMM was compared in terms of their period of data observation, the continuation of
maritime basepoint, and the radius of validity for the tidal datum. For this period of
observation, the tidal data must be at least 18.6 years for a stable tidal datum deter-
mination. For the continuation of the maritime basepoint, the basepoint must not be
Figure 17. 3D visualisation of superimposing the PMNSTD (LATmsl ) and TanDEM-X for Peninsular
Malaysia as two separate layers in SURFER.
INTERNATIONAL JOURNAL OF REMOTE SENSING 25
sparsely distributed but continuously arranged for a consistent establishment of
a maritime baseline. Last but not least, as for the radius for the validity of the tidal
datum, the separation distance should not exceed 10 km as according to (Parvazi et al.
2015), the tidal datum is only applicable in coastal regions for areas near the tide
gauge stations. (Parvazi et al. 2015) also stated that the determination of tidal datum
for locations more than 10 km away from the tide gauge stations is barely accurate.
Hence, the comparison between the proposed and the current maritime baseline of
DSMM is shown in Figure 20.
Firstly, in terms of the period of observation data, the PMNSTD (LATmsl) for the
proposed approach was determined based on 23 years of tidal data. As for the
current approach, there are no clear statements on the technique (either tidal
observation or tidal prediction) and the period of tidal observation for the 95
DSMM basepoints (DSMM 2022). Thus, leading to the establishment of maritime
basepoints that are still questionable (DSMM 2022). Secondly, in terms of the
continuation of maritime basepoints, the comparison has shown that the proposed
approach produces a more continuous establishment of 201 maritime basepoints
in comparison to the sparse distribution of LAT from the 95 DSMM maritime
basepoints along the coast of Peninsular Malaysia (DSMM 2022). Thirdly, in terms
of the radius for the validity of the tidal datum, the PMNSTD (LATmsl ) derived from
the proposed approach aligns with the requirement of a less than 10 km radius
Figure 18. Current maritime baseline (red line) by DSMM of Peninsular Malaysia (DSMM, 2022).
26 M. F. ABD RAHMAN ET AL.
Figure 19. Establishment of the proposed maritime baseline (green line) using PMNSTD (LATmsl).
Figure 20. Comparison between the current and proposed maritime baseline for Peninsular Malaysia.
INTERNATIONAL JOURNAL OF REMOTE SENSING 27
(Parvazi et al. 2015). On the other hand, for the current approach, the derived LAT
from the 95 DSMM basepoint does not comply with the minimum requirement as
the distance to the maritime basepoints exceeded a 10 km radius (DSMM 2022).
Thus, it can be concluded that the approach of using PMNSTD (LATmsl) for mar-
itime boundary delimitation leads to a more continuous and justied maritime
baseline for the Peninsular Malaysia region in comparison to the current approach
by DSMM.
5. Conclusion
In conclusion, the establishment of the 201 maritime basepoints using the integration of
PMNSTD (LATmslÞbased on the integration of tide gauge, satellite altimetry and TMD-
derived tidal datum with TanDEM-X, in comparison to the 95 sparsely distributed mar-
itime basepoints by the DSMM has led to a continuous determination of the country’s
maritime basepoint.
Disclosure statement
No potential conict of interest was reported by the author(s).
Funding
This project is funded by the Ministry ofHigher Education (MOHE) under the Fundamental Research
Grant Scheme (FRGS)Fund, Reference Code: FRGS/1/2021/WAB05/UTM/02/1 (UTM Vote Number:R.
J130000.7852.5F478).
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