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USING SAR DATA FOR A NUMERICAL ASSESSMENT OF THE INDONESIAN
COASTAL ENVIRONMENT
Martin Gade (1), Bernhard Mayer (1), Thomas Pohlmann (1), Mutiara Putri (2) , Agus Setiawan (3)
(1) Universität Hamburg, Institut für Meereskunde, Bundesstraße 53, D-20146 Hamburg, Germany,
Email:{martin.gade;bernhard.mayer;thomas.pohlmann}@uni-hamburg.de
(2) Institute Technology Bandung, Bandung, Indonesia, Email: mutiara.putri@googlemail.com
(3) Agency for Marine and Fisheries Research and Development, Jakarta, Indonesia, Email: setiawan.agus@gmail.com
ABSTRACT
Within the German-Indonesian pilot study IndoNACE
(Indonesian Seas Numerical Assessment of the Coastal
Environment) a wealth of SAR data of two dedicated
regions in Indonesian waters are being analysed with
respect to the imaging of marine oil pollution.
Numerical tracer studies using a regional 3-d numerical
model are used to aide those analyses and to help
understanding the observed seasonal variations in
marine oil pollution. Our first results are based on 130
ENVISAT ASAR images of each of the two regions of
interest, the ‘Western Java Sea’ and the ‘Makassar
Strait’ and indicate that most pollution was found in
areas of high ship traffic and of intense oil production.
1. INTRODUCTION
Indonesian territorial waters cover about three million
square kilometres, thereby being larger than the
Mediterranean Sea, and are home to more than 3.000
species of fish and more than 500 species of corals. The
Indonesian coastline is longer than 80.000 kilometres,
and the Indonesian archipelago encompasses more than
17.000 islands. Major ship traffic routes, connecting the
economic centres on the South China Sea (and beyond)
with Europe, Africa, Australia, or the Persian Gulf, run
through Indonesian waters.
Although its total oil production has decreased by 25%
during the past decade, Indonesia still ranks amongst the
top 25 oil producing countries worldwide and is the
third-largest oil producer in Pacific Asia [2]. However,
not only because of a continuously increasing demand
Indonesia, along with its neighbouring countries, has
always been importing oil from other countries
worldwide.
The marine ecosystem in Indonesia is under increasing
pressure due to social and economic growth in the entire
region. Parts of the so-called Coral Triangle, a six
million square kilometres area in Pacific Asia, lie in
Indonesian territorial waters, where the coral reef area is
estimated to be 20,000 square kilometres in size (Fig.
1). Along with mangrove forests and seagrass meadows
on the coasts, these areas are particularly vulnerable to
pollutants.
Several marine protected areas (MPA) have been
defined in Indonesia, where part or the entire enclosed
environment is protected by law or other effective
means (Fig. 1). Continuous monitoring is of key
importance in these areas, but can only be done in an
effective manner by taking advantage of state-of-the-art
remote sensing and numerical modelling techniques.
The goal of the proposed Pilot Study, therefore, is to
combine spaceborne remote sensing data with
sophisticated numerical models, in order to meet these
monitoring requirements.
The joint German-Indonesian Pilot Study IndoNACE
(Indonesian seas Numerical Assessment of the Coastal
Environment) aims at improving the information on the
state of the Indonesian marine environment that is
gained from satellite data. Synthetic aperture radar
(SAR) data are used to produce oil pollution density
maps of two dedicated regions of interest (ROIs) in
Indonesian waters, namely the Western Java Sea and the
Strait of Makassar.
Marine mineral oil spills show up on SAR imagery as
dark patches [4][5], which however can be confused
with other, atmospheric or oceanic, phenomena such as
wind shadowing, biogenic slicks, etc. [3]. Since (the
development of) an automated oil-pollution detection
system is not in the scope of this study, a visual
inspection of all available SAR images of Indonesian
waters is being performed, along with a manual
registration in state-of-the-art databases including geo-
information on the detected spills (lat/lon, size, etc.) and
Figure 1. Marine Protected Areas (MPA) in Indonesia.
_____________________________________
Proc. ‘Living Planet Symposium 2016’, Prague, Czech Republic,
9–13 May 2016 (ESA SP-740, August 2016)
metadata (wind speed and direction, etc.). Special
emphasis is being put on the discrimination between
anthropogenic (mineral oil) spills and biogenic slicks,
since both species tend to cause similar features on SAR
imagery [6][7], see Fig. 4.
Both historical and actual SAR data from ESA’s
ENVISAT archive (for an example see Fig. 2) and
Sentinel 1A Rolling Archive (Fig. 3), respectively, are
used. Fig. 2 is an ENVISAT ASAR image of the Java
Sea, which shows many imprints of marine oil pollution
as dark spots. The image was picked arbitrarily and is a
good example for the frequent oil pollution in
Indonesian waters.
2. REGIONS OF INTEREST
The aim of the proposed study is to gain information on,
and to further the knowledge about, the vulnerability of
dedicated marine (coastal and offshore) areas in
Indonesia to marine oil pollution. Two regions of
interest (ROI) have been identified (Fig. 4), the western
part of the Java Sea, with borders 105.0°E ‐ 111.0°E and
7.0°S ‐ 3.0°S, and the Makassar Strait, with borders
116.0°E ‐ 120.0°E and 5.5°S ‐ 1.0°N. The ROIs were
chosen because of high economical activities (including
ship traffic) and a high density of MPAs and coral reefs,
respectively. Oil pollution density maps will be
produced for both areas and, along with sensitivity
charts of coastal areas, will be used as input for
numerical modelling activities. The ultimate goal of this
effort will be to provide qualitative and quantitative
information on the way, in which marine oil pollution
presents a hazard to particularly sensitive coastal
regions.
3. NUMERICAL MODEL
To get an idea about the origin of potential oil spills
within the MPAs, a set of numerical models has been
applied. The first numerical model is the Hamburg Shelf
Ocean Model (HAMSOM, [1][11]), a three-dimensional
regional baroclinic ocean circulation model, here with a
Figure 2. Envisat ASAR image (82 km × 88 km) of the
Java Sea, north off Java (Eretan Bay is in the lower
image centre), acquired on 8 December 2005 at 02:25
UTC. Throughout the image small dark patches can be
delineated, which are due to mineral oil spills.
However, dark areas on the lower left and off the coast
are due to low wind. The upper right part of the image
is a Marine Protected Area (MPA), see Fig. 1.
Figure 3. Sentinel 1A SAR image (240 km × 253 km) of
the northern Strait of Macassar, acquired on 18
November 2014 at 10:18 UTC. The north-western part
of Sulawesi is reaching through the image. Major dark
elongated patches in the upper left part of the image,
i.e., at the northern end of the Strait, are likely to be due
to mineral oil spills. Further south of the imaged area
extended coral reefs can be found, see Fig. 1.
Figure 4. Two regions of interest (ROI): “W Java Sea”
with borders 105.0°E / 111.0°E and 7.0°S / 3.0°S, and
“Makassar Strait” with borders 116.0°E /120.0°E and
5.5°S / 1.0°N.
horizontal grid resolution of 6' (approx. 11 km) and an
increasing vertical resolution from 6 m at the surface to
several hundred meters at greater depths. The
meteorological forcing was taken from NCEP/NCAR
[9]. The open boundary conditions (temperature,
salinity, sea surface height) were taken from the global
circulation model MPIOM [8]. The results of this
hydrodynamical model were validated using observed
velocities from moored current meters of the INSTANT
project [12] at different locations as well as SST and
SSS satellite data. The subsequently applied model was
a Lagrangian tracer model [10], which used the
simulated velocities of HAMSOM. According to the
tracer's location within a grid cell, it is subject to the
spatially interpolated velocity including its acceleration
along its path due to spatial change of the velocities.
This is done for the horizontal direction only, because
the oil spills are tracked only as long as they move
horizontally on the sea surface. The simulation was then
performed in a backward direction for four weeks in
four typical months in the period 2003-2011: end to
beginning of February (fully developed NW monsoon),
of April (transition period), of August (fully developed
SE monsoon), of October (transition period). Tracers
were located into every grid cell located within the
coordinates of the three MPAs.
4. MODELLING RESULTS
The simulation results show the possible origins of oil
spills ending up in the aforementioned MPAs after four
weeks as presented in Figs. 5 and 6. For each year from
2003-2011, the backward paths of selected tracers for
the corresponding month is plotted in its year-specific
color. Diamonds show the positions after one week
backwards, or, if direction is changed to forward, they
display the position of the tracers one week before they
arrive at the MPA.
For the Seribu Islands MPA (Fig. 5), only the August
trajectories show a uniform distribution of the tracer
paths, with this, it is most probable that oil spills
detected in the Seribu MPA, originate from the east,
regardless of the year. The possible source is located
within an area of approx. 110 km (north-south) and 400
km (west-east) along the northern coast of Java. During
the SE monsoon season, the quite strong surface
currents in the Java Sea are clearly directed westward.
During NW monsoon season (February), the direction is
opposite with much weaker currents. The area of
possible sources for oil in the ocean covers approx. 110
km (north-south) and 200 km (west-east). Only in 2003,
the tracers came through the Sunda Strait from the
Indian Ocean, and only for three years, the origin might
have been around Bangka Island, almost 400 km north
of Seribu Islands. Both transition periods April and
Figure 5. Simulated backward trajectories of tracers
starting in the MPA "Seribu Islands", western Java Sea.
Different colours show different years, different panels
show different months. The diamonds show the position
after one week backward simulation, i.e. one week
before they would arrive at the MPA.
Figure 6. Same as Fig. 5, but for the MPAs "Berau",
northwest of Makassar Strait entrance (marked by a
black rectangle), and "Bontang" in the northwestern
Makassar Strait (marked by a red star).
October show year-dependent wide-spread possible
origins coming from a large area to the north and east of
Seribu Islands, which is a result of a yearly varying
transition period.
For the Berau MPA (black rectangle in all panels of Fig.
6), the oil spills originate always in the north to north
east of the MPA, showing the general counter-clockwise
circulation in the Celebes Sea. Only for February and
October, oil spills might be transported even from the
Sulu Sea to Berau MPA. Trajectories east of 121.5 °E
were truncated because of the end of the tracer model
grid. In the forward view, tracers starting at this
longitude would arrive at the MPA after approx. 9-14
days in all months and all years. In the August panel, a
large eddy is obvious for three years. This is the result
of eddy shedding processes of the Mindanao Current, of
which the reflection zone south of the Philippines back
to the NECC (North Equatorial Counter Current) moves
more and more into the Celebes Sea. After shedding, the
eddy moves westward in the Celebes Sea towards the
northern entrance to the Makassar Strait.
The Bontang MPA (red star in all panels of Fig. 6)
tracers show hardly any movement, because they are
close to the coast, were the currents are obviously very
slow in this region.
5. SAR DATA BASIS
In total, for our statistical analyses more than 5000 SAR
images are available, which were acquired by
ENVISAT ASAR (almost 1200, acquired 2002-2012),
ALOS-1 PALSAR (more than 2800, acquired 2006-
2011), and Sentinel-1A (almost 800, acquired from
2014). Analyses of all SAR images have been done
visually, after the student operators were thoroughly
trained. In this paper, we concentrate on those results
that were obtained through the analysis of 260
ENVISAT ASAR images, of which 130 images were
acquired over the Western Java Sea and 130 over the
Makassar Strait. Fig. 7 shows the total coverage of both
ROIs by ENVISAT ASAR imagery, indicating that the
western and south-western parts of the Java Sea were
best covered, as well as the north-western Makassar
Strait, off the harbour of Balikpatan and to its north-
east, where oil production plays a major role.
6. SAR IMAGE ANALYSES
The (visual) inspection of the wealth of available SAR
data allows for the generation of pollution occurrence
maps that include all detected oil pollution. Fig. 8 shows
the geographical locations of all (so far) detected oil
spills, binned on a 0.05°×0.05° grid, for both ROIs, the
Makassar Strait (upper panel) and the Western Java Sea
(lower panel). Clearly visible are areas of higher oil
pollution off Kalimantan’s coast, where the maximum
number of oil spills per grid cell exceeds five, and north
of Java, where a maximum number of three spills per
grid cell were found. These areas are marked by high
ship traffic (‘W Java Sea’) and by heavy oil production
(‘Makassar Strait’), both putting the local environment
under severe threat. We also note, however, that the
areas of maximum detected oil pollution coincide with
those areas, where the SAR image coverage is highest
(Fig. 7). A greater number of SAR images is therefore
needed to allow for better statistics.
Figure 7. Coverage of both ROIs by almost 1200
ENVISAT ASAR images of 2002-2012.
Figure 8. Number of Spills per 0.05°×0.05° grid cell, as
detected in 130 ENVISAT ASAR images of each ROI.
The seasonality of the observed oil pollution in the
Western Java Sea is demonstrated in Fig. 9. The upper
panel shows the total number of oil spills detected in
each month of the year, while the lower panel shows the
respective number of oil spills per SAR image of that
ROI.
The largest number of oil spills has been found in
(boreal) spring (March and April) and autumn (October
– December). We note that these periods mark the
transition from winter monsoon to summer monsoon,
and vice versa. During those periods, the overall current
pattern in the Java Sea changes, which can be seen in
the simulated backward trajectories from the MPA
‘Seribu Islands’ in Fig. 5. A greater amount of water
from the inner Java Sea is moving towards south-west,
thereby reaching those areas where the highest pollution
was encountered. This example demonstrates how our
approach, to combine numerical tracer modelling with
(visual) SAR image analyses, can help in better
understanding the observed seasonality.
The corresponding results for the Makassar Strait are
shown in Fig. 10. Here, maximum pollution was found
during the (boreal) winter months, i.e. in December –
February. This is the period of the north-westerly winter
monsoon, which drives additional water from the Banda
Sea into the Makassar Strait, thereby slowing down the
overall current speed. Further results of these analyses will be a pollution
density map of both Regions of Interest, which will be
frequently updated throughout the lifetime of the pilot
study.
7. CONCLUSIONS
Historical and actual SAR data from ESA’s ENVISAT
archive and Sentinel 1A Rolling Archive, respectively,
are being used for the generation of pollution
occurrence maps that include all detected oil pollution.
SAR images of the two ROIs have been visually
inspected, while special emphasis has been put on the
discrimination between anthropogenic (mineral oil)
spills and biogenic slicks, since both species tend to
cause similar features on SAR imagery. The crude
statistical charts presented herein will be further
improved by including information on the SAR
coverage and local weather conditions (basically the
wind speed, which is the limiting factor for the visibility
of oil pollution on SAR imagery). As a result an
improved pollution density map of both ROIs will be
generated and will be kept up-to-date through the
inclusion of actual SAR data.
In parallel, an existing numerical model has been
adapted and, in combination with a tracer dispersion
model, high-resolution numerical backward tracer
experiments have been performed. Choosing dedicated
MPAs as starting point for backward tracing modelling
exercises, we could show that potential areas, from any
marine pollution of the MPAs could originate, differ
depending on the season and, therefore, on the overall
wind conditions (winter and summer monsoon).
Figure 9. Seasonal variation of the detected oil
pollution in the ROI ‘W Java Sea’. The upper panel
shows the distribution of the numbers of oil spills that
were found in 130 ENVISAT ASAR images. The lower
Panel shows the respective distribution of the average
numbers of oil spills per SAR image.
Figure 10. Same as Fig. 9, but for the ROI ‘Makassar
Strait’.
Our crude statistical charts will be further improved by
including information on the local SAR coverage and
local weather conditions (basically the wind speed,
which is the limiting factor for the visibility of oil
pollution on SAR imagery). Further studies will also
include forward tracer modelling, starting from those
areas, in which the strongest marine pollution was
found, i.e. using the previously gained information sets
on existing pollution as input. Thereby we will identify
strongly affected coastal areas (with most oil pollution
being driven onshore), but also sensitive parts of major
ship traffic lanes (where any oil pollution is likely to be
driven into Marine Protected Areas).
8. ACKNOWLEDGEMENTS
The pilot study IndoNACE is receives funding from the
European Space Agency (ESA) under contract ITT AO
1-8176/14/F/MOS. ENVISAT ASAR imagery was
kindly made available by ESA’s EO Grid Processing
On-Demand (EO-GPOD) Team.
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