environmental sensitivity index assessment using formosat-2
TRANSCRIPT
Subagio et al.
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ENVIRONMENTAL SENSITIVITY INDEX ASSESSMENT USING
FORMOSAT-2 SATELLITE IN LABUAN COASTAL, BANTEN
Widitya Putri Fitriyanny Subagio 1)
,Abd. Rahman As-Syakur 2)
, Wandito
Himawan Soedomo 3)
, And I Wayan Sandi Adnyana 4)
1) Research Center for Marine Technology – Ministry of Marine Affairs and Fisheries
2) ,4) Environmental Research Center Udayana University
3) The Agency for the Assessment and Application Technology
Email : [email protected]
ABSTRACT Labuan coastal has highly risk of pollution case that might be distributed both from activity in
north area and land activity throughout coastline. Buffer process produced three zones of
sensitivity area. Sensitive area located in Karang Kebua Island and Popole Island. Average
sensitive area located throughout coastline in Pagelaran sub district, Panimbang sub district and
north part of Labuan sub district. Less sensitive area located throughout coastline in south part
of Labuan sub district. From numerical simulation result, Popole Island could get direct impact
from steam power plant (PLTU Labuan) activity. Meanwhile, coastline area throughout Labuan
sub district, Pagelaran sub district and Panimbang sub district have potential to be polluted from
pollutant in north area that might be brought through current circulation. Environmental
Sensitivity Index (ESI) map can be used to decide which area is the most susceptible and
sensitive concern with pollution in order to support regional planning strategy for stakeholders
and decision makers.
Keywords: Environmental Sensitivity Index, Labuan coastal, FORMOSAT-2 satellite data,
Geographical Information System (GIS)
I. INTRODUCTION
Coastal areas, by virtual of their position at the interface between truly terrestrial
ecosystems and aquatic systems, belong to the most dynamic and important ecosystems
on Earth (Yang et al., 1999). They are also the foci of human settlement, industry, and
tourism. Large coastal population and intense development are exacerbating
environmental stress and degradation of the coastal ecosystems, thus placing an elevated
burden on organizations responsible for the planning and management of these highly
sensitive areas (Yang, 2008).
Coastal maps are widely regarded to be an essential data source for coastal
management planning (Mumby et al., 1999). To a large extent, management objectives
can be defined in terms of coastal area, either because of their intrinsic value or because
of their significance in habitat characterization. Remote sensing could be used to
mapping coastal environment. Remotely sensed optical signatures have proved useful
for mapping mangrove, Coral Reefs, Macroalgae and other coastal habitat (Green et al.,
2000).
Labuan coastal located between industrial and tourism activity in northern area
(Cilegon, Carita, Anyer areas) that might bring some pollutants through ocean
circulation process to Labuan coastal and also Ujung Kulon National Park in the south
which designated for conservation area. It is important to arrange Environmental
Sensitivity Index (ESI) map in order to get information where is the most sensitive area
concern with pollutant in Labuan coastal. In the present study ESI analysis maps are
prepared to collect information regarding environmental baseline status of the study
Environmental Sensitivity Index Assessment Using Formosat-2 Satellite
In Labuan Coastal, Banten
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area pertaining to physical, human, biological resources, land use/land cover, and socio-
economic attributes which form important attribute for ESI maps (Sexena et al., 2004).
The most sensitive area in Labuan coastal needs special monitoring because this
area will be very susceptible with pollutant. Result of Environmental Sensitivity Index
map can be used to support stakeholders and decision makers to arrange regional
planning strategy in Labuan coastal.
Formosat-2, a satellite owned by the Taiwan National Space Organisation (NSPO),
was launched in May 2004. It provides images with features very close to Venμs: spatial
resolution of 8 m in four spectral bands centered at 488, 555, 650 and 830 nm, spatial
resolution of 2 m in panchromatic spectral, and field of view of 24 km (Hagolle, et al.,
2008). The orbital cycle is completed within one day. The sensor may deviate from
nadir in order to point at sites close to the ground track. Therefore, accessible locations
at Earth's surface are observed under a unique viewing direction (Bsaibes et al., 2009).
Remote sensing image analysis systems and geographic information systems
(GIS) show great promise for the integration of a wide variety of spatial information as
a support to tasks ESI. Remote sensing often requires other kinds of ancillary data to
achieve both its greatest value and the highest level of accuracy as a data and
information production technology. GIS can provide this capability (Star and Estes,
1990). GIS can make order to develop the required capability of natural resources
mapping and periodical monitoring (Muzein, 2006). As the coastal sensitive response
community moves towards development of automated sensitivity maps, it is important
to define what comprises the ESI mapping system and how this information is being
developed and distributed using GIS technology (NOAA, 2002).
II. METHOD
Figure 1. Reseach Location.in Pandeglang Regency (inset figure) (Source:
www.bapedalbanten.go.id)
This research located in Labuan coastal in western coast of Banten province with
specific location 6° 15' 40" - 6° 41' 30" S / 105° 35' 00" - 106° 00' 00" E (Figure 1).
FORMOSAT-2 satellite data recorded from National Space Agency of Taiwan in
9th
August 2007 was used as data base to produce Environmental Sensitivity Index Map.
This satellite data has 2 m x 2 m resolution (panchromatic band (0.45~0.90μm)), and 8
m x 8 m resolution (multispectral band (0.45~0.52μm (Blue); 0.52~0.60μm (Green);
0.63~0.69μm (Red); 0.76~0.90μm (Near Infra Red). Ground truth data were available
from Ministry of Marine Affairs & Fisheries, Research Center of Marine Technology
Subagio et al.
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(Pratama et al., 2007) taken on 5th
– 7th
August 2007. Ground truth data were consisted
of water quality data (temperature, salinity, tubidity, total suspended solid), sea grass
area, coral reef area, coastal characteristic, and important place. These data were taken
using rapid coastal habitat assessment methods (English et al., 1997 in Pratama., 2007)
in 22 stations to support data analysis.
Research process was divided into three parts: (1) data collection, (2) data
processing (Image processing using brovey transformation, land use classification using
supervised classification, pollutant source and distribution using numerical model
simulation) and (3) arrangement of Environmental Sensitivity Index Map using
Geographical Information System (buffering process methods).
2.1. Brovey Transform
Based on Neteler et al. (2004), brovey transform can combine both panchromatic
image and multispectral image to produce high quality image with equation (1) :
1
1 2 3
*bfused pan
b b b
DNDN DN
DN DN DN………………………………………………..(1)
Where DNfused (Digital Number after fusion process); DNb1 (Digital Number band
1 multispectral); DNb2 (Digital Number band 2 multispectral); DNb3 (Digital Number
band 3 multispectral); DNpan (Digital Number panchromatic image).
2.2. Supervised Classification
A supervised classification was a methods of clustering pixels in a data set into
classes corresponding to user-defined training classes. Training classes are groups of
pixels or individual spectra and it was selected as representative areas or materials that
mapped in the output (CCRS, 2003).
In this research, supervised classification has determined with mahalanobis
distance method which has assumed that all pixel were classified to the closest region of
interest. Region of interests have been determined by choosing pixels from image
satellite data. Groups of pixel were chosen to represent one region or class. Furthermore
with mahalanobis distance process, groups of pixel in several region or class were
classified to describe some region or class from image satellite data. In some cases,
some pixels may be classified in the same class with other pixel although it was not the
exactly region. To avoid that condition, visual interpretation and ground truth data are
needed to support such classification.
2.3. Numerical Simulation Model
Numerical simulation model has been done to predict source and distribution of
pollutant. Total simulation is 31 days and it divided into thermal distribution model
(source pollutant from PLTU Labuan) and current circulation model in equation (2), (3)
and (4) based on Kouitas (1988) in Soedomo (2006):
Continuity equation
0u v
t x y ………………………………………… (2)
Environmental Sensitivity Index Assessment Using Formosat-2 Satellite
In Labuan Coastal, Banten
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Momentum equation
2
h h
U U UU V g fV v U
t x y x ………………………………………….(3)
Thermal distribution equation
( ) ( )x y
C CU CV C Cv R R C
t x y x x y y……………………………….
(4)
Where η (elevation); u (velocity x direction); v (velocity y direction); g (gravity
component); f (friction component); C (temperature); Rx & Ry (diffusion component).
2.4. Buffering Process
Buffering technique refers to the creation of a zone of a specified width around a
point or a line or a polygon area. It is also referred to as a zone of specified distance
around coverage features (Mandagere, 2008).
Buffer technique formed new buffer zone that covered buffered object (point, line
or polygon) based on the distance that already set before buffering process. Buffer zone
can be used to define spatial closeness function from one object to another object.
Spatial data of buffer zone is liable with several spatial operation and attribute.
In this case, buffer zone combined each score of parameters become total
Environmental Sensitivity Index (ESI) scoring. From total Environmental Sensitivity
Index (ESI) scoring, the most and the least sensitive area could be predicted.
Figure 2. Determining of buffer zone distance (Source : http://www.sli.unimelb.edu.au)
2.5. Environmental Sensitivity Index
Environmental Sensitivity Index is scoring method to decide the most sensitive
area based on combination score coverage of coral reef, coverage of sea grass,
important place and coastal characteristic (Sloan, 1993) based on equation (5):
Subagio et al.
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ESI CC SG CR IP …………………………………….. (5)
Where ESI (Total Environmental Sensitivity Index score; range 1-20); CR (Score
of coral reef cover percentage; range 1-5); SG (Score of sea grass cover percentage;
range 1-5); CC (Score of coastal characteristic; range 1-5); IP (Score of important place;
range 1-5). Score 1 is the least sensitive area and score 5 is the most sensitive area. This
scoring index showed in Table 1. Determination of total Environmental Sensitivity
Index score will be divided into total Environmental Sensitivity Index score in three
small islands (Karang Kebua Island, Popole Island and Liwungan Island) and total
Environmental Sensitivity Index score in region throughout coastline area in three
subdistrict (Labuan sub district, Pagelaran sub district, Panimbang sub district
Table 1. Environmental Sensitivity Index Value (Sloan, 1993)
Principal parameters Score
Coastal Characteristic
Muddy coastal 5
Sheltered tidal flat 4
Exposed tidal flat 3
Grained sandy coastal 2
Exposed rocky shore 1
Coral Ecosystem
Coverage hard coral & other family 80-100% 5
Coverage hard coral & other family 60-80% 4
Coverage hard coral & other family 40-60% 3
Coverage hard coral & other family 20-40% 2
Coverage hard coral & other family 0-20% 1
Sea Grass Ecosystem
Coverage sea grass 80-100% 5
Coverage sea grass 60-80% 4
Coverage sea grass 40-60% 3
Coverage sea grass 20-40% 2
Coverage sea grass 0-20% 1
Important Place
Tourism resort (include diving & snorkeling
site)
5
Planting area (include fishpond) 4
Settlement and Power Station 3
Fisheries area 2
Port / Harbor 1
Environmental Sensitivity Index
Very sensitive area 16-20
Sensitive area 11-15
Average sensitive area 6-10
Less sensitive area 1-5
Environmental Sensitivity Index Assessment Using Formosat-2 Satellite
In Labuan Coastal, Banten
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III. RESULTS AND DISCUSSION
3.1. Brovey Transform and Land Use Classification Result
Figure 2 showed the result of satellite image before and after brovey
transformation. Image after brovey transformation (Figure 3 right) indicated clearer
image than that without brovey transform (Figure 3 left).
Figure 3. Comparisson image without brovey transform (left) and with brovey transform
(right) (Source: data processing result)
Land use classification using supervised classification methods classified each
pixel based on training area or region of interest (CCRS,2003).
Supervised classification result consist of 14 classes only because there are so many
pixel in image satellite data that have similar value therefore supervise classification
process classified similar pixel into one region. Therefore each detail class were
digitized using the integration between supervised classification result, high image
quality from Brovey transform result and also field data. This process will change raster
data to vector data using digitations process. After digitations, Labuan coastal is
classified into 22 classes in vector type (Fig 4).
Figure 4. Supervised classification result vector data type (source: data processing
result)
Panimbang Pagelaran
Labuan Karang Kebua Island
Popole Island
LiwunganIsland
SUNDA STRAIT
Subagio et al.
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From land use classification, the area can be divided into 4 parameters there are
coral distribution, sea grass distribution, coastal characteristic, and important place.
3.2. Source of Pollutan Using Numerical Model Simulation
Result of this numerical model can be seen in Figure 5 and Figure 6.
Figure 5. Result of thermal pollution distribution model in day 1, day 15, day 31
(source: data processing result)
Figure 6. Result of current circulation throughout coastline area in day 1, day 15, day 31
(source: data processing result)
Simulation model for thermal pollution showed that thermal pollutants from
power station could be distributed until Popole Island. Hot sea water from power
station outlet has temperature until 36oC. High temperature could disturb coral reef
and sea grass ecosystem in Popole Island. Simulation model for current distribution
showed that current system flow from north part to south part. Industrial and tourism
activity from Cilegon, Carita and Anyer area could be distributed throughout Labuan
coastline area. This result is appropriate with research of Pariwono (1999) whom
said that current system in Sunda Strait is always flows from north part to the south
part.
3.3. Arrangement of Environmental Sensitivity Index Map
Total Environmental Sensitivity Index score in region throughout coastline
area only consist of coastal characteristic and important place therefore these areas
are divided into 17 buffer zones (Figure 7) to make a combination score between
score of important place and coastal characteristic.
Environmental Sensitivity Index Assessment Using Formosat-2 Satellite
In Labuan Coastal, Banten
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Figure 7. Buffering zones to arrange buffering process
(source: data processing result)
Figure 7. Buffer Zone (source: data processing result)
Total Environmental Sensitivity Index (ESI) Score in Small Islands
Based on buffer process and ESI table score in that mention in table 1, ESI
score in Karang Kebua Island consist of combination score of coverage coral reef
(coverage 50%; score 3), important place (tourism; score 5) and coastal
characteristic (muddy coastal; score 5) so that total ESI score is 13 (sensitive area).
ESI score in Popole Island consists of combination score of coverage coral
(coverage 63%; score 4), important place (tourism; score 5); coverage sea grass
(coverage 50%; score 3) and coastal characteristic (grained rubble; score 2) so that
total ESI score is 14 (sensitive area). ESI score in Liwungan Island consists of
combination score of coverage coral reef (coverage 13%; score 1) and coastal
characteristic (grained rubble; score 2) so that total ESI score is 3 (Less sensitive
area).
Total Environmental Sensitivity Index (ESI) Score in Region Throughout
Coastline. ESI score in region throughout coastline can be seen in table 2 below. Total
score of each parameters were based on Environmental Sensitivity Index Value in
table 1.
11 21 31 4
1 51 61 71 8
1
1001
91
11
12
13
14
15
161
17
Subagio et al.
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Table 2. ESI Score in Region Throughout Coastline
Buffer
Zone
Paramaters Total
Score
ESI Index
1 settlement (score:3) & muddy coastal (score:5) 8 Average Sensitive
2 planting area (score:4) & muddy coastal
(score:5)
9 Average Sensitive
3 tourism area (score:5) & muddy coastal
(score:5)
10 Average Sensitive
4 planting area (score:4) & muddy coastal
(score:5)
9 Average Sensitive
5 planting area (score:4) and rocky coastal
(score:1)
5 Less Sensitive
6 port (score:1) and rocky coastal (score:1) 2 Less Sensitive
7 planting (score:4) and rocky coastal (score:1) 5 Less Sensitive
8 planting area (score:4) & muddy coastal
(score:5)
9 Average Sensitive
9 Power plan (score:3) & muddy coastal (score:5) 8 Average Sensitive
10 planting area (score:4) & muddy coastal
(score:5)
9 Average Sensitive
11 settlement (score:3) & muddy coastal (score:5) 8 Average Sensitive
12 planting area (score:4) & muddy coastal
(score:5)
9 Average Sensitive
13 planting area (score:4) & muddy coastal
(score:5)
9 Average Sensitive
14 settlement area (score:3) & muddy coastal
(score:5)
8 Average Sensitive
15 forest area (score:4) & muddy coastal (score:5) 9 Average Sensitive
16 grass field (score:4) & rubble grain coastal
(score:2)
6 Average Sensitive
17 tourism area (score:5) & grained rubble coastal
(score:2)
7 Average Sensitive
Environmental Sensitivity Index Map can be arranged based on result of buffering
process and can be seen in Figure 8. From the figure can be seen that Karang Kebua
Island and Popole Island are categorized in sensitive area. Furthermore, steam power
plant (PLTU Labuan) located near Popole Island and from numerical simulation model
can be seen that outlet from power station (water with high temperature) can be
distributed until Popole Island. Change of temperature will give impact to the local
ecosystem in Popole Island such as coral reef and sea grass that very susceptible with
change of environment and very easy to disturb. Furthermore local government has
planned to develop this area become tourism area. This condition should be considered
by stakeholders to split the differences between power station activity and conservations
of environment in order to develop the best regional planning strategy.This condition
can be recommended to the stakeholders and decision makers to be considered in order
to arrange regional planning strategy based on environmental condition. For example do
some monitoring of coral reef and sea grass quality and condition in Popole Island and
Environmental Sensitivity Index Assessment Using Formosat-2 Satellite
In Labuan Coastal, Banten
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Karang Kebua Island, or make good quality of waste water management process in
PLTU Labuan.
Meanwhile, Karang Kebua Island could be polluted from pollutant that distributed
from industrial and tourism area in north part through current system distribution
(numerical model result). Furthermore, from current pattern (Figure 6) can be seen
clearly that this current flow throughout coastline area with shallow bathymetry in
Pagelaran and Panimbang sub district. This is also one of serious problems because
pollutant can be mixed with mud and it will hard to remove naturally. Whereas there are
many important places in coastline area for planting area and settlement. If pollutant
mix together with mud materials, so that the water quality could change. This condition
can be recommended to the stakeholders and decision makers to do some continuous
monitoring especially for water quality monitoring in two sub district.
Figure 8. Environmental Sensitivity Index Map (source: data processing result)
IV. CONCLUSIONS
1. Sensitive areas were located in Popole Island and Karang Kebua Island. These areas
are the most susceptible coastal area concern with pollutant and need high
awareness to protect this area from pollutant in order to avoid adverse consequences.
Land activity from power plant outlet can produced thermal pollutant that might
give impact to the surrounding environment especially to Popole Island. Changes of
water quality could give destructive impact to the local ecosystem of coral reef and
sea grass in this Island. Therefore plan of local government to develop this area
become tourism area for snorkeling and diving might be misallocated.
2. Average sensitive area were located in Pagelaran sub district, Panimbang sub district
and north part of Labuan sub district. These areas also have high potential to be
polluted especially in area dominated by mud material because pollutants can be
mixed and hard to remove naturally. Current circulation could bring pollutant from
Industrial city (Cilegon area) & tourism resort (Carita & Anyer area) throughout
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coastline area. This is very high risk condition because pollutant could be mixed
very well with mud material in shallow bathymetry.
3. Less sensitive area were located in southern part of Labuan sub district and
Liwungan Island. This means that these areas are the most unsusceptible coastal
area concern with pollutant. But Several locations in Labuan coastal area could be
already misallocated concern with pollutant source and distribution in this area.
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