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Sustinere
Journal of Environment and Sustainability
Volume 4 Number 3 (2020) 189-204
Print ISSN: 2549-1245 Online ISSN: 2549-1253
Website: https://sustinerejes.com E-mail: sustinere.jes@iain-surakarta.ac.id
RESEARCH PAPER
The impact of Cirebon coal-fired power plants on
water quality in Mundu Bay, Cirebon Regency
Millary Agung Widiawaty1, Nurhanifah1, Arif Ismail1
*
, Moh. Dede2
1Departement of Geography Education, FPIPS, Universitas Pendidikan Indonesia, Indonesia
2Master Program on Environmental Science, Postgraduate School, Universitas Padjadjaran, Indonesia
Article history:
Received 22 June 2020 │ Accepted 5 October 202 0 │ Available online 31 December 2020
Abstract. The presence of Cirebon coal-fired power plant I and II caused negative effects to
coastal morphology and the quality of marine waters. This also have negative impacts to the
fisherman around that sea. This study aims to examine the impact of the Cirebon coal-fired
power plant on the water quality of Mundu Bay, Cirebon Regency. Water quality is
determined based on total suspended solids (TSS), sea surface temperatures (SST),
chlorophyll-A, and salinity in the range 1999 – 2019. Data collection was carried out using
satellite imagery of Landsat-5 TM, Landsat- 7 ETM+, and Landsat-8 OLI verified with in-situ
field measurements, Sentinel-2 A MSI, and MODIS Aqua imageries. Changes in water quality
due to the infrastructure of the two power plants are known through the Mann-Whitney U-
Test and Spearman’s correlation analysis. This research shows that two Cirebon coal-fired
power plant has a significant effect on changes in the quality of Mundu Bay waters. Changes in
water quality are shown by a significant increase in TSS concentrations and SST values
accompanied by a decrease in chlorophyll-A levels and salinity levels. Changes in the quality
of these waters also disrupt marine biota habitat and cause fishermen in around are difficult
to get the ideal catchment yield.
Keywords: Cirebon steam power plant; Mundu bay; remote sensing; water quality
1. Introduction
Development is process-oriented towards fulfilling the needs of human life and livelihood
on Earth. Although development is essentially anthropocentric, it demands the preservation of
environmental carrying capacity to prevent many disasters and destructions (Abdullah, 2017).
In energy sector, the development to provide adequate energy have multiplier capabilities and
can drive diverse sectors (Aissa & Hartono, 2016). The efficiency of energy changes can be
viewed from the entropy such as electrical power output and heat released into the
environment, along with the various wastes it produces (Levine & Kendall, 2006; Xu et al., 2020).
Indonesia has abundant natural resources for developing energy such as wind, sunlight,
geothermal, and ocean current. However, it still experiencing problems in fulfilling electricity,
whereas the Indonesian government has targets to realize an electrification ratio of up to 99.9
*
Corresponding author. E-mail: arifismail@upi.edu
DOI: https://doi.org/10.22515/sustinere.jes.v4i3.114
SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204 190
percent by 2020 (Legino et al., 2019). In order to accelerate the fulfillment of electricity for
household and industrial needs, the Government launched a 35,000 mW power plant
development program by 2028 – after withdrawing from its previous target in 2019 (Untsa,
2017). The goal of fulfilling electrical energy in a short time causes the use of non-renewable
resources, especially coal-fired power plant, inevitable (Cahyadi, 2011; Yang et al., 2019). This is
evidenced by the construction of coal steam power plant projects in several regions in Java in
order to fulfill the increasing electrical energy needs.
The coal-fired power plant presences are an effort to create market share for the domestic
mining industry, considering that Indonesia is main producer of coal commodities in the world
(Hudaya & Madiutomo, 2019; Rosyid & Adachi, 2016). In addition, coal-fired power plants can be
built more easily and placed closer to users after going through various suitability studies, thus
production costs are relatively cheaper. Pragmatically, the construction of a coal-fired power
plant is a surefire solution to fulfill the electrical energy needs. Even though when examined
carefully, the coal-fired power plant operation in the long term also contributes to
environmental impacts such as decreasing the quality of water, air and land which will have
implications for socio-economic conditions (Dede et al., 2020; Ha-duong et al., 2016; NRDC,
2014). Operational cases of the coal-fired power plant which has helped to change the quality of
the environment and socio-economy around it are Cirebon coal-fired power plant. The power
plant that was built in the early 2000s known as the PLTU Cirebon I was able to provide 660 mW
of energy to support the fulfillment of industrial and household needs in the western region of
Java (Prima, 2018).
Although PLTU Cirebon claimed to be a pioneer of clean coal technology, the construction
and operation of the coal-fired power plants in a coastal area will change the coastal landscape,
air, and water quality (Choi et al., 2012; Kumar et al., 2013). It has implications for decreasing
catches, as well as causing fishermen to decrease in profit margins due to the greater cost to
reach the ideal waters for fishing. This problem also caused protests from the surrounding
community towards PLTU Cirebon I, although the results remained nil and continued with the
presence of second coal-fired power plant (PLTU Cirebon II). At present, Mundu Bay is an open-
access resource that has experienced a tragedy of the commons as shared resources by many
parties. As a result, Mundu Bay has used excessively and ignored the balance of the ecosystem,
especially if monitoring its impact not continuously. There is an assumption that the presence of
Cirebon coal-fired power plant does not have negative implications on the environment thus
insistence to fulfill energy needs also encourages the development of similar infrastructure in
Cirebon namely PLTU Cirebon II (Muhaimin et al., 2015).
In 2015, the government built PLTU Cirebon II (capacity 1000 mW) due to the large
demand for electricity to drive development in Ciayumajakuning (Dewanto, 2016). The second
coal-fired power plant will be full operation in 2022. Issue of decreasing the ecosystem quality
continues to strengthen when fishermen found dead marine biota with body parts contaminated
with pollutants from the coal-fired power plants. This problem eventually stopped without
continued investigation and due process, due to conflicting agreements. Dualism of information
is biased and affect decision-makers, hence the commitment to improve the water quality at
Mundu Bay needs to be reviewed with other perspectives using remote sensing and geographic
information systems as part of environmental management (Elhag et al., 2019; Ruslisan et al.,
2016). Multi-spectral satellite imagery has multiple sensors that can be adjusted to the user
191 SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204
needs and has a fairly short temporal resolution are useful as input datasets for GIS (Dede et al.,
2019; Yan et al., 2015).
Remote sensing imagery can detect changes in temperature, dissolved oxygen, sediment
loads, oil spills, waste concentrations, and other components accurately (Hafeez et al., 2018;
Lubis et al., 2017; Widiawaty et al., 2020). The integration of remote sensing and GIS to see the
impact before and after the construction-operation of the coal-fired power plant can be viewed
from many parameters of water quality. The accuracy of remote sensing data will be higher if
accompanied by in-situ field measurements or compared to other satellite imagery data
(Murayama, 2012). In contrast to previous studies which examined one or two parameters of
water quality due to the construction of power plants, this study seeks to assess total suspended
solids (TSS), sea surface temperature (SST), phytoplankton (chlorophyll-A), and sea surface
salinity (SSS or SS-Sal) levels in before-after the construction-operation of Cirebon coal-fired
power plants (Miara et al., 2018; Rosen et al., 2015; Widyarani et al., 2019). Research on the
development and operational impacts of the Cirebon coal-fired power plants is a need to
respond to the information which circulating in the public given its considerable influence on the
environment because it concerns sustainability and community livelihood. Based on these
problems, this research seeks to uncover the impact of Cirebon coal-fired power plants on the
water quality of Mundu Bay in Cirebon Regency, West Java, Indonesia.
2. Research Method
This research was conducted in the Mundu Bay around the PLTU Cirebon I and II sites. The
area of interest (AOI) (Sanchez, 2014; Widiawaty & Dede, 2018).
Figure 1. Research location shows the site of Cirebon steam power plan
SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204 192
2.1. Data Acquisition
The main data in this study came from secondary sources. To increase validity and reduce
information bias, secondary data used come from different sources - triangulation using other
secondary data and primary sources (Fielding, 2012; Shelby & Vaske, 2008). The selection of
data sources is also adjusted to the purpose and efficiency of information acquisition, in this
study most of the secondary data came from the United States Geological Survey (USGS),
European Space Agency (ESA), and National Aeronautics and Space Administration (NASA)
(Table 1).
Table 1. Satellite imageries for analysis
Variables
Unit
Imageries
Years
Path/Row
Level
Total suspended
solid (TSS)
mg/l
Landsat-8 OLI (USGS)
Landsat-7 ETM+ (USGS)
Sentinel-2 MSI (ESA)
2014, 2019
1999
2019
121065
121065
T49MBN
L1
L1
L1
Sea surface
temperature
(SST)
°C
Landsat-8 OLI (USGS)
Landsat-7 ETM+ (USGS)
MODIS Aqua “MYD11” (NASA)
2014, 2019
1999
2019
121065
121065
H28V09006
L1
L1
L1
Phytoplankton
concentration
(Chlorophyll-A)
mg/m3
Landsat-8 OLI (USGS)
Landsat-7 ETM+ (USGS)
Sentinel-2 MSI (ESA)
2014, 2019
1999
2019
121065
121065
T49MBN
L1
L1
L1
Sea surface
salinity (SSS)
Psu
Landsat-8 OLI (USGS)
Landsat-7 ETM+ (USGS)
Sentinel-2 MSI (ESA)
2014, 2019
1999
2019
121065
121065
T49MBN
L1
L1
L1
This research not only uses secondary sources, but also uses primary sources through field
observation and in-situ measurements in 2019. The number of sampling points for each variable
varies according to the needs and abilities of researchers (see Appendix). In this study, only
chlorophyll-A samples were not tested in-situ due to time and cost constraints, so the tests were
only based on comparison of remote sensing data from two different sensors. When referring to
datasets used, the main data was based on the availability on before and after the Cirebon coal-
fired power plants which ranges from 1999-2019. Therefore, data from Landsat series images
are the main data in this study. The difference in variables and characteristics for each object on
the surface of the earth causes different processing algorithms to produce the necessary
information. Before entering these algorithms, satellite image data requires preprocessing steps
through geometry, atmospheric, and radiometric corrections (Widiawaty, 2019; Young et al.,
2017). In this study, the digital number (DN) on each band of satellite images is converted into
reflectance value using the DOS1 method. The satellite image processing algorithm to obtain
information related to the research variables is presented in Table 2 – These algorithms are
suitable for dynamics analysis of the tropical environment in Indonesia which has high rainfall
and temperature (megathermal) with the monsoons influence.
2.2. Data Analysis
This research is classified as a quantitative approach because variables of water quality are
presented in numerical descriptions and statistical analysis (Eyisi, 2016). Disclosure of changes
in water quality is done by analyzing secondary data which are combined with a primary data
from field measurements and other data sources as validators in order to answer research pro-
193 SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204
Table 2. Algorithms for processing satellite data
Variables
Dataset
Algorithms
TSS
Landsat
series and
Sentinel-2
Parwati and Purwanto (2017)
TSS(mg/l) = 0.6211 × (7.9038 × Exp (23.942 × RBρ)0.9645
Where RBρ is the BoA reflectance value of the red band.
SST
Landsat
series and
MODIS
Nurdian et al. (2020),
Lλ = × +
T = K2
ln K1
Lλ+1
Where Lλ is the spectral radiation value of ToA, ML as the thermal band
rescaling factor, Qcal is the total heat energy, AL shows the value of the
thermal band constant, T is the temperature value in Kelvin units, and
K2 / K1 as the calibration constant obtained from the metadata.
Chlorophyll-A
Landsat
series and
Sentinel-2
Nuriya et al. (2010)
(mg/m3) = 0.2818 NIRρ + SWIRρ
ρ
Where NIRp is the BoA value of near infrared band, shortwave infrared
band, and red band.
SS-Sal
Landsat
series and
Sentinel-2
Ladya et al. (2015)
L(psu) = - 42.72 × ((-61.182 × B3 + 79.129 × B2 - 34.022 × B + 4.865) +
32.702)
Where B is the blue chromatization of the divided blue band blue band
+ green band + red band. All bands in the equation use BoA reflectance
values.
blems (Johnston, 2014). In this study, the data sample used saturated sampling which covered
all Mundu Bay waters in accordance with AOI. Data from the water quality algorithms are then
tested for validity by comparing the results from two different satellites in the same year.
Validity test using the Spearman Rank correlation (Equation 1) because all the results of the
processing have non-normal distribution (Setiawan et al., 2019). Data prove to be valid as
indicated by the minimum significance value of 0.05, thus analysis can be continued using the
Mann-Whitney U-Test as presented in Equations 2 (Dadson, 2017; Milenovic, 2011; Sanyé-
Mengual et al., 2018). Details about the data analysis stage is presented in Figure 2.
(1)
Where ρ indicates the level of correlation (r-value), n the amount of data observed, and d is the
difference value of paired data. Correlation is significant if the ρ > ρ-table at a confidence level of
95 to 99 percent.
(2)
Where U is the value of the Mann-Whitney test results, n indicates the number of samples
for each dataset, and R as the number of ranks for each dataset. Significant difference (take the
lowest value from Ui or Ui+1) if U < U-table.
SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204 194
Figure 2. Research scheme and data analysis
3. Results and discussion
The presence of coal-fired power plants is expected to increase electricity capacity. PLTU
Cirebon I which began operating in 2011 has a similar goal to support many economic sectors in
Java. Since the establishment of the coal-fired power plant, the local community has felt various
changes to the environment and socio-economic conditions because the fishermen's yield is
decreased significantly compared to before the construction and operation of power plant. This
is due to the environmental impact caused by the coal-fired power plant on the water quality
and marine biota (Myllyvirta & Chuwah, 2017).
3.1. Water quality in Mundu bay
When compared with data in 1999-2014, the presence of PLTU Cirebon I was able to
increase the TSS level by an average of 18.75 mg/l (156.25 percent) (Figure 3) . This condition
was followed by a decrease in SST of 4.68 oC to below 18oC, thus disrupting the growth and
breeding of phytoplankton as primary productivity for waters (Figure 4). Even the average
levels of phytoplankton (chlorophyll-A) decreased by more than 50 percent from 1999-2014
(Figure 5). PLTU Cirebon I also caused a decrease in salinity (SS-Sal) of 17.6 psu thus complaints
from the fishing communities around the coal-fired power plants occur due to changes in the
quality of the water that is declining (Figure 6), ecosystem balance is disrupted and has an
impact on the decline in yield catches due to pollutant compounds increasing as a limiting factor,
in addition to restrictions on access to certain water spaces in Mundu Bay (Nurhasanah, 2017;
Tarunamulia et al., 2019).
Despite changes in water quality that affect the socio-economic conditions of the
surrounding community, the electricity supply program is continuing. The PLTU Cirebon II
development also contributed to changes in the water quality of Mundu Bay, especially in
increasing TSS levels and decreasing salinity. The presence of PLTU Cirebon II did not change as
much as PLTU Cirebon I, even though the TSS levels rose more than three times compared to
before the presence of two coal-fired power plants (see Table 3). Besides the numerical
195 SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204
description system, changes in the water quality in Mundu Bay can also be viewed from a spatial
perspective. Before PLTU Cirebon I existed, precisely in 1999, sea waters close to the mainland
had low TSS levels, were clear and sunlight was able to penetrate to the bottom of the waters -
except in areas close to river estuaries (Gholizadeh et al., 2016; Widiawaty et al., 2020). Socio-
economically, this condition has enabled fishermen to catch various species of marine animals
such as fish, shrimp, crab, and shellfish. The unpolluted sea which is relatively close to
traditional harbors also reduced operational cost. The presence of Cirebon coal-fired power
plants along with anthropogenic landforms that stretch to the waters of Mundu Bay also changed
the spatial distribution of TSS. Ironically, it is difficult to find proper seawater quality with low
TSS near the coast now after the coal-fired power plants exist. Even in 2019 - after the
construction and operation of the PLTU Cirebon II – waters with low TSS levels cannot be found
up to a distance of five kilometers from the coast (Figure 3).
Figure 3. TSS distribution in Mundu bay 1999-2019
In contrast to other water quality variables, SST has increase and decrease after the coal-
fired power plants operation (Figure 4). During the construction and operation of the PLTU
Cirebon I, SST distribution changed to be lower. However, this condition has changed again after
the construction and operation of the PLTU Cirebon II, where SST has increased again with a
distribution pattern and values similar to those in 1999 (Figure 4). The returns of SST in its
previous form did not mean as recover for the water quality in Mundu Bay because habitat
suitability for marine-aquatic ecosystems is not only determined by temperature changes (Choi
SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204 196
et al., 2012). The increase in SST is hypothetically caused by thermal water discharge from the
power plant as well as increased water turbidity due to TSS caused by PLTU Cirebon I operation
in 2014.
Table 3. Water quality dynamic in Mundu bay from satellite imageries
Variables
Year
Min
Max
Mean
Std. Dev.
TSS (mg/l)
1999
6.75
4.95
12.00
11.13
2014
7.42
1143.6
30.75
27.57
2019
21.25
270.59
49.49
30.18
SST (oC)
1999
20.96
26.28
22.34
0.44
2014
16.34
20.35
17.66
0.59
2019
21.94
25.83
23.60
0.52
Chlorophy-A
(mg/m3)
1999
0.14
1.83
0.37
0.15
2014
0.09
1.43
0.18
0.08
2019
0.14
1.52
0.20
0.08
SS-Sal
(psu)
1999
5831.43
5882.63
5871.65
11.45
2014
5821.73
5880.13
5854.05
11.57
2019
5798.38
5856.36
5836.53
7.88
Figure 4. SST distribution in Mundu bay 1999-2019
197 SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204
Figure 5. Chlorophyll-A distribution in Mundu bay 1999-2019
Figure 6. SS-Sal distribution in Mundu bay 1999-2019
SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204 198
TSS was increasing in Mundu Bay and coming closer to the mainland, it decreasing
chlorophyll-A at the same time. In 1999, chlorophyll-A was abundant from the coast - less than
one kilometer. This condition persisted until the presence of chlorophyll-A decreased due to the
increasing TSS after the operation of PLTU Cirebon in 2014, thus Mundu Bay has low primary
productivity (Figure 3 and Figure 5). The spatial distribution of chlorophyll-A has a similar
pattern with surface salinity levels, its distribution continues to decrease in near the coastal area
(Figure 6). Despite SST rising, salinity value actually continues to decrease due to reduction in
salt compounds and substituted by TSS and freshwater from rivers and rainfall (Fang et al.,
2010). In addition, the salinity changes can also be caused by thermal water waste, it is able to
decipher the salt compounds bonding. Reduced salinity means reducing the ideal habitat for
marine biota and decreasing the yield of salt-embankment.
Figure 7. Histogram of water quality changes in Mundu bay
The spatial distribution of the Mundu Bay from 1999-2019 resulted in ecosystem changes
that were not favorable for the community, the changes of these variables have influenced for
the aquatic ecosystem (Figure 7). In the long term, the lack of supervision and inaccurate
environmental management of coal-fired power plants will lead to a bad policy that triggers
poor execution for the community and Mundu Bay as open ecosystems. Whereas fisheries and
marine activities are the basic sectors that have a multiplier effect on the socio-economic in
Cirebon, it has a strong influence on other i.e industry and service sectors (Dede et al., 2016).
3.2. Impact of coal-fired power plant on water quality
To know the impact of Cirebon coal-fired power plants on water quality begins using
statistical tests. Data validity testing shows that the information from the Landsat series with
other satellite data was declared feasible. This result shows the highest correlation in TSS, even
though the correlation value for these variables is significant with p-value ≤ 0.05 (see Table 4)
and its suitable for further analysis (Nudian et al., 2019). Meanwhile, when we referring to data
from in-situ measurements for TSS, SST, and salinity also show information from multi-spectral
satellite imagery was valid. Table 5 shows that the TSS has the highest correlation. Thus both the
validity test with other imageries and in-situ samples of these variables are declared eligible for
environmental impact analysis by coal-fired power plants.
Changes in the aquatic environment quality due to Cirebon coal-fired power plants are
known from the Mann-Whitney U-Test using Landsat series imagery data for the periods on
before and after of infrastructure development. The test shows environmental quality changes
as indicated by high U-value for all variables, it indicates significant difference in the Mundu Bay
ecosystem from 1999 to 2019. The highest U-value come from chlorophyll-a which means an
199 SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204
extreme changes in food chain of aquatic environment - the phytoplankton population continues
to decrease and detrimental to the fishing community. Based on the results, we known that the
development and operation of Cirebon coal-fired power plants have significant impact on the
water quality (Table 6).
Table 4. Validation of water quality from inter-satellite imageries
Variables
r-value
Sig.
Validity
TSS
0.893
0.000
Valid
SST
0.386
0.000
Valid
Chlorophyll-A
0.499
0.000
Valid
SS-Sal
0.767
0.000
Valid
Table 5. In-situ measurement validation for satellite imagery algorithms
Variables
n (point)
r-value
Sig.
Validity
TSS
8
0.778
0.023
Valid
SST
26
0.437
0.026
Valid
SS-Sal
26
0.437
0.026
Valid
Table 6. U-Test result of water quality in before and after the two steam power plan exist
Variables
Mann-Whitney U-value
Sig.
Information
TSS
3645336.00
0.000
Different and significance
SST
12498092.00
0.000
Different and significance
Chlorophyll-A
20315663.50
0.000
Different and significance
SS-Sal
2813980.50
0.000
Different and significance
Besides has negative impacts on coastal ecosystems and its surrounding social systems,
changes in water quality variables also interact with each other (Table 7). Increasing TSS
triggers SST , chlorophyll-A, and salinity significantly decrease. In Mundu Bay, TSS plays a vital
role in this ecosystem. TSS increasing is caused by the wharf (jetty) of coal-fired power plants,
jetty able to changing the flow of sea current and able to accumulated sediments (Widiawaty et
al., 2020). TSS increasing can be caused by the combustion dust and coal debris which carried in
run-off water (Shahzad Baig & Yousaf, 2017).
Table 7. Correlation between variables of water quality
Variables
TSS
SST
Chlorophyll-A
SS-Sal
TSS
1
-0.305
-0.323
-0.451
SST
-0.305
1
0.352
0.494
Chlorophyll-A
-0.323
0.352
1
0.214
SS-Sal
-0.451
0.494
0.214
1
SUSTINERE: Journal of Environment & Sustainability, Vol. 4 Number 3 (2020), 189-204 200
Figure 8. Jetty of the Cirebon steam power plant I
The Cirebon coal-fired power plants have a direct impact on the sustainability of the
ecosystem and hampered the economic activities of the surrounding which is predominantly
dependent on the sea. Before the PLTU Cirebon II was built, people's complaints related to
income from fishing were not heard because it was still sufficient to life needs. Currently, the
presence of Cirebon coal-fired power plants have caused coastal landscape change and
increasing waste accumulation in Mundu Bay. This condition is not optimal for marine biota
growth and brings detrimental to fishermen yields. In addition, the waste material also has the
potential to contain heavy metals which can cause health problems in the future (Miara et al.,
2018). Even though the construction and operations have many negative impact on the
environment, Indonesia's government has planning to build a coal-fired power plant near
Mundu Bay as known as PLTU Cirebon III.
4. Conclusion
The Cirebon coal-fired power plants construction has met environmental requirements in
administrative document, but its negative impacts on the ecosystem and surrounding social
systems are still occurring. This study shows that the presence of coal-fired power plants has
significantly reduced water quality in Mundu Bay, its presence is able to change TSS, SST,
Chlorophyll-A, and salinity which interfere the marine biota growth and causing fishermen to
suffer losses. Water quality changes create a multiplier effect for economic activities depend on
marine biological resources. Stakeholders should be able to review environmental management
of Cirebon coal-fired power plants to meet sustainability criteria. Based on this study, satellite
imageries are effectives to assess the changes of aquatic environment. In the future, the use of
remote sensing technology, both airborne and satellite, can continue to be optimized for
environmental monitoring and auditing.
Acknowledgement
Thank you for the local people who help us to get water samples and willing as informants.
Special thanks for Geosac’s board of jury which chosen our manuscript as the best paper.
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Appendixes
In-situ measurement of TSS and remote sensing (RS) data.
Sample
In-situ (mg/l)
RS (mg/l)
Sampel
In-situ (mg/l)
RS (mg/l)
TSS-1
59
52.02
TSS-5
331
241.58
TSS-2
68
91.38
TSS-6
200
205.05
TSS-3
68
33.85
TSS-7
19
60.86
TSS-4
89
83.51
TSS-8
79
70.07
In-situ measurement of SST and remote sensing (RS) data.
Sample
In-situ (oC)
RS (oC)
Sampel
In-situ (oC)
RS (oC)
SST-1
34
36.98
SST-14
35
35.45
SST-2
33
34.21
SST-15
36
34.96
SST-3
34
35.00
SST-16
35
34.47
SST-4
35
36.16
SST-17
34
33.37
SST-5
33
34.85
SST-18
36
34.87
SST-6
34
35.39
SST-19
35
35.24
SST-7
34
34.77
SST-20
34
35.69
SST-8
35
35.48
SST-21
34
34.01
SST-9
34
33.60
SST-22
35
36.35
SST-10
35
34.87
SST-23
35
36.62
SST-11
34
33.97
SST-24
37
35.82
SST-12
34
34.73
SST-25
34
35.64
SST-13
36
35.74
SST-26
36
35.44
In-situ measurement of sea surface salinity (SS-Sal) and remote sensing (RS) data.
Sample
In-situ (mg/m3)
RS (psu)
Sampel
In-situ (mg/m3)
RS (psu)
Sal-1
0.001
5858.862946
Sal-12
0.012
5856.599713
Sal-2
0.002
5859.037657
Sal-13
0.013
5868.952353
Sal-3
0.003
5860.415772
Sal-14
0.014
5861.491613
Sal-4
0.004
5861.309229
Sal-15
0.015
5851.623825
Sal-5
0.005
5856.306199
Sal-16
0.016
5850.633583
Sal-6
0.006
5862.870168
Sal-17
0.017
5850.769414
Sal-7
0.007
5866.096681
Sal-18
0.018
5856.066840
Sal-8
0.008
5859.634657
Sal-19
0.019
5849.465571
Sal-9
0.009
5858.520417
Sal-20
0.020
5849.886763
Sal-10
0.010
5863.905229
Sal-21
0.021
5857.246186
Sal-11
0.011
5857.915128
