ANALYSIS OF CHANGES IN MANGROVE AREA AND …

Journal of Environmental Engineering & Sustainable Technology JEEST Vol. 07 No. 02, November 2020, Pages 1-17 http://jeest.ub.ac.id

P-ISSN:2356-3109 E-ISSN: 2356-3117 1

ANALYSIS OF CHANGES IN MANGROVE AREA AND SEDIMENTATION ON

THE INDAH KAPUK BEACH USING REMOTE SENSING DATA

Umi Zakiyah1* , Mentari Ramadhanti

2 and Etty Parwati

3

1Lecturer of Aquatic Resources Management Study Program 2Student of Aquatic Resources Management Study Program

* Correspondence author

*Correspondecne Email: [email protected]

ABSTRACT

Currently the construction of reclamation

in Jakarta Bay being carried out on several

islands that have been approved by the

Government of Indonesia and located nearby

the Mangroves forests ecosystem which

always inundated by seawater and are affected

by tides. The purpose of this study were

analyzing the changes in the mangrove

ecosystem area due to the changes in Total

Suspended Solid (TSS) based sedimentation

and the effect of hydro-oceanography factors

on the TSS. This research was conducted

using a literature study, processing the

LANDSAT OLI images for the analysis of

mangrove changes, TSS analysis, and analysis

of the effect of hydro-oceanography on TSS

within the years of 2013 to 2020. The results

of this study indicate that the area of mangrove

forest on the coast of North Jakarta is

enlarging by 3-5 ha/year, especially in the

reclamation island area due to the process of

sedimentation which is influenced by hydro-

oceanography. High sedimentation can be

shown from the high value of Total Suspended

Solid (TSS) in the waters. The TSS values

processed by the satellites images also showed

a significant increase during these years

between 2013 to 2020 except December 2018

experienced the lowest value. While the

hydro-oceanographic factor has lesser effect

on the TSS value compare to mangrove

ecosystem in the study area.

Keywords: Change in mangrove area,

Sedimentation, hydro-oceanographyc factor,

Landsat OLI images, TSS

1. INTRODUCTION

Mangrove forest is a typical tropical

coastal vegetation community, some area are

covered by mud or sandy mud substrates.

According to Rahmawaty (2006), mangrove

forests can be found in 118 countries in the

world with a total area of about 137,760 km2.

Indonesia as one of the countries that has the

largest mangrove forest in the world, the area

of mangrove ecosystems in Indonesia reaches

75% of the total mangroves in Southeast Asia,

and about 23% of the world's with 45 true

mangrove species from 75 species in the

world.

Other than, Lasibani and Kamal (2010),

that has stated that the benefits of mangrove

ecosystems related to physical functions such

as wave dampers and storm winds, coastal

protection from abrasion, tidal waves,

tsunamis, mudguards and sediment traps and

can neutralize water pollution to a certain

extent, Rahmawaty in Dien (2016), added that

mangrove ecosystems maintain a stable

coastline and sedimen and it means protect the

existing biota dwelled. Furthermore, Besperi

(2011), stated that mangroves are plants in the

form of shrubs and trees with respiratory

supporting roots, that can catch mud and cause

sedimentation.

Rusmendro (2008), stated that mangrove

sediments have natural characteristics and can

be used as a benchmark to see its potential and

productivity. Furthermore, Bates and Jackson

(1987), determined that sediment is a solid

material, derived from nature that form layers

on the earth's surface. Most of sediments in

mangrove ecosystems are different however

the majority will consist of mud or sandy mud

(Nento et al., 2013)

The sedimentation that occurred in

mangrove ecosystem can caused changing in

Journal of Environmental Engineering & Sustainable Technology Vol. 07 No. 02, November 2020, Pages 1-17

2 P-ISSN:2356-3109 E-ISSN: 2356-3117

the coastline (Hang Tuah, 1991). Meanwhile Fandeli (2011), stated that the shoreline or

shoreline can change depending on the sea

level which always experiences highs and

lows. This changes in the area of mangrove

ecosystem can be traced and observed using

remotely sensed data (Paharuddin, 2011),

since it has been able to provide

data/information on natural, land and marine

resources regularly and periodically. The

availability of satellite images data in digital

form allows for quantitative and consistent

computer analysis.

Indah Kapuk beach is one of the beaches

in North Jakarta which has a fairly extensive

mangrove forest with a beautiful stretch of

beach. Masriah and Mujahid (2011), stated

that there were transition of mangrove areas

into residential areas, condominiums, business

centers, recreation and golf courses in the

Pantai Indah Kapuk and this was done without

considering the condition of the mangroves.

According to Marfai et al., (2015) the

occupation pressure on mangrove forest areas

is increasing along with the increase in

population nearby. The existing direction of

development in the 1985-2005 National Long

Term Development Plan document or what is

referred to as REPELITA VI and revealed

through Presidential Decree no. 52 of 1995

explains to increase the acceleration of

economic growth that includes reclamation.

According to Law no. 27 of 2007 reclamation

is an activity of stockpiling or drying in a

location of marine waters to utilize land

resources to create a new land. Large-scale

marine reclamation activities can be observed

in island countries such as Japan, Korea, and

Singapore, as well as non-island countries

such as the Netherlands, Germany, and the

United States (UNAOO, 2006). Reclamation

activities will certainly have an impact as well

on ecological resilience during the process.

And as stated by (Peng et al., 2013) an

increase in turbidity in the water column due

to dredging and stockpiling activities in the

form of nutrients, heavy metals, and

suspended solids can disrupt biota, the

ecosystem in it, and humans who depend on

that environment. According to the Decree of

the Minister of the Environment no. 51 /2004

concerning Seawater Quality Standards that

the level of turbidity due to suspended solids

in the water column should not exceed 20

mg/l. Therefore, there is a need for monitoring

activities on reclamation activities that

assumed to have negative impact to the

mangrove ecosystem area. The objectives of

this research were to determined the changes

in mangrove ecosystem area based

sedimentation, the existing TSS values due to

the reclamation activities nearby as well

observed the hydro-oceanographic factors

involved (Jasmin et al., 2020).

2. MATERIALS AND METHOD

This research is quantitative descriptive

method using remotely sensed data of Landsat

8 - OLI satellite imagery in the period of 2013

till 2020 as the main data,to determine the

changes in mangrove area and the TSS values

of Indah Kapuk bay. These satellites imagery

was obtained from Indonesian National

Institute of Aeronautics and Space Agency.

Meanwhile, the hydro-oceanographic data

such as tides, TSS values of the same area

were obtained from the Jakarta Environment

Agency (JEA) and the Jakarta City Park and

Forest Service (JCPFS)and were processed

quantitaively, supported by literature studies.

The existing data were mainly data of the area

of mangrove forest located in Indah Kapuk

bay as shown in (Figure 1). The satellites data

were validated with RMSE based of field data

that were obtained from the Agencies.

Zakiyah et al., Analysis Of Changes In Mangrove Area…

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Figure 1. Research Location

3. RESULT AND DISCUSSION

3.1 TSS Detection Result from Landsat 8

OLI Satellite Imagery Processing

The results of TSS values that based

on the satellite imagery processing, in 2013

are shown in Figure 2(a,b) that the

distribution of Total Suspended Solid in July

has the highest TSS content with a value of

180-680 Mg/l and the lowest at 22-69 Mg/l. In

2014 the results of satellite imagery TSS data

processing shown in Figure 3(a,b,c) show that

the distribution of Total Suspended Solid in

April had the highest TSS content with a value

of 358-1,216 Mg/l and the lowest at 20-34

Mg/l. In 2015 the results of satellite imagery

TSS data processing shown in Figure 4(a,b)

show that the distribution of Total Suspended

Solid in May had the highest TSS content with

a value of 57-147 Mg/l and the lowest at 20-32

Mg/. In 2016, the results of satellite imagery

TSS data processing shown in Figure 5

(a,b,c) show that the distribution of Total

Suspended Solid in January has the highest

TSS content with a value of 283-851 Mg/l and

the lowest at 37-101 Mg/l.

In 2017, the results of processing TSS

satellite imagery data in 2017 shown in

Figure 6(a,b,c), show that the distribution of

Total Suspended Solid in May had the highest

TSS content with a value of 119-387 Mg/l and

the lowest at 26-65 Mg/l. In 2018, the results

of satellite imagery TSS data processing in

2018 shown in Figure 7(a,b,c), show that the

distribution of Total Suspended Solid in

March had the highest TSS content with a

value of 74-185 Mg/l and the lowest at a value

of 30-50 Mg/ In 2019 the results of satellite

imagery TSS data processing shown in Figure

8(a,b), show that the distribution of Total

Suspended Solid in May had the highest TSS

content with a value of 83-191 Mg/l and the

lowest at 27-40 Mg/.


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Figure 2(a,b). Year 2013.

Figure 3(a,b,c). Year 2014.


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Figure 4(a,b). Year 2015.



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Figure 6 (a,b,c). Year 2017.



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Figure 8 (a,b). Year 2019.

According to DHI Environment (2011),

Jakarta Bay is experiencing erosion in several

areas such as Tanjung Pasir, Sunda Kelapa

Harbor, Ancol Beach and Cilincing Beach. The

current speed around the reclamation island

slows down while in other places the current

speed increases, causing erosion on the coast

of Jakarta. Some of the changes that may occur

are changes in current patterns, erosion and

sedimentation, as well as the composition and

abunandce of biota living in the reclaimed

aquatic environment. Another impact of

reclamation efforts is the increased turbidity of

the waters (Bambang et.al., 2012).

3.2 TSS Detection Result from Landsat 8

OLI Satellite Imagery in 2014

The results of processing TSS satellite

imagery data in 2014 shown in the show that

the distribution of Total Suspended Solid in

April has the highest TSS content with a value

of 358-1,216 Mg/l and the lowest at 20-34

Mg/l. In August 2014, the highest TSS level

was in the 60-252 Mg/l grade, while the lowest

TSS level was 23-35 Mg/l. in October 2014 the

highest TSS level was 92-320 Mg/l, while the

lowest value was 44-63 Mg/l. When observed

based on the reclamation area of the Jakarta

Bay in April, the highest TSS content value

was due to the image results of the area with

high TSS levels being in the river near the

Mangrove Protected Forest. Some of the

changes that may occur are changes in current

patterns, erosion and sedimentation, as well as

the composition and abunandce of biota living

in the reclaimed aquatic environment. Another

impact of reclamation efforts is the increased

turbidity of the waters (Bambang et.al., 2012).

According to Djainal (2019), one of the

consequences of reclamation development

activities is sedimentation. Sedimentation that

is not dissolved in the water causes an

increase in Total Suspended Solid levels in

the water column. This has an impact on the

productivity of biological and physical

parameters in the waters. According to

research conducted by Puspasari et. al (2017),

there was a decrease in the index of

phytoplankton and macrozoobenthos diversity

in 2016 compared to 2014 in the Jakarta Bay

reclamation area. In addition, there was a

decrease in the parameters of salinity and

brightness in the same year and location. The

decline in the productivity of biological and

physical parameters in the reclamation area of

Jakarta Bay caused a decrease in fish catches

for the types of fishing gear types such as


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bagan tancap, sero, net rampus per kg per unit

per day

in 2014 compared to 2006.

3.3 Validation of Field Data with Satellite

Image Results

The results of TSS levels between image

processing and field data carried out by the

DKI Jakarta Provincial Environment Service

were carried out using a statistical approach

by extracting the results of TSS images by

entering the coordinates obtained from the

agency that shows at Figure 9 and Figure 10.

Based on the calculation of the Root

Median Square Error (RMSE) between the

image data and the DKI Jakarta

Environmental Agency data when the water

conditions are high tide, the value is 538.99%

and when it is low tide, the value is

170,3848%. According to Adamuthe (2017),

explaining that the smaller the number of

Root Median Square Error (RMSE) results,

the greater the level of accuracy. The RMSE

value obtained by this study has a much

different value from the research conducted

by Zulfikar and Eko (2017), which compared

the results of tidal data on the reclamation of

Jakarta Bay using data downloaded from the

BIG web with the same year and month as the

Environment Agency. In addition, this value

is much different from the comparison

between the downloaded data and the DKI

Jakarta Environmental Service data when the

water conditions are high tide.

Figure 9. TSS Observation Chart Satellite Image of DLH DKI Jakarta Coordinates.

Figure 10. DLH DKI Jakarta TSS Observation Graph.


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3.4 Current Conditions and Effects

The results of processing surface current

data in Jakarta Bay show that the current

velocity from 2013 to 2019 has varying speeds.

In Figure 11, it can be seen that the current

velocity in 2013 had an average speed of 0.39

m/s which was dominated by the direction

from the south and then deflected to the

northwest. Current velocity conditions at the

time of observation of TSS image recording in

Jakarta Bay reclamation, the maximum current

is 0.7 m/s, the minimum speed is 0.115 m/s,

and the average speed is 0.417 m/s.

Figure 11. Current Correlation Value of TSS

Image.

The Pearson correlation value shown at

Figure 11 by the analysis using the correlation

method showed the value 0.2. A positive

charge indicates a directly proportional

relationship between the current and the TSS

value. Meanwhile, the value of 0.2 is classified

as a very weak relationship classification.

Therefore, it can be interpreted that the

relationship between the current and the image

TSS value has a very weak direct proportional

relationship.

Figure 12. Current Regression Value of TSS

Image

The R-sq value shows by Figure 12 that

the influence of current on the TSS Image

value is 29.1574%. This is the same as the

research conducted by Gusman et al. (2013),

which states that currents affect the

accumulation of material in the western part

of the river mouth of the research location and

the distribution of TSS as a whole. Current

velocity has a significant effect on changes in

TSS if the water depth is shallow. This is

similar to the research conducted by Gusman

et al. (2013), which found station points with

high TSS values and current velocity and

shallow water depths. Meanwhile, in the

reclamation area of Jakarta Bay, the

maximum current speed only reaches 0.7 cm.

In addition, the influence of current in this

study emphasizes the changes in levels that

occur in the TSS value when the current

passes through that point. The formula is

obtained as shown in Figure 76. Based on this

equation, if there is a current velocity of 1

m/s, a TSS value of 38.58 Mg/L will be

obtained.

3.5 Tidal Conditions and Effects

The results of numerical calculations

using the Admiralty method, it can be seen

that the Jakarta Bay area has a Formzahl

number value of 5.3. When referring to the

classification of tidal types based on the

Formzahl number value according to

Rapengan (2013), Jakarta Bay has a single

daily tidal type (diurnal tides) which means

that in one day there is one high tide and one

low tide. The condition of tidal elevation at

the time of observation of TSS image

recording in Jakarta Bay reclamation that the

highest tide was 45.7 cm, the lowest low tide

was - 41.7 cm, and the average elevation was

-0.05069 cm.

TSS and Current

PValue Pearson

Correlation

R^2 STD

0.286099 -0.106620795 0.012775 27.5141

TSS Image and Field Data

PValue Pearson

Correlation

R^2 STD

0.225437 -0.128388344 0.0016466 29.1574


Figure 13. Tidal Correlation Value of TSS

Image

The Pearson correlation value shown by

Figure 13 the analysis using the correlation

method shows the number 0.044. A positive

charge indicates that there is a directly

proportional relationship between the tides and

the TSS value. Meanwhile, the value of 0.044

belongs to the classification of very weak close

relationship. Therefore, it can be interpreted

that the relationship between the wave and the

TSS value of the image has a very weak direct

proportional relationship.

Figure 14. Tidal Regression Value of TSS

Image

The Figure 14 shown that R-sq value

effect of tides on TSS Image is 0.19%. This is

different from the research conducted by

Manurung et al. (2017), which states that tides

have a significant effect on changes in TSS at

the research site. The most significant changes

in TSS occur when the water conditions recede

towards high tide. This difference is caused by

the condition of the research location

conductedby Manurung et al. (2017) coincides

with the river mouth. When conditions recede

towards high tide, there is a change in the

increase in water volume and currents caused

by the tide so that friction occurs between the

tidal current and the bottom of the water which

results in stirring of sedimentation in the water

column and when sea water rises and reaches

the crest, the speed will decrease so that in at

that time more TSS were released. In addition,

the input flow from the river that meets the

tidal current causes turbulence in the flow of

water so that the mixture at the bottom of the

water becomes stronger. In contrast to the

reclamation location of the Jakarta Bay with

tidal observation points far from the river

mouth and far from the mainland, so that the

tides have no effect on changes in suspended

cargo solids because changes in tidal elevation

do not cause stirring at the bottom of the

waters during low tide to high tide or vice

versa due to different levels of depth. In

addition, the effect of tides in this study

emphasizes the changes in levels that occur in

the TSS value when tides occur at that point.

The formula is obtained as shown in Figure 79.

Based on this equation, if there is a tidal

elevation of 1 m, the TSS value is 32,013

Mg/L.

3.6 Mangrove Detection Result from

Landsat 8 OLI Satellite Imagery

According to the Decree of the Minister of

Forestry in 1995, the area of coastal mangroves

in North Jakarta amounted to 327.70 hectares.

Based on the processing of mangrove satellite

image data for 8 years in Jakarta Bay from

2013 until 2020, different mangrove area

values are obtained, which are shown in

Figure 15, Figure 16, Figure 17, Figure 18,

Figure 19, Figure 20, Figure 21 and Figure

22.


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Figure 15. Results of Mangrove Satellite Imagery Data Processing Year 2013



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Figure 19. Results of Mangrove Satellite Imagery Data Processing Year 2017.



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The value of mangrove area in a row for 8

years is obtained from the results of processing

mangrove area data in 2013, using Landsat 8

OLI satellite imagery, which is 327.70

hectares. The comparison obtained between the

results of digitizing satellite images with the

Decree of the Minister of Forestry in 1995 is 0

hectares. The results of data processing

mangrove area in 2014, which is an area of

331.75 hectares. The comparison between the

digitized results of satellite imagery and the

Decree of the Minister of Forestry in 1995 is

4.05 hectares. The results of data processing


332.62 hectares. The comparison obtained

between the results of digitizing satellite

images with the Decree of the Minister of

Forestry in 1995 is 4.92 hectares. According to


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Putra and Ragil (2019), the reclamation area on

the coast of DKI Jakarta, especially in the

study area, the mangrove area has increased

and decreased along with the sedimentation.

Where the development of mangroves is

strongly influenced by the sedimentation

process.

The results of data processing mangrove

area in 2016, which is an area of 329.43



Decree of the Minister of Forestry in 1995 is

1.73 hectares. The results of data processing on

the area of mangroves in 2017, which is an

area of 329.02 hectares. The comparison

obtained between the results of digitizing

satellite images with the Decree of the Minister

of Forestry in 1995 is 1.32 hectares. The

results of data processing on the area of

mangroves in 2018, which is an area of 327.70



Decree of the Minister of Forestry in 1995 is 0

hectares. The results of data processing on


327.70 hectares. The comparison obtained

between the digitized results of satellite

imagery and the Decree of the Minister of

Forestry in 1995 is 0 hectares. While the

results of data processing of mangrove area in

2020, which is 327.70 hectares. The

comparison obtained between the results of

digitizing satellite images with the Decree of

the Minister of Forestry in 1995 is 0 hectares.

This can be caused by several things,

namely natural and human factors. In the case

of mangroves in Pantai Indah Kapuk, the

increase in mangrove area in the west is due

to the periodic planting of mangroves and in

recent years it has become a mangrove natural

tourism park. The reduction of mangroves in

the east of Pantai Indah Kapuk may be due to

sediment runoff due to reclamation in Jakarta

Bay. To ensure this, further analysis is needed

in the form of additional information related

to the physical condition of the waters in the

study area.

According to Sofian et al (2020), the

mangrove ecosystem has changed a lot and

has become the most threatened tropical

ecosystem in coastal areas. Excessive use of

mangrove ecosystems such as the opening of

new land for ponds on a large scale is the

biggest factor in the threat of mangrove areas

(Adharani et al., 2018) . The degradation of

mangrove area will also have an impact on the

environment, social and economy around the

area. According to Yunus et. al (2017), direct

human activities can cause damage to

mangrove ecosystems in coastal areas, such as

conversion of mangrove land into ponds,

industrial development, and disposal and

spraying of pesticides.

No. Pick Up

Year

Area

(Ha)

Increase

(Ha)

1. Agustus

2013 327,70 0

2. September

2014 331,75 4,05

3. Agustus

2015 332,62 4,92

4. Mei 2016 329,43 1,73

5. Juli 2017 329,02 1,32

6. Juli 2018 327,70 0

7. Juli 2019 327,70 0

8. April

2020 327,70 0

Figure 23. Analysis Area

Based on the analysis of the area of

mangroves that showed at Figure 23, the

reclamation area, it is estimated that the

average expansion of mangrove stands from

2013 to 2020 is 1.5 ha/year. Based on field

observations, there are several types of

mangroves that are planted with human

assistance and naturally. Natural nurseries are

usually the mangrove species Sonneratia Alba,

Rhyzophora Mangle, Bruguiera Cylindrica,

Xylocarpus Granatum and human-assisted

nurseries of mangrove species Sonneratia

Alba.

CONCLUSION

Based on the mangrove area analysis of,

it can be concluded that there is a reclamation

area, a mangrove ecosystem on the coast of

DKI Jakarta, especially in the study area,

namely the Muara Angke mangrove area.

Mangrove area has increased along with the


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sedimentation. The results of the analysis

conclude that the area value varies in each

year between 327.70 - 332.62 hectares. The

smallest distribution is located in the

Arboretum of 10.51 hectares. Changes in

mangrove area are influenced by tides. This

situation can encourage abrasion in the

surrounding coastal areas, which are able to

erode and carry sediment.

TSS levels have increased significantly

when construction is taking place on the

reclamation island. In addition, December

2018 is the only month under Quality

Standard no. 51 of 2004. Comparison of

image processing data with agencies has a

very high error rate. This value can be used as

a reference that the results of the information

can be used to identify TSS at the research

site by using the LANDSAT 8 – OLI satellite

imagery with the Syarif Budiman algorithm.

The hydro-oceanographic factor in this

study has a very small effect on the TSS value

and very high on the mangrove area in the

study area. From the total percentage of all

parameters, only 7.9%. The influence that has

the highest significant level is the current with

a value of 4%. The TSS value in the waters is

influenced by other factors that have not been

carried out in this study, such as the influence

of rainfall, river flow, human activities,

fishing activities, and shipping.

The recommendation that can be given

were firstly, mapping TSS, as well the

mangrove area in the reclamation sites of

Jakarta using remote sensing is still in

needed for observing the spatial-temporal

differences. In addition, further monitoring

research is needed to determined the most

significant effect on TSS levels and the

sedimentation process in the mangrove area

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