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LAND COVER CHANGE & SEDIMENT

DISTRIBUTION IN THE

JOHOR RIVER BASIN

Report Prepared for

GEK 2503 Mid-Term Project

By

LEE ZHI KANG

LEE YEAN SHENG

November 2011


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by suspended materials. The more particles suspended in water, the more difficult it is for

light to travel through it and the higher the measured turbidity. SPOT-5 images will be used

to establish the relationship between land activities and surface turbidity. Lastly, we will

evaluate the usefulness of satellite imagery in monitoring turbidity, using SPOT-5 and other

Earth Observation Satellites.

Land situation

Vegetation Cover

Vegetation reflectance is distinctively high in the NIR band and low in the Red band. Hence

changes in vegetation cover can be studied through the Normalised Difference Vegetation

Index computed using SPOT-5 images (Figure 2a & 2b). NDVI values are often used to

identify the different land cover classes and vegetation density. Healthy vegetation has the

highest NDVI values, followed by moist vegetation area such as mangrove swamps. Next

will be bare lands and urban areas. Water usually has negative NDVI values.

An alternative for the study of vegetation cover will be using band combinations. One of it is

false colour display(RGB= 321) (Figure 4a & 4b). High vegetation reflectance in the NIR

band allows effective distinction of vegetation areas which appears in different shades of red,

from water bodies and built-up areas. Hence the studying of general vegetation cover patterns

between time periods can be easily carried out.

False colour display (RGB = 432) is also useful for vegetation studies. This combination

(Figure 5a & 5b) provides great colour contrast which is very useful in identifying the

changes in vegetation cover and agricultural mapping. The absorption of water in SWIR band

enables us to differentiate vegetation with different moisture level. Normal vegetation and


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plantation will appear in bright green, moist vegetation like mangroves swamps in dark green

and exposed soil will appear mauve.

Ground truthing techniques can be used to identify specific vegetation features such as oil

palm plantations and mangrove swamps in the Johor River basin, and such information are

readily available on the internet from Google Earth (Figure 3).

Refer to Figure 4a, 4b, 5a & 5b

Area

Label

Change in NDVI value

(Figure 2a , 2b)Change in area of vegetation cover

A 0.54, -0.01 Degradation of mangrove swamps, becoming

barren landsB 0.10, 0.49 Cleared land from oil palm plantations have been

reused to grow new oil palm plantations

C 0.44 , -0.05 Expansion of artificial floodplains for agriculture

activities (Rice Fields)

To further analyze changing patterns, TNTmips is used to calculate the area affected regions.

For example, the degraded mangrove swamps at A, expanded from approximately 0.47km2

in

2004 to 2km2

in 2010. Such information from satellite imageries are often used by

environmentalist to shape environmental protection policies. A successful example can be

seen downstream (N13245.3, E1040018) where there is a decrease in mangrove

degradation due to area protection policy by the Environmental Science Associates (ESA).

Man-made developments

The standard colour infrared (RBG= 321) (CIR) is also useful in identifying man-made

features. Depending on their nature, different features appear in different shades of cyan-blue.

One of such features is the Kongkong Dam (N14340.18, E1035844.22), located west of

the Johor River seen in Figure 6. It can be identified by the blockage of the tributary and the

concrete structure that appears white in the image as non-vegetated areas appear white or

cyan-blue in the CIR image. The dam turns the tributary (Sungai Layang) into a water


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reservoir, represented by the dark-blue coloured area. The dam was already present in 2004,

therefore it appears in both images without much changes. North of the dam, is a small patch

of cyan-blue area identifying human settlements; Sungai Layang jetty (N134'53.04",

E10358'42.12") a kampong stylejetty that ferries people to Kelongs along Sungai Johor.

The second feature is the Sungai Johor Bridge, located south of the Johor River mouth seen

in Figure 7. Construction of the bridge only began in 2005, thus it is not seen in the 2004

image. The 4 km long suspension bridge connects Pulau Juling in the west to Tanjung

Penyabong in the east by the Senai-Desaru Expressway. It is identified by the long horizontal

cyan-blue line (Figure 4b) that stretches from the eastern to western inland area, across the

river. Paying close attention to east of the suspension bridge, we will observed that there is a

cyan-blue cluster which suggests the presence of urban developments. In fact, it is the cleared

land that was used as the main construction site during the construction of the bridge that

stores that construction materials and serves as a port for Floatable Cranes (machine).

Despite being identified as an Environmental Protection Zone, human influences are not

excluded along the coastal regions. Figure 4a & 4b suggest presence of sparse distributions

of human settlements along the eastern coastlines of the river which are represented by the

cyan-blue spots. Along the eastern coastline is Johor Lama (N135'10'', E1040'49'') which

was the old royal capital of Johor, currently a tourist attraction and Telok Sengat (N134'0",

E1042'0") which is a fishing village. Comparing the two images suggests that there are no

significant changes on the spatial distribution of urban development from 2004 to 2010.

Changes along coastal regions

To identify changes to the Johor River banks, a clear demarcation between water and land

pixels is required. Figure 8a & 8b are created using Band 3 (NIR) and contrasted at the

digital number (DN) range that omits water pixels which forms the first peak in the NIR-DN
http://en.wikipedia.org/w/index.php?title=Pulau_Juling&action=edit&redlink=1http://en.wikipedia.org/w/index.php?title=Tanjung_Penyabong&action=edit&redlink=1http://en.wikipedia.org/w/index.php?title=Tanjung_Penyabong&action=edit&redlink=1http://en.wikipedia.org/w/index.php?title=Tanjung_Penyabong&action=edit&redlink=1http://en.wikipedia.org/w/index.php?title=Tanjung_Penyabong&action=edit&redlink=1http://en.wikipedia.org/w/index.php?title=Pulau_Juling&action=edit&redlink=1


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histogram is due to their low reflectance. By applying green linear colour palette, land is

represented by green pixels and water by black pixels. Band 3 (NIR) is the most suitable as

infrared radiation is absorbed by water but reflected by land, creating a significant difference

in reflectance level between land and water bodies, giving a clear outline of the Johor River.

To have a clearer view on the changes along the river banks, another false colour display

(RGB= 342) can be used (Figure 9a & 9b).This band combination is sensitive to disparities

in moisture level of both vegetation and soil as it features high water absorption that allows

for detection of thin layers of water. Vegetation with low moisture content have higher Band

4 reflectance, contributing more green and results in an orangeier colour. Generally, wetter

soil will appear darker, because of the infrared absorption capabilities of water (GDSC).

Hence it enables us to distinguish clearly between the Johor River body and its river banks.

We observe that near the river banks, the flooding of the barren lands and swamps around

that area are common throughout in 2010 (Figure 8b). There are significant dark-blue spots

representing water bodies due water accumulation (Figure 9a & 9b). Such a scene is

justifiable as Figure 9b was taken in November whereas Figure 9a was taken in August. In

Peninsula Malaysia the first wet season occurs in October-November while June-August are

dry inter-monsoon months (Azmi, 2002). Thus due to heavy rainfall, water levels rise in

swampy areas, exceeding above surface lands and shorter mangrove communities.

However there is no significant eroded river corridor even with the high rainfall. This is seen

from Figure 8c that compares the 2004 river bank outlined in yellow with the 2010 river

bank. The slight deviation observed is due to a misalignment of a few pixels between the

images that will occur even after georeferencing the image.

Surface water turbidity (Spot 5)


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To conduct an assessment on surface turbidity of the river, the NIR image which is sensitive

to turbidity differences with adequate contrast enhancement (Figure 10a & 10b) will be most

suitable. In Band 3 (NIR), reflectance of clear water is virtually zero. The adsorption and

scattering properties of particles in turbid waters provide sufficient scattering to overcome

this strong absorption by water at the NIR wavelengths, hence reflecting the surface turbidity

patterns on the image. The image is produced by contrasting at the digital number (DN) range

of water pixels: at the first peak, and applied a colour palette.

Red water represents water of higher turbidity compared to blue water. Hence we

observed that turbidity levels are generally higher at the upper section of the Johor River and

its tributaries, and that the turbidity level decreases progressively in the direction towards the

river mouth. The highest turbidity levels can be seen along the coastline outlined by reddish

coastal waters.

Comparing both images, there is a significant increase in both the intensity and the spatial

distribution of the rivers turbidity as the red outline along the river banks is enhanced and the

greenish turbid waters have extended further downstream.

Contributing Factors

Human influence

The increase in surface turbidity of Johor River coincides with the increase in human

activities and developments at the upper stream regions. Figure 11 suggests that there are

urban developments at the tributaries where Kota Tinggi is located. Comparing Figure 12a &

12b, Kota Tinggi and other built-up areas have expanded over the years and this may have

adversely affected the water quality of the river. An example would be embankments, built to


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protect urban areas which divert runoff that contains high levels of urban contaminants such

as sewage materials and oil straight into the river channel (Sim, 2009).

Higher concentrations of turbid waters are also spotted along the coastline (Figure 10a &

10b). This may be a result of agricultural discharge from surrounding oil palm and rubber

plantations. Fertilisers with high salt content such as nitrates and phosphates are washed

down during rain which promotes growth of phytoplankton and algae in the river.

Urban structures such as dams and suspension bridges also affect river surface turbidity level.

Generally, higher concentration of turbid waters is found at the upper stream of these urban

structures. Without human influence, turbidity level generally decreases uniformly

downstream. This impact can be seen by focusing onthe newly erected Sungai Johor Bridge

region. Turbidity level is higher at the upstream of the bridge and is relatively lower after the

bridge. Such structures act as an obstacle to the natural flow of the river, decreasing the water

velocity; hence sediments which cause turbidity will settle and remain upstream.

Urban runoff

In urban areas, the impervious concrete surfaces lead to the increase in surface runoff

volume. Urban runoff rate is also higher due to man-made channels and canals which bypass

natural processes such as infiltration, percolation and ground water discharge. Increasing

volume and flow rate of water at tributaries will increase river erosion upstream, thus

carrying more sediment downstream, which increases turbidity levels.

Soil erosion

Soil erosion, a part of the natural hydrological cycle, plays a significant role in the turbidity

levels in the Johor River as it is amplified by the widespread of plantations in the river basin.

Plantations are designed to be in an orderly manner, unlike natural rainforest, to facilitate


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harvesting for the plantation owners. This reduces ground vegetation which lowers the

infiltration rate of the area. A more serious problem is the clearing of oil palm plantations.

Studying Figure 10a, turbidity concentration at the vicinity of the cleared land (area B) is

generally higher as land with sparse vegetation cover has a lower ability to retain water, thus

higher rate of soil erosion. Furthermore, the surface runoff will contain high amount of soil

sediments and pollutants that are left by the cleared plantations.

Seasonal monsoons also affect soil erosion rates. The Johor River catchment area, situated in

the equatorial region, experiences the northeast (November to March) and southwest (May to

August) monsoon. The region experiences high precipitation level during the northeast

monsoon as the monsoon winds enter from the South China Sea towards the east coast of

Peninsula Malaysia. Whereas, it receives lower rainfall during the southwest monsoon due to

the sheltering effect of the mountains of Sumatra (MWWG, 1990). Higher precipitation

implies that the ground water level and soil saturation level will be higher, leading to more

surface runoff which increases turbidity levels. This is shown in Figure 10a, taken in

November which turbidity is higher than Figure 10b, taken in August.

Surface water Turbidity (Other satellite platforms)

Other Satellites have capabilities to monitor water turbidity, similar to SPOT-5. Moderate-

resolution Imaging Spectroradiometer (MODIS) launched by NASA has 36 spectral bands, of

which Band 8-16 is used to identify ocean colour and phytoplankton (GSFC). IKONOS also

carries the NIR band similar to SPOT-5 and is frequently used for detailed lake assessments.

Compared to SPOT-5s revisit time of 2-3 days, MODIS has a revisit cycle of approximately

1 day and allows frequent turbidity monitoring on a daily basis. MODIS also has unique

spectral bands that provide direct measurements of scattering and absorption by the

atmosphere, where atmospheric corrections could be made in relation to assess Secchi Disk


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Transparency based on satellite imagery. However, unlike SPOT-5 with 10m spatial

resolution, MODIS has low spatial resolution of 250m, 500m and 1km which is ineffective in

monitoring small rivers like Sungai Johor as the river cannot be clearly identified as seen in

Figure 13. At best, Band 2 (NIR) at 250m resolution can only map the width of Sungai Johor

which spans across 2460m by 4 pixels. And, to use more sensitive spectral bands 8-16, will

result in lower resolution, mapping out the river with even lesser pixels. (Li et al., 2001)

Similar to SPOT-5, IKONOS with a 3 day revisit time can monitor turbidity at the same rate.

The method used to map turbidity by both satellites is similar as they carry the NIR band.

However the difference boils down to the detailing. IKONOS has a higher spatial resolution

of 3.2m compared to SPOT-5s 10m, thus IKONOS maps out the turbidity of small rivers

like Sungai Johor better. It gives us greater accuracy and more information in the distinction

of turbid waters and due to finer detailing; turbid water can be identified from multispectral

image (Figure 14) by murkier waters which appear white or brownish in colour.

Mapping out Turbidity using satellite imagery

Turbidity measured in NTU (Nephelometric Turbidity Units) is important to determine the

quality of water. Mapping the spatial distribution of suspended sediments involves

establishing the relationship between turbidity measures in NTU from in-situ data and the

backscattering coefficient of water calculated from the reflectance of satellite optical signals.

Backscatter refers to the reflection of wave particles and its coefficient measures the intensity

of reflection, which is directly proportional to turbidity levels as more turbid water reflects

NIR band to a greater extent compared to clearer water.

Firstly, we collect multiple water samples of the river of varying location and sediment types,

and measure the NTU of the samples using Portable Turbidimeters (TURB 430). Secondly,

under laboratory environment we use spectroradiometers (GER 3700) to measure the


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reflectance (corrected for additive and multiplicative effects like solar elevation and spectral

irradiance) of the water samples which can be used to calculate the backscattering coefficient

via these equations: Ri (Go + G1Ui)Ui (1)

Where Ui is given by: Ui =

(2)

relating with water surface reflectance Ri, backscattering coefficient bbi, absorption

coefficient ai at the i-th spectral band, Go 0.084, G1 0.170. (Lee et al., 1999)

By scatter plotting NTU against backscattering coefficient of the respective locations, we can

establish a linear relationship between the 2 variables via a regression analysis using

MATLAB as seen in Figure 15. As such, the backscattering coefficient relates well to

turbidity level. And the relationship is use to convert the reflectance image from satellites

into river water turbidity levels; example Figure 16maps the NTU of water pixels with their

corresponding backscattering coefficient. (Liew et al., 2009)

Conclusion

Satellite imagery does prove to be a better alternative to traditional methods of sample

collection and lab analysis which is slow and labour intensive in monitoring turbidity. Not

only is it more effective, monitoring could be done routinely depending on the revisit time of

the satellite. However, an obstacle may be the lag time between in-situ data and satellite

image as this depends on the orbit of the satellite and also the interference of cloud covers

which delays analysis, resulting in inaccuracy. Moreover, monitoring river turbidity requires

high resolution images from SPOT or IKONOS which may be too expensive for routine

monitoring. In the case of Johor River, Singapores PUB can collaborate with Johor State to

fund the monitoring using satellite imagery as it is a vital water source for the 2 states. It is

essential to maintain the Johor River waters fit-for-drinking. (Pereira et al., 2011)


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References

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October 2011, fromhttp://www.wildasia.org/main.cfm/library/Seasons_in_Malaysia

Environmental Science Associates. (2007).Natural and Green Environment. Planning and

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http://modis.gsfc.nasa.gov/about/specifications.php

Geospatial Data Service Centre.Band Combinations. National Aerospace Laboratory.

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http://gdsc.nlr.nl/gdsc/en/earth_observation/band_combinations

Kwoh, K. L. &, Ng, S. M. & Kuan, H. N. & Chia, K. & Liew, S. C. & Chang, C. W. &

Kwoh, L. K.(2009)Investigating relationship of nephelometric turbidity unit and total

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Modeling, Singapore-MIT Alliance for Research and Technology & Centre of

Remote Imaging, Sensing and Processing (CRISP), National University of Singapore

Liew, S. C. & Saengtuksin, B. & Kwoh L. K. (2009)MONITORING TURBIDITY AND

SUSPENDED SEDIMENT CONCENTRATION OF COASTAL AND INLAND

WATERS USING SATELLITE DATA. Centre for Remote Imaging, Sensing and

Processing (CRISP)
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Li, R. & Li, J. (2004) Satellite Remote Sensing Technology for Lake Water Clarity

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CONCENTRATION IN THE WATER OF THE ITUPARARANGA/SP/BR RESERVOIR

ESTIMATED THROUGH MULTISPECTRAL IKONOS IMAGERY. Universidade

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Images from:

CRISP Catalogue. Retrieved 2011, fromhttp://crisp.nus.edu.sg/crisp_cat.html

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Longman. (2002) Atlas Singapore and the World. Pearson Education. pg. 44.
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Appendix A

Instruments used in mapping Water Surface Turbidity

TURB 430, a portable turbidity meter for accurate turbidity measurements in the laboratory

or field studies.

The GER 3700 from the Geophysical and Environmental Research Corporation (GER) is a

high performance single-beam field spectroradiometer measuring over the visible to short-

wave infrared wavelength range.

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