ASSESSING WETLAND VEGETATION FRAGMENTATION IN ...

MRSS 2010, PWTC, Malaysia. April 28-29, 2009
ASSESSING WETLAND VEGETATION FRAGMENTATION IN BEAUFORT,
SABAH USING MULTITEMPORAL SATELLITE REMOTE SENSING
ABSTRACT
K.U. Kamlun 1 , M.H. Phua 1
1 School of International Tropical Forestry
Universiti Malaysia Sabah, 88400 Kota Kinabalu, Sabah, Malaysia
Email: kamlisa@ums.edu.my
Wetland is a part of natural ecosystem that provides many intangible services to human. The
wetland in Beaufort, Sabah lays pieces of pristine peat swamp forest (PSF) that has been
rapidly disappearing. This study aims at quantifying the wetland vegetation changes and
fragmentation in Beaufort area from mid-80s to mid-2000s using multitemporal satellite data
of Landsat MSS (1985), Landsat TM (1991), Landsat 7 ETM+ (1999), Landsat 7 ETM+
(2003) and SPOT4-HRVIR (2003). The satellite images were classified into ten land cover
types with supervised classification approach. The classification’s results show significant
changes in peat swamp forest (PSF), bareland and grassland in the 18-year period. The PSF
had plummeted by about 70% from 1985 to 2003. Mean patch size and largest patch index
between 1985 and 2003 show an increase of fragmentation in the PSF. Mean nearest
neighbor distance of PSF indicates that the patches of PSF have low connectivity and
isolated. From the degrees of deforestation and fragmentation, the PSF may disappear from
this wetland if no effective restoration strategy is taken.
Keywords: Fragmentation, Peat swamp forest, Landscape indices, Deforestation and Land
cover change
INTRODUCTION
Wetland is an important natural unique ecosystem that is highly diverse. It provides the
important value to human environment especially socio-economic sustainable development
(Liu et al., 2004). However, no matter how important wetlands are, human existence on the
earth affects the ecosystem causing changes to the natural environment to this pristine
wetland. According to Safford and Maltby (1998), world wetland covers 6% of the earth and
now over 50% of that total have been degraded or lost (Millenium Ecosystem Assessment,
2005). Anthropogenic alterations on wetlands are globally concern in the form of
fragmentation by over exploitation of natural resources. This will increase the potential of
natural disaster such as forest fire.
The most distinctive wetland type found in Southeast Asia is peat swamp forest
(PSF). In Malaysia particularly, there is about 2.7 million hectares (ha) of PSF (Wong, 1991)
compared to recent data which shows that the area had decreased to 1.5 million ha
(UNDP/GEF, 2006). This means almost half of the pristine wetland had been destroyed
within a decade. The reduction of PSF in Southeast Asia is mostly due to fires (Stuebing et
al., 2006). Rapid conversion of forest to other land uses also causes fragmentation of the PSF.
In Peninsular Malaysia, most of the wetland areas were converted into agricultural land. In
the state of Selangor, oil palm plantation is the major contributor to the forest fragmentation
in wetland areas (Abdullah & Nakagoshi, 2006). In Sabah, the largest pieces of PSF in Klias
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MRSS 2010, PWTC, Malaysia. April 28-29, 2009
Peninsula were severely destroyed by recurrent fires especially during the 1998 and 2003
ENSO events (Phua et al., 2007; 2008).
There are various methods for detecting changes involving a large area. Analyzing
vegetation change over a long period of time can be very time consuming and expensive.
Land cover mapping using surveying method is labour intensive, time consuming and
completed relatively infrequent (Olorunfemi, 1983). The development of remote sensing and
GIS technologies facilitate accurate monitoring of vegetation change as less time consuming,
cost effective and highly efficient (Ying et al., 2005). Remote sensing technique is used to
collect data about the earth from the space without having to take physical sample of the earth
surface. Remote sensing technology integrated with GIS can render reliable information on
changes. Land cover type derived from satellite remote sensing is very important in landscape
fragmentation studies especially for assessing the landscape structure (Kepner et al, 2000).
Changes can be quantitatively characterized as landscape patterns which link the changes to
ecological processes in the landscape. According to Frohn (1998), landscape metrics are vital
for identifying the patterns of changes that are not readily visible to the human eye or easily
detectable by human analysis. In this study, multitemporal satellite remote sensing was used
for detecting the temporal changes of land cover and temporal patterns of the PSF in the Klias
Peninsula.
MATERIALS AND METHOD
Study Area
The Klias Peninsula is a large coastal plain is located at the southwestern coast of Sabah
approximately between the 115˚.45’ and 115˚.72’N and 5˚.42’ and 5˚.15’E. The Klias
Peninsula lies at the foothills of the Crocker Range (UNDP/GEF, 2006). The Klias Peninsula
is an extensive wetland concentrated in Beaufort area which is about 100 km from Kota
Kinabalu (Figure 1). The wetland is protected by a few forest reserve (FR). Binsuluk FR
(BFR) and Klias FR (KFR) are both Class 1 protection FR gazetted in 1984. This two FR
protect the largest remaining pieces of PSF in the Klias Peninsula. Binsuluk FR is largest at
12,106 ha while Klias FR consist of 3,630 ha (UNDP/GEF, 2005). Although the Beaufort
area receives high rainfall with an annual average of 3500 mm, fires during the prolonged
droughts of El-Niño events in 1983, 1991, 1998 and 2003 have severely affected the PSF in
this area. Due to the poor remaining stands of PSF, there are tremendous pressures for its
conversion to agricultural uses from the adjacent local community (Sabah Forestry
Department, 2005).
Data source and pre-processing
The satellite images used include Landsat MSS (June 29, 1985), Landsat TM (June 14, 1991),
Landsat-ETM+ (December 07, 1999 and Jan 14, 2003) and SPOT4-HRVIR (March 26,
2003). The MSS85 and TM91 were free of cloud and haze while 10% of the ETM99 was
haze and cloud outside the two protection FR. A relatively small amount of cloud was in the
ETM03 some haze was visible in the Klias FR. Meanwhile, 20% of the SPOT03 was affected
by cloud.
Topographic maps (1:50,000) obtained from JUPEM were used to rectify all the
images to Universal Transverse Mercator (UTM) projection. The georeference residuals for
all the satellite images were within 1 pixel. The resolutions for the five sensor data ranges are
different for the MSS 1985 (79 m), TM 1991 (30 m), ETM+ 1999 (30 m), ETM+ 2003 (30
m) and SPOT 2003 (20 m). All images were resampled to 30m using nearest neighbor
resampling for land cover classification.

Beaufort
Kota Kinabalu
MRSS 2010, PWTC, Malaysia. April 28-29, 2009
Figure 1: Location of Beaufort, Sabah.
Land Cover Classification
Often, land cover change studies adopt either supervised or unsupervised classification to
determine the spectrally distinctive land cover classes (Smits et al, 1999).To detect the land
cover changes in the Klias Peninsula, supervised classification with maximum likelihood
algorithm was applied. Ten land cover categories were defined in this study, namely PSF,
mangrove, grassland, shrubland, bareland, oil palm, rubber, water, cloud and shadow. The
spectral signature of the land cover categories were developed using digitized training sites.
The training areas for MSS85, TM91 and ETM99 were collected based on JUPEM’s
topographic maps (1:50,000), which were updated in 1993 and also land cover map of 1996
(1:100,000) from Sabah Land and Survey Department. Apart from these, ground truthing and
the history of land use obtained from interview with local people were useful in the
classification. The training areas for landsat ETM03 and SPOT03 were collected based on the
interpretation of the RGB colors of the unchanged classes. Finally, the maximum likelihood
algorithm was used to classify the images. The resulting land cover classifications were
filtered with 3X3 majority filter to reduce the salt and paper effect in the images.
Landscape indices
There are several landscape metrics to describe the landscape structure and pattern in
fragmentation assessment. We employed the indices to quantify landscape fragmentation and
the changes over time in the Klias Peninsula. We focused on fragmentation of the good PSF
using area metrics, shape metrics, patch density, patch size, variability metrics, nearest
neighbour metrics, diversity metrics and contagion and interspersion metrics available in
FRAGSTATS version 3.3 (McGarigal and Marks, 1995).
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RESULTS AND DISCUSSION
Land Cover Changes
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MRSS 2010, PWTC, Malaysia. April 28-29, 2009
Figures 2 and 3 show the land cover types between 1985 and 2003, resulted from the
supervised classification. There had been significant changes in the entire land cover of
Beaufort area. The land cover types that change the most are PSF, bareland and grassland.
The land cover classifications indicate drastic changes in the PSF occurred between 1991 and
1999. The PSF had severely decreased by more than 10000 ha to about 8000 ha in 1999. This
indicates that, more than 50% or half of the PSF was destroyed. The severe damage is
attributable to disastrous forest fires occurred in 1998 during the ENSO-related drought
(UNDP/GEF, 2006). In contrast, the grassland area has increased to more than 20000 ha. This
shows fire disturbance to PSF will rapidly change the forest landscape into an extensive
grassland landscape (Haberle, 2007; Cochrane, 2003). A further significant decrease of 25%
of the PSF from 7198 ha to 5364 ha occurred between January 2003 and March 2003. This
was due to fires in another prolonged El-Niño event recurred in 2003 (UNDP/GEF, 2006).
The PSF in the Binsuluk FR that was once more 8000 ha in 1997 (Phua et al., 2007) but the
largest piece of PSF in the Klias Peninsula has shrunken to 2000 ha. The piece of PSF (more
than 3000 ha) in the Klias FR now holds the largest amount of this forest type in the Klias
Peninsula. However, the most significant vegetation change in this period was the increase of
bareland from 14750 ha to 30108 ha which was more than twice. The gain in bareland was
largely due to the decrease in the grassland from 40450 ha to 29427 ha, a total of 11023 ha.
LCC 1985
LCC January 2003
(Before fire occurrence)
LCC 1991
LCC March 2003
(After fire occurrence)
Figure 2: Land Cover Classes of Klias Peninsula
LCC 1999

45000
40000
35000
30000
25000
20000
15000
10000
5000
0
(ha)
Good Peat
Swamp
Forest
MRSS 2010, PWTC, Malaysia. April 28-29, 2009
Figure 3: Land Cover Classes of the Klias Peninsula from 1985-2003.
Landscape fragmentation pattern
Mangrove Shrubland Grassland Bareland Oil Palm
Plantation
Land Cover Class
Rubber
Plantation
For analyzing the fragmentation of the PSF, the producer’s and user’s accuracies of the peat
in all the land cover classifications were at least 85%. The temporal patterns of the landscape
indices are shown in Table 1. The patch density, patch size and largest patch index clearly
show that the Good PSF in the Klias Peninsula has undergone a drastic fragmentation from
1985 to 2003. In Table 1 the PSF is facing with the largest reduction in the wetland area. The
total class area in 1985 was 20287.89 ha but only 5369.22 ha remained in March 2003. This
means a reduction of 74% of the PSF over 18 years. It is supported by the percent of
landscape which was 11.97% in 1985 and dropped to 3.17% in March 2003. The decrease of
patch density, patch size and largest patch index provide evident that the PSF in Beaufort area
has undergone an increase of fragmentation between 1985 and March 2003. Not only the
number of patches has decreased substantially from 6628 to 2123, the mean patch size also
pinpoints the fragmentation where it has decreased significantly from 3.06 ha in 1985 to 1.44
ha in 1999 and only increased slightly to 1.54 ha in March 2003. The largest patch index also
supports this analysis where the largest PSF patch has decreased from 1.30% in 1985 to
0.52% in March 2003. According to McGarigal and Marks (1995), a landscape with a smaller
mean forest patch size is considered more fragmented. During the ENSO 2003, increasing the
mean patch size coupling with decreasing patch number was observed. This indicates the loss
of these patches from the landscape (Manier and Laven, 2001).
Fragmentation of the PSF will potentially affect the connectivity of wildlife habitat in
the landscape. Smaller patches will be difficult for wildlife species dispersion. According to
Goodwin and Fahrig (2002), an increase of patch number would offer more opportunities for
species to visit new patches. This suggests that the PSF in Beaufort area is becoming low in
terms of connectivity especially to species distribution due to the decreasing patch number.
Furthermore, the patches are becoming more isolated.
Water
Year 1985
Year 1991
Year 1999
Year January 2003
Year March 2003
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MRSS 2010, PWTC, Malaysia. April 28-29, 2009
Table 1: Landscape fragmentation indices for Good PSF in the Klias Peninsula for 1985
and 2003
Year
INDICES
1985 1991 1999 Jan 2003 March 2003
Class Area (ha) 20287.89 18605.70 8019.97 7196.58 5369.22
Percent of Landscape (%) 11.97 10.98 4.73 4.25 3.17
Number of Patches 6628.00 6008.00 5554.00 4673.00 2123.00
Patch Density (#/100/ha) 3.91 3.55 3.28 2.76 1.25
Largest Patch Index (%) 1.30 1.24 0.60 0.58 0.52
Mean Patch Size (ha) 3.06 3.10 1.44 1.54 2.53
Patch Size CV (%) 2015.64 1934.16 1753.96 1656.56 1331.23
Mean Shape Index 1.28 1.28 1.29 1.30 1.40
Mean Patch Fractral 1.05 1.06 1.06 1.06 1.07
Mean Proximity Index 319.91 311.12 87.47 76.13 105.61
Mean Nearest Neighbour
Distance (m)
118.67 120.86 136.97 142.23 181.31
Nearest Neighbour CV (%) 71.26 71.98 75.99 78.31 95.57
Interspersion/ Juxtaposition
(%)
14.54 15.12 14.92 14.92 15.25
CONCLUSION
Multitemporal satellite remote sensing was instrumental in detecting land cover change in the
Klias Peninsula. The PSF has significantly decreased due to land conversion and fires
occurred during El-Niño events in 1985 and 2003. More than 70% of the PSF areas were
transformed to bareland and grassland. Overall, the PSF has shrunken significantly from
20287.89 ha to 5369.22 ha within the 18-year change period. Destruction on the two
remaining patches of PSF has led to forest fragmentation. The percent of landscape and patch
density shows that the patches has been shrinking in the area and sparse. The mean patch size
and largest patch index shows an increase of fragmentation in 1999 and the patches are
gradually disappearing from the landscape in 2003. As a result, the PSF is more isolated and
low in connectivity which may adversely affect wildlife species dispersion. Without proper
control of unsustainable land use practices, deforestation leading to further fragmentation will
destroy the remnants of the PSF in the Klias Peninsula.
ACKNOWLEDGEMENT
We would like to express our appreciations to the Sabah Forestry Department and UNDP for
permission, support and knowledge sharing.

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