 |
 |
 |
 |
 |
 |
Remote Sensing for
Mapping RAMSAR Heritage Site at Sungai Pulai Mangrove Forest Reserve, Johor,
Malaysia
(Penderiaan Jauh
untuk Pemetaan Tapak Warisan RAMSAR di
Hutan Simpan Bakau di Sungai Pulai, Johor, Malaysia)
I. Mohd Hasmadi*, H.Z. Pakhriazad
& K. Norlida
Forest Surveying and Engineering Laboratory, Faculty of Forestry
Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia
Diserahkan: 5 November 2009 / Diterima: 6 Ogos 2010
ABSTRACT
The Sungai Pulai Mangrove
Forest Reserve (SPMFR) is the largest riverine
mangrove system in Johore. In 2003 about 9,126 ha of the Sungai Pulai mangrove
was designated as a RAMSAR site. RAMSAR sites
are wetland areas that are deemed to have international importance and are
included in the List of Wetlands of International Importance. The SPMFR plays a significant socio-economic role to the adjacent 38
villages. Satellite remote sensing is a useful source of information where it
provides timely and complete coverage for vegetation mapping especially in
mangroves where the accessibility is difficult. This study was carried out to
identify and map land cover types using SPOT-4 imagery at the Sungai
Pulai-RAMSAR site and its surrounding areas. Through
unsupervised classification technique a total of seven classes of land cover
type were mapped, where about 90% mapping accuracy was gained from the accuracy
assessment. Later, vegetation densities were classified into five levels namely
very high, high, medium, low and very low based on crown density scale using
vegetation indices model such as NDVI, AVI and OSAVI.
Results from NDVI and OSAVI model were almost similar
but AVI model detected more on medium vegetation which did
not show the real ground condition. The study concludes that SPOT-4
imagery was able to discriminate mangrove area clearly from other land covers
type. Vegetation indices model can be used as a tool for mapping vegetation
density level in the SPMFR and its surrounding area.
Therefore VI’s models from remote sensing are useful to monitor and
manage the mangrove forest for sustainable management and preserve the SPMFR as a RAMSAR site in Peninsular Malaysia.
Keywords: Conservation
Management; mangrove mapping; RAMSAR site; remote sensing
ABSTRAK
Hutan Simpan Paya Bakau
Sungai Pulai (SPMFR) merupakan sistem hutan paya bakau terbesar di
negeri Johor. Pada tahun 2003, kira-kira 9,126 ha kawasan paya bakau Sungai
Pulai telah diberikan taraf sebagai tapak RAMSAR.
Tapak RAMSAR adalah kawasan tanah lembap yang mempunyai
kepentingan antarabangsa dan termasuk dalam Senarai Kepentingan Tanah Lembap
Antarabangsa. SPMFR memainkan peranan penting dalam sosio-ekonomi
kepada 38 kampung yang berdekatan. Penderiaan jarak jauh merupakan sumber
maklumat yang bermanfaat kerana ia menyediakan liputan masa yang tepat dan
lengkap untuk pemetaan tumbuhan paya bakau terutama di kawasan yang sukar.
Kajian ini dijalankan untuk mengenal pasti dan memeta jenis litupan tanah
menggunakan imej SPOT-4 di kawasan Sungai Pulai dan
kawasan sekitarnya. Dengan menggunakan teknik pengelasan tidak terselia, tujuh
kelas tumbuhan telah dihasilkan dan kira-kira 90% hasil pemetaan adalah tepat.
Kemudian kepadatan tumbuhan dikelaskan kepada lima iaitu sangat padat, padat,
sederhana padat, kurang padat dan sangat kurang padat berdasarkan skala
kepadatan silara menggunakan model Indek Tumbuhan (VI’s)
seperti NDVI, AVI dan OSAVI.
Keputusan daripada model NDVI dan OSAVI adalah
hampir sama tetapi AVI lebih tertumpu kepada tumbuhan
berkepadatan sederhana dan tidak menggambarkan keadaan sebenar di lapangan.
Kajian ini jelas menunjukkan data SPOT-4 mampu membezakan kelas
hutan bakau daripada tumbuhan yang lain. Indeks tumbuhan boleh digunakan untuk
menghasilkan peta kepadatan tumbuhan. Oleh itu, model indeks tumbuhan daripada
data deriaan jarak jauh boleh membantu dalam pemantauan dan pengurusan hutan
paya bakau secara berterusan serta mengekalkan SPMFR sebagai
tapak RAMSAR di Semenanjung Malaysia.
Kata kunci:
Pemetaan paya bakau; penderiaan jarak jauh; pengurusan pemuliharaan; tapak RAMSAR
RUJUKAN
Alongi, D.M. 2002.
Present state and future of the world’s mangrove forests. Environmental
Conservation 29(3): 331-349.
Blasco, F.T.,
Gauquelin, T., Rasolofoharinoro, M., Denis, J., Aizpuru, M. & Caldairou, V.
1998. Recent advances in mangrove studies using remote sensing data. Marine
and Freshwater Research 49: 287-296.
Boyd, D.S. 2001.
Vegetation indices. In The encyclopaedic dictionary of environmental change,
edited by J.A. Mathews. London: Arnold.
Dahdouh-Guebas, F.
& Koedam, N. 2008. Long-term retrospection on mangrove development using
transdisciplinary approaches: A review. Aquatic Botany 89(2): 80-92.
Diaz,
B.M. & Blackburn, G.A. 2003. Remote sensing of mangrove biophysical
properties: evidence from a laboratory simulation of the possible effects of
background variation on spectral vegetation indices. International Journal
of Remote Sensing 24: 53-73.
Duke, N.C.,
Meynecke, J.-O., Dittmann, S., Ellison, A.M., Anger, K., Berger, U., Cannicci,
S., Diele, K., Ewel, K.C., Field, C.D., Koedam, N., Lee, S.Y., Marchand, C.,
Nordhaus, I. & Dahdouh-Guebas, F. 2007. A world without mangroves? Science 317: 41-42.
Ellison, J.C. 2008.
Long-term retrospection on mangrove development using sediment cores and pollen
analysis: A review. Aquatic Botany 89(2): 93-104.
Farnsworth, E.J.
& Ellison, A.M. 1997. The global conservation status of mangroves. Ambio 26(6): 328-334.
FAO 2007. The
World’s Mangroves 1980-2005. FAO Forestry Paper 153. Food and Agricultural
Organization, Rome, Italy.
Hirano, A., Madden,
M. & Welch, R. 2003. Hyperspectral image data for mapping wetland
vegetation. Wetlands 23: 436-448.
Kathiresan, K.
& Bingham, B.L. 2001. Biology of mangroves and mangrove ecosystems. Advances
in Malaysia Biology 40: 81-201.
Mohd. Hasmadi, I.,
H.Z. Pakhriazad & Kamaruzaman, J. 2008. Mangrove canopy density of Sungai
Merbok, Kedah from Landsat TM. J. Malaysian Forester 71(1): 67-74.
Paine, D.P. 1981. Aerial
Photography and Image Interpretation for Resource Management. New York: John Wiley.
Polidoro, B.A.,
Carpenter, K.E., Collins, L., Duke, N.C., Ellison, A.M., Ellison, J.C.,
Farnsworth, E.J., Fernando, E.S., Kathiresan, K., Koedam, N.E., Livingstone,
S.R., Miyagi, T., Moore, G.E., Ngoc Nam, V., Ong, J.E., Primavera, J.H., Salmo
III, S.G., Sanciangco, J.C., Sukardjo, S., Wang, Y. & Hong Yong, J.W. 2010. The
loss of species: mangrove extinction risk and geographic areas of global
concern. PLoS ONE 5(4): e10095.
Rikimaru, A. 1997.
Concept of FCD mapping model and semi-expert system. Project on PD32/93
Rev2.(F) Rehabilitation of logged-over forests in Asia/Pacific region for
International Tropical Timber Organization (ITTO).
Rondeaux, G.,
Steven, M. & Barret, F. 1996. Optimization of Soil Adjusted Vegetation
Index. Remote Sensing of Environment 55: 95-107.
Rouse, J.W., Haas,
R.H., Schell, J.A., Deering, D.W. & Harlan, J.C. 1974. Monitoring the
vernal advancement of retrogradation of natural vegetation. NASA/GSFC, Type
III, Final Report Greenbelt MD, USA, 1-371 pp.
Thampanya, U.,
Vermaat, J.E., Sinsakul, S. & Panapitukkul, N. 2006. Coastal erosion and
mangrove progradation of Southern Thailand. Estuarine Coastal and Shelf
Science 68: 75-85.
Vaiphasa, C.,
Ongsomwang, S., Vaiphasa, T. & Skidmore, A.K. 2005. Tropical mangrove
species discrimination using hyperspectral data: A laboratory study. Estuarine
Coastal and Shelf Science 65: 371-379.
Vijay, V., Biradar,
R.S., Inamdar, A.B., Deshmukhe, G., Baji, S. & Pikle, M. 2005. Mangrove
mapping and change detection around Mumbai (Bombay) using remotely sensed data. Indian Journal of Marine Sciences 34: 310-315.
*Pengarang untuk surat-menyurat; email: mhasmadi@putra.upm.edu.my
|
|||
