Sains Malaysiana 40(2)(2011): 83–88

 

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

 

Received: 5 November 2009 / Accepted: 6 August 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

 

REFERENCES

 

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.

 

*Corresponding author; email: mhasmadi@putra.upm.edu.my