Remote Sensing For Mapping Ramsar Heritage Site At Sungai Pulai Mangrove Forest Reserve, Johore, Malaysia

• Main Authors: I., Mohd Hasmadi, K., Norlida, H. Z., Pakhriazad
• Format: Conference or Workshop Item
• Language: English; English
• Published: 2009
• Online Access: http://psasir.upm.edu.my/id/eprint/18020/1/ID%2018020.pdf; http://psasir.upm.edu.my/id/eprint/18020/
• Institution: Universiti Putra Malaysia

The Sungai Pulai Mangrove Forest Reserve (SPMFR) is the largest riverine mangrove system in Johore State. 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 playa significant role for socio-economic to the adjacent 38 villages. The villagers depends on the estuary as its mudflats, an ideal feeding, spawning and fattening ground, support a significant proportion of fish species. Other mangrove uses include wood cutting, charcoal production, aquaculture activities and eco-tourism. The current development of Iskandar Development Region (IDR) and construction of a new port at the river estuary may represent a direct impact on the mangrove ecosystem, causing shorelines erosion and water pollution from associated reclamation and dredging works. However the conservation management of the site is managed in line with Integrated Management'Plan for the sustainable use of mangroves in Iohor state. Satellite remote sensing'is a useful source of information as it provides timely and complete coverage for vegetation mapping especially in mangroves where the access is difficult. This study was carried out to identify and map land cover types using SPOT 4 image in the Sungai Pulai-RAMSAR site and its surrounding areas. Unsupervised classification technique has produce eight classes of land cover type over the study site. Ground verification was carried out to verify and assess the accuracy of classification. The results showed that approximately 90% of the area was classified correctly. Vegetation density was classified into five levels namely very high, high, medium, low and very low based on crown density scale. The study concludes that SPOT 4 was capable to discriminate mangrove area clearly from other land covers type, meanwhile vegetation indices model can be used as a tool for mapping vegetation density level in the SPMFR and its surrounding area. Results clearly showed usefulness of remote sensing for monitoring, management and development of mangrove forest for sustainable management and preserve the SPMFR as a RAMSAR site in Peninsular Malaysia.