Abstract
Malaysia has been recognizedas a country with the greatest diversity of mangrove species. In this study, the mangrove forest at Rembau River, Negeri Sembilan, Malaysia was classified using multispectral SPOT 5 image. The mangrove vegetation species was identified using texture analysis, Normalized Difference Vegetation Index was also utilized to identify vegetation densities in the mangrove area. Classification approach was implemented using Maximum Likelihood Classifier. Eight classes of mangrove species were found within the study site which includes Sonneratia caseolaris, Nypa fruticans Bruguiera gymnorhiza, Xylocarpus granatum, Cerbera odollam, Sonneratia alba, Thespesia populnea and Rhizophora apiculata. The results showed that the highest per pixel classification accuracy (84.81%) for SPOT 5 image was using NIR band with a 9 × 9 window size. The upstream riverside area was dominated by Sonneratia caseolaris whereas Rhizhopora apiculata were dominant at downstream of the river. Dense vegetation dominates the overall mangrove forest of this study area. However, Sonneratia caseolaris and Nypa fruticans were found in low dense vegetation area. This endangers the firefly habitat. The results suggest preserving mangrove ecosystems to support firefly tourist operations. The findings of this research will benefit in monitoring and conservation of the mangrove habitats for the firefly population.
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