Mangroves are known as salt-tolerant evergreen forests, whereas its create land-ocean interface ecosystems. Besides,
mangroves bring direct and indirect benefits to human activities and play a major role as significant habitat for
sustaining biodiversity. However, mangrove ecosystem study based on the mangrove species are very crucial to get a
better understanding of their characteristics and ways to separate among them. In this paper, discriminant functions
obtained using statistical approach were used to generate the score range for six mangrove species (Rhizophora
apiculata, Acrostichum aurem, Acrostichum speciosum, Acanthus ilicifolius, Ceriops tagal and Sonneratia ovata) in
Matang Mangrove Forest Reserve (MMFR), Perak. With the computation of score range for each species, the fraction of
the species can be determined using the proposed algorithm. The results indicate that by using 11 discriminant functions
out of 16 are more effective to separate the mangrove species as the higher accuracy was obtained. Overall, the
determination of leaf sample’s species is chosen base on the highest fraction measured among the six mangrove species.
The obtained accuracy for mangrove species using statistical approach is low since it is impossible to successfully
separate all the mangrove species in leaf level using their inherent reflectance properties. However, the obtained
accuracy results are satisfactory and able to discriminate the examined mangrove species at species scale.