Spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects

Abstract

In this study, we used the spectral information divergence (SID) and spectral angle mapper (SAM) algorithm classification to identify ~ 40,000 individual trees from 19 mangrove species; these data were collected from 7 sampling points spread across 40,288 ha of the Matang Mangrove Forest Reserve (MMFR) in the state of Perak, Malaysia. This information was examined and analysed to answer two questions: (1) can medium resolution of satellite image identify the individual mangrove species (2) how are the distributions of individual species within the mangrove zonation associated with the anthropogenic matrix? Species identification with spectral library derived from the in-situ measurements using the SID algorithm was compared with that derived from the Landsat 8 using the SAM algorithm; it was found that the two methods offered different but complementary information with different rates of accuracy. The observed levels of classification accuracy are at 84.95% and 85.21%, respectively for SID and SAM algorithm classification. The mangrove species distribution has a correlation with the anthropogenic activities, but the distribution occurred randomly without specific zones. All the 19 selected mangrove species are closely related with different correlation by the anthropogenic activities. The use of the SID and SAM algorithms may provide the most promising way of classification for improving the mangrove species identification, with medium resolution of satellite image. Recognising the characteristics of mangrove zonation may give a better understanding of mangrove species appearances and conservation. However, mangrove zonation will remain a daunting mapping task and is a challenge for the ecologists in the future.