Spatial analysis of heavy metals in mangrove estuary at east coast peninsular Malaysia: a preliminary study
The objectives of this preliminary study are to determine heavy metal concentration in mangrove estuary and to identify spatial patterns in the water quality based on heavy metals concentration. Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs) were selected to analyze the dataset of six heavy metal parameters namely: Ni, Cu, Pb, Cd, As and Zn. PCA results show that the major source of water pollution in mangrove estuary is mostly due to the agriculture activities surface runoff. ANN results show a better prediction performance in discriminating between the regions with an excellent percentage of correct classification.
This study presents the obligation and expediency of environmetric for the understanding of datasets directing to gain better information about water quality patterns in mangrove estuary based on spatial characterizations at the selected monitoring stations.
Keywords: marine water quality; PCA; ANN; heavy metal; mangrove