Modelling chlorophyll concentrations using Modis satellite data

Abstract

Accurate chlorophyll data are critical for determining the magnitude and variability of global ocean primary production, the effect of biological processes on carbon dioxide drawdown in surface waters and for improving the understanding of phytoplankton dynamics in the oceans. In this study, four algorithms have involved to map chlorophyll spatial distribution from MODIS satellite data along east coast of Malaysia: Aiken algorithm, Clark-3-bands algorithm, Gordon algorithm and Normalized Difference Chlorophyll Index (NDCI) algorithm. The results show that the Aiken's algorithm is appropriate for accurately synoptic chlorophyll mapping distribution. In fact, the algorithm performs the lowest root mean square error of ±0.10 mg m-3 as compared to other algorithms. In conclusion, MODIS data can be used as a geomatica tool for accurately mapping of chlorophyll concentration along the coastal water of Malaysia with implementation of Aiken's algorithm. © Medwell Journals, 2010.