Abstract: This paper presents
the utilization of MODIS data for mapping of seasonal salinity, temperature and
chlorophyll a concentration spatial distribution in east coast of
Malaysia
. The objective of this work is to monitor the seasonal in-shore and open
sea
of
Sea
Surface
Salinity
(SSS), temperature and chlorophyll a concentration. The linear regression has
been done for estimation salinity. Brown and Minnet algorithm has also been
compiled for estimation of Sea Surface Temperature (SST). Four algorithms have
been involved in this study which are Aiken’ algorithm, Clark-3-bands
algorithm, Gordon algorithm and Normalized Difference Chlorophyll Index (NDCI).
In this study, the maximum amount of salinity has been determined in the
southwest monsoon; which is 32.39psu and the minimum value during northeast
monsoon (27.34psu). But the maximum chlorophyll concentration value of 56.60 is occurred during northeast monsoon
period whereas the minimum chlorophyll a concentration value of 33.76 has been seen in inter-monsoon
period. It is interesting to find 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 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.
Keywords and phrases: salinity, sea surface temperature, chlorophyll a, linear algorithm, Brown and Minnet algorithm, Aiken’s algorithm, Clark 3-band algorithm, Gordon algorithm.
