Title :
Linear algorithm for salinity distribution modelling from MODIS data
Author_Institution :
Natural Tropical Resources Inf. & Mapping Res. Group (NATRIM Res. Group), Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
This paper was utilized a new approach for modeling sea surface salinity (SSS) from MODIS satellite data. This was based on utilizing of the least squares method in order to retrieve SSS from multi MODIS bands data. The study shows that homogenous offshore sea surface salinity as compared with onshore SSS variations. The onshore SSS are ranged between 28.5 and 29.5 psu whereas the offshore SSS variations have maximum value of 33.8 psu. The results also show a good correlation between in situ SSS measurements and the SSS that is retrieved from MODIS satellite data with high r2 of 0.96 and RMS of bias value of ±0.37 psu. It can be said that least squares method can be used to provide a new algorithm for SSS retrieval from MODIS satellite data.
Keywords :
geophysical signal processing; least squares approximations; oceanographic techniques; remote sensing; seawater; MODIS satellite data; least squares method; linear algorithm; offshore sea surface salinity; onshore SSS variations; salinity distribution modelling; sea surface salinity modeling; Brightness temperature; Information retrieval; Least squares methods; MODIS; Ocean temperature; Optical surface waves; Satellite broadcasting; Sea measurements; Sea surface; Sea surface salinity; MODIS satellite data; Sea surface salinity (SSS); least square estimators; linear model;
Conference_Titel :
Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009
Conference_Location :
Cape Town
Print_ISBN :
978-1-4244-3394-0
Electronic_ISBN :
978-1-4244-3395-7
DOI :
10.1109/IGARSS.2009.5417778
