Title :
Retrieving seasonal sea surface salinity from MODIS satellite data using a Box-Jenkins algorithm
Author :
Marghany, Maged ; Hashim, Mazlan
Author_Institution :
Inst. of Geospatial Sci. & Technol. (INSTeG), Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
In this study, we investigate the relative ability of a Box-Jenkins algorithm to retrieve sea surface salinity (SSS) from MODIS satellite data. The accuracy of this work has been examined using the root mean square of bias of sea surface salinity retrieved from MODIS satellite data. The study shows comprehensive relationship between Box-Jenkins algorithm, least square method, and in situ SSS measurements with high r2 of 0.98, 0.96 and RMS of bias value of ±0.34 psu, and ±0.32 psu, respectively. Thus, lower RMS of bias value of ± 0.32 psu has performed with Box-Jenkins algorithm. In conclusions, Box-Jenkins algorithm can be used to retrieve time series of SSS from MODIS satellite data as compared to least square algorithm.
Keywords :
least squares approximations; mean square error methods; ocean chemistry; oceanographic techniques; remote sensing; seawater; time series; Box-Jenkins algorithm; MODIS satellite data; bias value; least square method; root mean square; seasonal sea surface salinity retrieval; time series; Correlation; Data models; MODIS; Satellites; Sea measurements; Sea surface salinity; Time series analysis; Box-Jenkins algorithm; MODIS satellite data; Sea surface salinity (SSS); least square algorithm;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4577-1003-2
DOI :
10.1109/IGARSS.2011.6049526
