Examining the least square method to retrieve sea surface salinity from MODIS satellite data

In this study, we investigate the relative ability of least square algorithm to retrieve sea surface salinity (SSS) from MODIS satellite data. We also examine with comprehensive comparison of the root mean square of bias the difference between second polynomial order algorithm and least square algor...

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Main Author: Marghany, Maged
Format: Article
Published: EuroJournals Publishing, Inc. 2010
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Online Access:http://eprints.utm.my/id/eprint/26138/
http://www.eurojournals.com/ejsr_40_3_06.pdf.
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Institution: Universiti Teknologi Malaysia
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spelling my.utm.261382018-10-23T02:04:39Z http://eprints.utm.my/id/eprint/26138/ Examining the least square method to retrieve sea surface salinity from MODIS satellite data Marghany, Maged TD Environmental technology. Sanitary engineering In this study, we investigate the relative ability of least square algorithm to retrieve sea surface salinity (SSS) from MODIS satellite data. We also examine with comprehensive comparison of the root mean square of bias the difference between second polynomial order algorithm and least square algorithm. Both the least squares and algorithm second polynomial order algorithm are used to retrieve the sea surface salinity (SSS) from multi MODIS bands data. Thus, the basic linear model has been solved by using second polynomial order algorithm and least square estimators. The accuracy of this work has been examined using the root mean square of bias of sea surface salinity retrieved from MODIS satellite data and the in situ measurements that are collected along the east coast of peninsular Malaysia by using hydrolab instrument. The study shows comprehensive relationship between least square method and in situ SSS measurements with high r2 of 0.96 and RMS of bias value of ±0.37 psu. The second polynomial order algorithm, however, has lower performance as compared to least square algorithm. Thus, RMS of bias value of ± 7.34 psu has performed with second polynomial order algorithm. In conclusions, the least square algorithm can be used to retrieve SSS from MODIS satellite data. EuroJournals Publishing, Inc. 2010 Article PeerReviewed Marghany, Maged (2010) Examining the least square method to retrieve sea surface salinity from MODIS satellite data. European Journal of Scientific Research, 40 (3). 377 -386. ISSN 1450-216X http://www.eurojournals.com/ejsr_40_3_06.pdf.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TD Environmental technology. Sanitary engineering
spellingShingle TD Environmental technology. Sanitary engineering
Marghany, Maged
Examining the least square method to retrieve sea surface salinity from MODIS satellite data
description In this study, we investigate the relative ability of least square algorithm to retrieve sea surface salinity (SSS) from MODIS satellite data. We also examine with comprehensive comparison of the root mean square of bias the difference between second polynomial order algorithm and least square algorithm. Both the least squares and algorithm second polynomial order algorithm are used to retrieve the sea surface salinity (SSS) from multi MODIS bands data. Thus, the basic linear model has been solved by using second polynomial order algorithm and least square estimators. The accuracy of this work has been examined using the root mean square of bias of sea surface salinity retrieved from MODIS satellite data and the in situ measurements that are collected along the east coast of peninsular Malaysia by using hydrolab instrument. The study shows comprehensive relationship between least square method and in situ SSS measurements with high r2 of 0.96 and RMS of bias value of ±0.37 psu. The second polynomial order algorithm, however, has lower performance as compared to least square algorithm. Thus, RMS of bias value of ± 7.34 psu has performed with second polynomial order algorithm. In conclusions, the least square algorithm can be used to retrieve SSS from MODIS satellite data.
format Article
author Marghany, Maged
author_facet Marghany, Maged
author_sort Marghany, Maged
title Examining the least square method to retrieve sea surface salinity from MODIS satellite data
title_short Examining the least square method to retrieve sea surface salinity from MODIS satellite data
title_full Examining the least square method to retrieve sea surface salinity from MODIS satellite data
title_fullStr Examining the least square method to retrieve sea surface salinity from MODIS satellite data
title_full_unstemmed Examining the least square method to retrieve sea surface salinity from MODIS satellite data
title_sort examining the least square method to retrieve sea surface salinity from modis satellite data
publisher EuroJournals Publishing, Inc.
publishDate 2010
url http://eprints.utm.my/id/eprint/26138/
http://www.eurojournals.com/ejsr_40_3_06.pdf.
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