{"title":"MODIS卫星海面盐度反演的最小二乘算法","authors":"M. Marghany","doi":"10.1109/ICSIPA.2009.5478707","DOIUrl":null,"url":null,"abstract":"This paper presents a new approach for retrieving sea surface salinity (SSS) from MODIS satellite data. In doing so, the least squares method is used which is based on the hypothesis of linearity between visual bands and the real sea surface salinity. The study shows that offshore sea surface salinity tends to be homogenous with SSS value of 33.8 psu. Onshore SSS variation, however, has irregular pattern as compared with offshore SSS that is ranged between 28.5 and 29.5 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. In conclusion, the least squares method can be used to provide a new algorithm for SSS retrieval from MODIS satellite data with RMS of bias value of ±0.37 psu.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Least square algorithm for sea surface salinity retrieving from MODIS satellite data\",\"authors\":\"M. Marghany\",\"doi\":\"10.1109/ICSIPA.2009.5478707\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new approach for retrieving sea surface salinity (SSS) from MODIS satellite data. In doing so, the least squares method is used which is based on the hypothesis of linearity between visual bands and the real sea surface salinity. The study shows that offshore sea surface salinity tends to be homogenous with SSS value of 33.8 psu. Onshore SSS variation, however, has irregular pattern as compared with offshore SSS that is ranged between 28.5 and 29.5 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. In conclusion, the least squares method can be used to provide a new algorithm for SSS retrieval from MODIS satellite data with RMS of bias value of ±0.37 psu.\",\"PeriodicalId\":400165,\"journal\":{\"name\":\"2009 IEEE International Conference on Signal and Image Processing Applications\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Signal and Image Processing Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIPA.2009.5478707\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Signal and Image Processing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIPA.2009.5478707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Least square algorithm for sea surface salinity retrieving from MODIS satellite data
This paper presents a new approach for retrieving sea surface salinity (SSS) from MODIS satellite data. In doing so, the least squares method is used which is based on the hypothesis of linearity between visual bands and the real sea surface salinity. The study shows that offshore sea surface salinity tends to be homogenous with SSS value of 33.8 psu. Onshore SSS variation, however, has irregular pattern as compared with offshore SSS that is ranged between 28.5 and 29.5 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. In conclusion, the least squares method can be used to provide a new algorithm for SSS retrieval from MODIS satellite data with RMS of bias value of ±0.37 psu.
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