Editorial for the Special Issue “Sea Surface Salinity Remote Sensing”
This Special Issue gathers papers reporting research on various aspects of remote sensing of sea surface salinity (SSS) and the use of satellites SSS in oceanography. It includes contributions presenting improvements in empirical or theoretical radiative transfer models; mitigation techniques of ext...
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Online Access: | https://www.mdpi.com/2072-4292/11/11/1300 |
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doaj-9fc1c3371b404ca8b876bd368b95898c2020-11-25T00:31:13ZengMDPI AGRemote Sensing2072-42922019-05-011111130010.3390/rs11111300rs11111300Editorial for the Special Issue “Sea Surface Salinity Remote Sensing”Emmanuel Dinnat0Xiaobin Yin1NASA Goddard Space Flight Center, Greenbelt, MD 20771, USABeijing PIESAT Information Technology Co., Ltd., Beijing 100195, ChinaThis Special Issue gathers papers reporting research on various aspects of remote sensing of sea surface salinity (SSS) and the use of satellites SSS in oceanography. It includes contributions presenting improvements in empirical or theoretical radiative transfer models; mitigation techniques of external interference such as radio frequency interferences (RFI) and land contamination; comparisons and validation of remote sensing products with in situ observations; retrieval techniques for improved coastal SSS monitoring, high latitude SSS monitoring and assessment of ocean interactions with the cryosphere; and data fusion techniques combining SSS with sea surface temperature (SST). New instrument technology for the future of SSS remote sensing is also presented.https://www.mdpi.com/2072-4292/11/11/1300sea surface salinityocean surface roughnessmicrowave radiometryremote sensingforward modelretrieval algorithm |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Emmanuel Dinnat Xiaobin Yin |
spellingShingle |
Emmanuel Dinnat Xiaobin Yin Editorial for the Special Issue “Sea Surface Salinity Remote Sensing” Remote Sensing sea surface salinity ocean surface roughness microwave radiometry remote sensing forward model retrieval algorithm |
author_facet |
Emmanuel Dinnat Xiaobin Yin |
author_sort |
Emmanuel Dinnat |
title |
Editorial for the Special Issue “Sea Surface Salinity Remote Sensing” |
title_short |
Editorial for the Special Issue “Sea Surface Salinity Remote Sensing” |
title_full |
Editorial for the Special Issue “Sea Surface Salinity Remote Sensing” |
title_fullStr |
Editorial for the Special Issue “Sea Surface Salinity Remote Sensing” |
title_full_unstemmed |
Editorial for the Special Issue “Sea Surface Salinity Remote Sensing” |
title_sort |
editorial for the special issue “sea surface salinity remote sensing” |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2019-05-01 |
description |
This Special Issue gathers papers reporting research on various aspects of remote sensing of sea surface salinity (SSS) and the use of satellites SSS in oceanography. It includes contributions presenting improvements in empirical or theoretical radiative transfer models; mitigation techniques of external interference such as radio frequency interferences (RFI) and land contamination; comparisons and validation of remote sensing products with in situ observations; retrieval techniques for improved coastal SSS monitoring, high latitude SSS monitoring and assessment of ocean interactions with the cryosphere; and data fusion techniques combining SSS with sea surface temperature (SST). New instrument technology for the future of SSS remote sensing is also presented. |
topic |
sea surface salinity ocean surface roughness microwave radiometry remote sensing forward model retrieval algorithm |
url |
https://www.mdpi.com/2072-4292/11/11/1300 |
work_keys_str_mv |
AT emmanueldinnat editorialforthespecialissueseasurfacesalinityremotesensing AT xiaobinyin editorialforthespecialissueseasurfacesalinityremotesensing |
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1725323015542013952 |