Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique
Special issue ESA's Soil Moisture and Ocean Salinity Mission - Achievements and Applications.-- 16 pages, 18 figures, 2 tables Abrupt changes in the Soil Moisture and Ocean Salinity (SMOS) brightness temperatures, such as those produced by land/sea/ice transitions and Radio-Frequency Interferen...
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Online Access: | http://hdl.handle.net/10261/135167 https://doi.org/10.1016/j.rse.2015.12.032 https://doi.org/10.13039/501100003329 https://doi.org/10.13039/501100000780 |
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ftcsic:oai:digital.csic.es:10261/135167 2024-02-11T10:08:33+01:00 Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique González Gambau, Verónica Olmedo, Estrella Turiel, Antonio Martínez, Justino Ballabrera-Poy, Joaquim Portabella, Marcos Piles, María Ministerio de Economía y Competitividad (España) European Commission 2016-07 http://hdl.handle.net/10261/135167 https://doi.org/10.1016/j.rse.2015.12.032 https://doi.org/10.13039/501100003329 https://doi.org/10.13039/501100000780 unknown Elsevier https://dx.doi.org/10.1016/j.rse.2015.12.032 Sí doi:10.1016/j.rse.2015.12.032 issn: 0034-4257 e-issn: 1879-0704 Remote Sensing of Environment 180: 205-220 (2016) http://hdl.handle.net/10261/135167 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100000780 none Soil Moisture and Ocean Salinity SMOS Interferometry Radiometry Image reconstruction Nodal sampling Nodal points Sidelobes Radio frequency interferences Salinity retrievals RFI artículo http://purl.org/coar/resource_type/c_6501 2016 ftcsic https://doi.org/10.1016/j.rse.2015.12.03210.13039/50110000332910.13039/501100000780 2024-01-16T10:16:41Z Special issue ESA's Soil Moisture and Ocean Salinity Mission - Achievements and Applications.-- 16 pages, 18 figures, 2 tables Abrupt changes in the Soil Moisture and Ocean Salinity (SMOS) brightness temperatures, such as those produced by land/sea/ice transitions and Radio-Frequency Interference (RFI) sources, produce artificial rippling patterns (i.e. the so-called Gibbs-like contamination) that propagate through the SMOS-reconstructed image. A nodal sampling technique, focused on the reduction of this kind of contamination by sampling at the points where the perturbation cancels, was introduced by González-Gambau et al. (2015). In this work we show that the quality of nodal sampling can be largely improved by refining the determination of the nodal grid. In addition, we have carried out an extensive validation of the resulting data over the ocean. Nodal sampling reduces sidelobe levels and ripples in the reconstructed images leading to brightness temperatures in better agreement with the theoretically modeled ones. Validation of the salinity retrievals against close-to-surface Argo salinity observations shows that nodal sampling leads to improved salinity retrievals in open ocean, while close to the coast land–sea contamination seems to deteriorate the quality. Besides, spectral analysis shows that nodal sampled salinities become closer to what is geophysically expected without loss of effective spatial resolution This work has been funded by the Spanish Ministry of Economy through the National R + D Plan by means of MIDAS-7 project AYA2012-39356-C05-03 and previous grants. The validation part of this work has been done with the support of the FP7-SPACE E-AIMS project (grant agreement 312642) Peer Reviewed Article in Journal/Newspaper Sea ice Digital.CSIC (Spanish National Research Council) Remote Sensing of Environment 180 205 220 |
institution |
Open Polar |
collection |
Digital.CSIC (Spanish National Research Council) |
op_collection_id |
ftcsic |
language |
unknown |
topic |
Soil Moisture and Ocean Salinity SMOS Interferometry Radiometry Image reconstruction Nodal sampling Nodal points Sidelobes Radio frequency interferences Salinity retrievals RFI |
spellingShingle |
Soil Moisture and Ocean Salinity SMOS Interferometry Radiometry Image reconstruction Nodal sampling Nodal points Sidelobes Radio frequency interferences Salinity retrievals RFI González Gambau, Verónica Olmedo, Estrella Turiel, Antonio Martínez, Justino Ballabrera-Poy, Joaquim Portabella, Marcos Piles, María Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique |
topic_facet |
Soil Moisture and Ocean Salinity SMOS Interferometry Radiometry Image reconstruction Nodal sampling Nodal points Sidelobes Radio frequency interferences Salinity retrievals RFI |
description |
Special issue ESA's Soil Moisture and Ocean Salinity Mission - Achievements and Applications.-- 16 pages, 18 figures, 2 tables Abrupt changes in the Soil Moisture and Ocean Salinity (SMOS) brightness temperatures, such as those produced by land/sea/ice transitions and Radio-Frequency Interference (RFI) sources, produce artificial rippling patterns (i.e. the so-called Gibbs-like contamination) that propagate through the SMOS-reconstructed image. A nodal sampling technique, focused on the reduction of this kind of contamination by sampling at the points where the perturbation cancels, was introduced by González-Gambau et al. (2015). In this work we show that the quality of nodal sampling can be largely improved by refining the determination of the nodal grid. In addition, we have carried out an extensive validation of the resulting data over the ocean. Nodal sampling reduces sidelobe levels and ripples in the reconstructed images leading to brightness temperatures in better agreement with the theoretically modeled ones. Validation of the salinity retrievals against close-to-surface Argo salinity observations shows that nodal sampling leads to improved salinity retrievals in open ocean, while close to the coast land–sea contamination seems to deteriorate the quality. Besides, spectral analysis shows that nodal sampled salinities become closer to what is geophysically expected without loss of effective spatial resolution This work has been funded by the Spanish Ministry of Economy through the National R + D Plan by means of MIDAS-7 project AYA2012-39356-C05-03 and previous grants. The validation part of this work has been done with the support of the FP7-SPACE E-AIMS project (grant agreement 312642) Peer Reviewed |
author2 |
Ministerio de Economía y Competitividad (España) European Commission |
format |
Article in Journal/Newspaper |
author |
González Gambau, Verónica Olmedo, Estrella Turiel, Antonio Martínez, Justino Ballabrera-Poy, Joaquim Portabella, Marcos Piles, María |
author_facet |
González Gambau, Verónica Olmedo, Estrella Turiel, Antonio Martínez, Justino Ballabrera-Poy, Joaquim Portabella, Marcos Piles, María |
author_sort |
González Gambau, Verónica |
title |
Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique |
title_short |
Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique |
title_full |
Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique |
title_fullStr |
Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique |
title_full_unstemmed |
Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique |
title_sort |
enhancing smos brightness temperatures over the ocean using the nodal sampling image reconstruction technique |
publisher |
Elsevier |
publishDate |
2016 |
url |
http://hdl.handle.net/10261/135167 https://doi.org/10.1016/j.rse.2015.12.032 https://doi.org/10.13039/501100003329 https://doi.org/10.13039/501100000780 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
https://dx.doi.org/10.1016/j.rse.2015.12.032 Sí doi:10.1016/j.rse.2015.12.032 issn: 0034-4257 e-issn: 1879-0704 Remote Sensing of Environment 180: 205-220 (2016) http://hdl.handle.net/10261/135167 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100000780 |
op_rights |
none |
op_doi |
https://doi.org/10.1016/j.rse.2015.12.03210.13039/50110000332910.13039/501100000780 |
container_title |
Remote Sensing of Environment |
container_volume |
180 |
container_start_page |
205 |
op_container_end_page |
220 |
_version_ |
1790607937758035968 |