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Global seasonal Sentinel-1 interferometric coherence and backscatter data set
This data set is the first-of-its-kind spatial representation of multi-seasonal, global C-band Synthetic Aperture Radar (SAR) interferometric repeat-pass coherence and backscatter signatures. Coverage comprises land masses and ice sheets from 82° Northern to 79° Southern latitudes. The data set is d...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917198/ https://www.ncbi.nlm.nih.gov/pubmed/35277516 http://dx.doi.org/10.1038/s41597-022-01189-6 |
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author | Kellndorfer, Josef Cartus, Oliver Lavalle, Marco Magnard, Christophe Milillo, Pietro Oveisgharan, Shadi Osmanoglu, Batu Rosen, Paul A. Wegmüller, Urs |
author_facet | Kellndorfer, Josef Cartus, Oliver Lavalle, Marco Magnard, Christophe Milillo, Pietro Oveisgharan, Shadi Osmanoglu, Batu Rosen, Paul A. Wegmüller, Urs |
author_sort | Kellndorfer, Josef |
collection | PubMed |
description | This data set is the first-of-its-kind spatial representation of multi-seasonal, global C-band Synthetic Aperture Radar (SAR) interferometric repeat-pass coherence and backscatter signatures. Coverage comprises land masses and ice sheets from 82° Northern to 79° Southern latitudes. The data set is derived from multi-temporal repeat-pass interferometric processing of about 205,000 Sentinel-1 C-band SAR images acquired in Interferometric Wide-Swath Mode from 1-Dec-2019 to 30-Nov-2020. The data set encompasses three sets of seasonal (December-February, March-May, June-August, September-November) metrics produced with a pixel spacing of three arcseconds: 1) Median 6-, 12-, 18-, 24-, 36-, and 48-days repeat-pass coherence at VV or HH polarizations, 2) Mean radiometrically terrain corrected backscatter (γ(0)) at VV and VH, or HH and HV polarizations, and 3) Estimated parameters of an exponential coherence decay model. The data set has been produced to obtain global, spatially detailed information on how decorrelation affects interferometric measurements of surface displacement and is rich in spatial and temporal information for a variety of mapping applications. |
format | Online Article Text |
id | pubmed-8917198 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89171982022-03-28 Global seasonal Sentinel-1 interferometric coherence and backscatter data set Kellndorfer, Josef Cartus, Oliver Lavalle, Marco Magnard, Christophe Milillo, Pietro Oveisgharan, Shadi Osmanoglu, Batu Rosen, Paul A. Wegmüller, Urs Sci Data Data Descriptor This data set is the first-of-its-kind spatial representation of multi-seasonal, global C-band Synthetic Aperture Radar (SAR) interferometric repeat-pass coherence and backscatter signatures. Coverage comprises land masses and ice sheets from 82° Northern to 79° Southern latitudes. The data set is derived from multi-temporal repeat-pass interferometric processing of about 205,000 Sentinel-1 C-band SAR images acquired in Interferometric Wide-Swath Mode from 1-Dec-2019 to 30-Nov-2020. The data set encompasses three sets of seasonal (December-February, March-May, June-August, September-November) metrics produced with a pixel spacing of three arcseconds: 1) Median 6-, 12-, 18-, 24-, 36-, and 48-days repeat-pass coherence at VV or HH polarizations, 2) Mean radiometrically terrain corrected backscatter (γ(0)) at VV and VH, or HH and HV polarizations, and 3) Estimated parameters of an exponential coherence decay model. The data set has been produced to obtain global, spatially detailed information on how decorrelation affects interferometric measurements of surface displacement and is rich in spatial and temporal information for a variety of mapping applications. Nature Publishing Group UK 2022-03-11 /pmc/articles/PMC8917198/ /pubmed/35277516 http://dx.doi.org/10.1038/s41597-022-01189-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Kellndorfer, Josef Cartus, Oliver Lavalle, Marco Magnard, Christophe Milillo, Pietro Oveisgharan, Shadi Osmanoglu, Batu Rosen, Paul A. Wegmüller, Urs Global seasonal Sentinel-1 interferometric coherence and backscatter data set |
title | Global seasonal Sentinel-1 interferometric coherence and backscatter data set |
title_full | Global seasonal Sentinel-1 interferometric coherence and backscatter data set |
title_fullStr | Global seasonal Sentinel-1 interferometric coherence and backscatter data set |
title_full_unstemmed | Global seasonal Sentinel-1 interferometric coherence and backscatter data set |
title_short | Global seasonal Sentinel-1 interferometric coherence and backscatter data set |
title_sort | global seasonal sentinel-1 interferometric coherence and backscatter data set |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917198/ https://www.ncbi.nlm.nih.gov/pubmed/35277516 http://dx.doi.org/10.1038/s41597-022-01189-6 |
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