SWOT Level-3 Overview algorithms and examples Article Swipe
Marie–Isabelle Pujol
,
Gérald Dibarboure
,
Yannice Faugère
,
Antoine Delepoulle
,
Frédéric Briol
,
Matthias Raynal
,
Clément Ubelmann
,
Robin Chevrier
,
Anaëlle Tréboutte
,
Pierre Prandi
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-egu24-1959
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-egu24-1959
The Surface Water Ocean Topography (SWOT) mission was launched in December 2023.It is the result of cooperation between CNES, NASA and their partners from the Canadian and UK Space Agencies. SWOT carries a unique altimetric payload, including a Ku-band Jason-class nadir altimeter and a Ka-band SAR-interferometric (KaRIn) wide-swath altimeter providing 2 swaths 50-km wide. It offers new opportunity for the observation of the small mesoscale structures over the oceans, including near coast and high latitude areas. Thanks to these observation capabilities, SWOT could contribute to a better understanding of the physical processes at play at these scales, and to the applications that flow from them.Few months after its launch, Level-2 product of the KaRIn measurement were made available for the SWOT Science Team. These products however remain complex and oriented for the altimetry expert community, while many non-expert users may need the swath measurement for different applications. To answer these needs, a Level-3 product was developed in the context of the SWOT Science Team Project DESMOS. It is the result of different processing steps including the use of the state of the art of different geophysical corrections (e.g. Mean Sea Surface, ocean tide), aiming to improve the quality of the sea level measurement at small mesoscale; the multi-mission calibration, that makes the SWOT measurements consistent with other altimeters; the data selection, to identify invalid measurements; the sea surface height noise-mitigation, aiming reduce the noise level on SSHA and allowing the estimation of the geostrophic current and vorticity. We present here the SWOT KaRIn Level-3 product.
Related Topics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.5194/egusphere-egu24-1959
- OA Status
- gold
- Cited By
- 7
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392587943
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4392587943Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.5194/egusphere-egu24-1959Digital Object Identifier
- Title
-
SWOT Level-3 Overview algorithms and examplesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-03-08Full publication date if available
- Authors
-
Marie–Isabelle Pujol, Gérald Dibarboure, Yannice Faugère, Antoine Delepoulle, Frédéric Briol, Matthias Raynal, Clément Ubelmann, Robin Chevrier, Anaëlle Tréboutte, Pierre PrandiList of authors in order
- Landing page
-
https://doi.org/10.5194/egusphere-egu24-1959Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.5194/egusphere-egu24-1959Direct OA link when available
- Concepts
-
SWOT analysis, Computer science, Algorithm, Economics, ManagementTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 3Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4392587943 |
|---|---|
| doi | https://doi.org/10.5194/egusphere-egu24-1959 |
| ids.doi | https://doi.org/10.5194/egusphere-egu24-1959 |
| ids.openalex | https://openalex.org/W4392587943 |
| fwci | 4.76729281 |
| type | preprint |
| title | SWOT Level-3 Overview algorithms and examples |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10567 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.6985999941825867 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2209 |
| topics[0].subfield.display_name | Industrial and Manufacturing Engineering |
| topics[0].display_name | Vehicle Routing Optimization Methods |
| topics[1].id | https://openalex.org/T11942 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.6539999842643738 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2203 |
| topics[1].subfield.display_name | Automotive Engineering |
| topics[1].display_name | Transportation and Mobility Innovations |
| topics[2].id | https://openalex.org/T11223 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.6207000017166138 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2209 |
| topics[2].subfield.display_name | Industrial and Manufacturing Engineering |
| topics[2].display_name | Maritime Ports and Logistics |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C119059837 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6930421590805054 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q175096 |
| concepts[0].display_name | SWOT analysis |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.5247823596000671 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C11413529 |
| concepts[2].level | 1 |
| concepts[2].score | 0.4605196714401245 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[2].display_name | Algorithm |
| concepts[3].id | https://openalex.org/C162324750 |
| concepts[3].level | 0 |
| concepts[3].score | 0.08744990825653076 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[3].display_name | Economics |
| concepts[4].id | https://openalex.org/C187736073 |
| concepts[4].level | 1 |
| concepts[4].score | 0.06866714358329773 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2920921 |
| concepts[4].display_name | Management |
| keywords[0].id | https://openalex.org/keywords/swot-analysis |
| keywords[0].score | 0.6930421590805054 |
| keywords[0].display_name | SWOT analysis |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.5247823596000671 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/algorithm |
| keywords[2].score | 0.4605196714401245 |
| keywords[2].display_name | Algorithm |
| keywords[3].id | https://openalex.org/keywords/economics |
| keywords[3].score | 0.08744990825653076 |
| keywords[3].display_name | Economics |
| keywords[4].id | https://openalex.org/keywords/management |
| keywords[4].score | 0.06866714358329773 |
| keywords[4].display_name | Management |
| language | en |
| locations[0].id | doi:10.5194/egusphere-egu24-1959 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.5194/egusphere-egu24-1959 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5107896422 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Marie–Isabelle Pujol |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Marie-Isabelle Pujol |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5060199060 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-3644-2495 |
| authorships[1].author.display_name | Gérald Dibarboure |
| authorships[1].countries | FR |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I2799535048 |
| authorships[1].affiliations[0].raw_affiliation_string | CNES, France |
| authorships[1].institutions[0].id | https://openalex.org/I2799535048 |
| authorships[1].institutions[0].ror | https://ror.org/04h1h0y33 |
| authorships[1].institutions[0].type | government |
| authorships[1].institutions[0].lineage | https://openalex.org/I2799535048 |
| authorships[1].institutions[0].country_code | FR |
| authorships[1].institutions[0].display_name | Centre National d'Études Spatiales |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Gerald Dibarboure |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | CNES, France |
| authorships[2].author.id | https://openalex.org/A5039054609 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-3764-1429 |
| authorships[2].author.display_name | Yannice Faugère |
| authorships[2].countries | FR |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I2799535048 |
| authorships[2].affiliations[0].raw_affiliation_string | CNES, France |
| authorships[2].institutions[0].id | https://openalex.org/I2799535048 |
| authorships[2].institutions[0].ror | https://ror.org/04h1h0y33 |
| authorships[2].institutions[0].type | government |
| authorships[2].institutions[0].lineage | https://openalex.org/I2799535048 |
| authorships[2].institutions[0].country_code | FR |
| authorships[2].institutions[0].display_name | Centre National d'Études Spatiales |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Yannice Faugere |
| authorships[2].is_corresponding | True |
| authorships[2].raw_affiliation_strings | CNES, France |
| authorships[3].author.id | https://openalex.org/A5078338881 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-4922-4198 |
| authorships[3].author.display_name | Antoine Delepoulle |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Antoine Delepoulle |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5108825369 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Frédéric Briol |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Frederic Briol |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5059495272 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-4535-5556 |
| authorships[5].author.display_name | Matthias Raynal |
| authorships[5].countries | FR |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I2799535048 |
| authorships[5].affiliations[0].raw_affiliation_string | CNES, France |
| authorships[5].institutions[0].id | https://openalex.org/I2799535048 |
| authorships[5].institutions[0].ror | https://ror.org/04h1h0y33 |
| authorships[5].institutions[0].type | government |
| authorships[5].institutions[0].lineage | https://openalex.org/I2799535048 |
| authorships[5].institutions[0].country_code | FR |
| authorships[5].institutions[0].display_name | Centre National d'Études Spatiales |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Matthias Raynal |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | CNES, France |
| authorships[6].author.id | https://openalex.org/A5041017262 |
| authorships[6].author.orcid | https://orcid.org/0000-0003-3609-2798 |
| authorships[6].author.display_name | Clément Ubelmann |
| authorships[6].countries | FR |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I47431100 |
| authorships[6].affiliations[0].raw_affiliation_string | DATLAS, France |
| authorships[6].institutions[0].id | https://openalex.org/I47431100 |
| authorships[6].institutions[0].ror | https://ror.org/038sc5x72 |
| authorships[6].institutions[0].type | company |
| authorships[6].institutions[0].lineage | https://openalex.org/I47431100 |
| authorships[6].institutions[0].country_code | FR |
| authorships[6].institutions[0].display_name | Dassault Systèmes (France) |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Clement Ubelmann |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | DATLAS, France |
| authorships[7].author.id | https://openalex.org/A5087304736 |
| authorships[7].author.orcid | |
| authorships[7].author.display_name | Robin Chevrier |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Robin Chevrier |
| authorships[7].is_corresponding | False |
| authorships[8].author.id | https://openalex.org/A5086655848 |
| authorships[8].author.orcid | |
| authorships[8].author.display_name | Anaëlle Tréboutte |
| authorships[8].author_position | middle |
| authorships[8].raw_author_name | Anaelle Treboutte |
| authorships[8].is_corresponding | False |
| authorships[9].author.id | https://openalex.org/A5046673710 |
| authorships[9].author.orcid | https://orcid.org/0000-0001-8224-0486 |
| authorships[9].author.display_name | Pierre Prandi |
| authorships[9].author_position | last |
| authorships[9].raw_author_name | Pierre Prandi |
| authorships[9].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.5194/egusphere-egu24-1959 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | SWOT Level-3 Overview algorithms and examples |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10567 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.6985999941825867 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2209 |
| primary_topic.subfield.display_name | Industrial and Manufacturing Engineering |
| primary_topic.display_name | Vehicle Routing Optimization Methods |
| related_works | https://openalex.org/W2748952813, https://openalex.org/W4205908667, https://openalex.org/W2807952359, https://openalex.org/W2264828925, https://openalex.org/W4312213642, https://openalex.org/W2378407273, https://openalex.org/W90157332, https://openalex.org/W2364866955, https://openalex.org/W2887776298, https://openalex.org/W2967320841 |
| cited_by_count | 7 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 4 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 3 |
| locations_count | 1 |
| best_oa_location.id | doi:10.5194/egusphere-egu24-1959 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.5194/egusphere-egu24-1959 |
| primary_location.id | doi:10.5194/egusphere-egu24-1959 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.5194/egusphere-egu24-1959 |
| publication_date | 2024-03-08 |
| publication_year | 2024 |
| referenced_works_count | 0 |
| abstract_inverted_index.2 | 50 |
| abstract_inverted_index.a | 32, 37, 43, 85, 151 |
| abstract_inverted_index.It | 54, 166 |
| abstract_inverted_index.To | 147 |
| abstract_inverted_index.UK | 27 |
| abstract_inverted_index.We | 247 |
| abstract_inverted_index.at | 92, 94, 203 |
| abstract_inverted_index.in | 9, 156 |
| abstract_inverted_index.is | 12, 167 |
| abstract_inverted_index.of | 15, 61, 88, 111, 159, 170, 177, 180, 183, 198, 241 |
| abstract_inverted_index.on | 235 |
| abstract_inverted_index.to | 77, 84, 98, 194, 221 |
| abstract_inverted_index.Sea | 189 |
| abstract_inverted_index.The | 0 |
| abstract_inverted_index.and | 20, 26, 42, 72, 97, 128, 237, 245 |
| abstract_inverted_index.art | 182 |
| abstract_inverted_index.for | 58, 118, 130, 144 |
| abstract_inverted_index.its | 107 |
| abstract_inverted_index.may | 139 |
| abstract_inverted_index.new | 56 |
| abstract_inverted_index.sea | 200, 226 |
| abstract_inverted_index.the | 13, 24, 59, 62, 67, 89, 99, 112, 119, 131, 141, 157, 160, 168, 175, 178, 181, 196, 199, 206, 211, 218, 225, 232, 239, 242, 250 |
| abstract_inverted_index.use | 176 |
| abstract_inverted_index.was | 7, 154 |
| abstract_inverted_index.Mean | 188 |
| abstract_inverted_index.NASA | 19 |
| abstract_inverted_index.SSHA | 236 |
| abstract_inverted_index.SWOT | 30, 81, 120, 161, 212, 251 |
| abstract_inverted_index.Team | 163 |
| abstract_inverted_index.data | 219 |
| abstract_inverted_index.flow | 102 |
| abstract_inverted_index.from | 23, 103 |
| abstract_inverted_index.here | 249 |
| abstract_inverted_index.high | 73 |
| abstract_inverted_index.made | 116 |
| abstract_inverted_index.many | 136 |
| abstract_inverted_index.near | 70 |
| abstract_inverted_index.need | 140 |
| abstract_inverted_index.over | 66 |
| abstract_inverted_index.play | 93 |
| abstract_inverted_index.that | 101, 209 |
| abstract_inverted_index.were | 115 |
| abstract_inverted_index.with | 215 |
| abstract_inverted_index.(e.g. | 187 |
| abstract_inverted_index.50-km | 52 |
| abstract_inverted_index.CNES, | 18 |
| abstract_inverted_index.KaRIn | 113, 252 |
| abstract_inverted_index.Ocean | 3 |
| abstract_inverted_index.Space | 28 |
| abstract_inverted_index.Team. | 122 |
| abstract_inverted_index.These | 123 |
| abstract_inverted_index.Water | 2 |
| abstract_inverted_index.after | 106 |
| abstract_inverted_index.coast | 71 |
| abstract_inverted_index.could | 82 |
| abstract_inverted_index.level | 201, 234 |
| abstract_inverted_index.makes | 210 |
| abstract_inverted_index.nadir | 40 |
| abstract_inverted_index.noise | 233 |
| abstract_inverted_index.ocean | 191 |
| abstract_inverted_index.other | 216 |
| abstract_inverted_index.small | 63, 204 |
| abstract_inverted_index.state | 179 |
| abstract_inverted_index.steps | 173 |
| abstract_inverted_index.swath | 142 |
| abstract_inverted_index.their | 21 |
| abstract_inverted_index.these | 78, 95, 149 |
| abstract_inverted_index.users | 138 |
| abstract_inverted_index.while | 135 |
| abstract_inverted_index.wide. | 53 |
| abstract_inverted_index.(SWOT) | 5 |
| abstract_inverted_index.Thanks | 76 |
| abstract_inverted_index.aiming | 193, 230 |
| abstract_inverted_index.answer | 148 |
| abstract_inverted_index.areas. | 75 |
| abstract_inverted_index.better | 86 |
| abstract_inverted_index.expert | 133 |
| abstract_inverted_index.height | 228 |
| abstract_inverted_index.months | 105 |
| abstract_inverted_index.needs, | 150 |
| abstract_inverted_index.offers | 55 |
| abstract_inverted_index.reduce | 231 |
| abstract_inverted_index.remain | 126 |
| abstract_inverted_index.result | 14, 169 |
| abstract_inverted_index.swaths | 51 |
| abstract_inverted_index.tide), | 192 |
| abstract_inverted_index.unique | 33 |
| abstract_inverted_index.(KaRIn) | 46 |
| abstract_inverted_index.2023.It | 11 |
| abstract_inverted_index.DESMOS. | 165 |
| abstract_inverted_index.Ka-band | 44 |
| abstract_inverted_index.Ku-band | 38 |
| abstract_inverted_index.Level-2 | 109 |
| abstract_inverted_index.Level-3 | 152, 253 |
| abstract_inverted_index.Project | 164 |
| abstract_inverted_index.Science | 121, 162 |
| abstract_inverted_index.Surface | 1 |
| abstract_inverted_index.between | 17 |
| abstract_inverted_index.carries | 31 |
| abstract_inverted_index.complex | 127 |
| abstract_inverted_index.context | 158 |
| abstract_inverted_index.current | 244 |
| abstract_inverted_index.however | 125 |
| abstract_inverted_index.improve | 195 |
| abstract_inverted_index.invalid | 223 |
| abstract_inverted_index.launch, | 108 |
| abstract_inverted_index.mission | 6 |
| abstract_inverted_index.oceans, | 68 |
| abstract_inverted_index.present | 248 |
| abstract_inverted_index.product | 110, 153 |
| abstract_inverted_index.quality | 197 |
| abstract_inverted_index.scales, | 96 |
| abstract_inverted_index.surface | 227 |
| abstract_inverted_index.Canadian | 25 |
| abstract_inverted_index.December | 10 |
| abstract_inverted_index.Surface, | 190 |
| abstract_inverted_index.allowing | 238 |
| abstract_inverted_index.identify | 222 |
| abstract_inverted_index.latitude | 74 |
| abstract_inverted_index.launched | 8 |
| abstract_inverted_index.oriented | 129 |
| abstract_inverted_index.partners | 22 |
| abstract_inverted_index.payload, | 35 |
| abstract_inverted_index.physical | 90 |
| abstract_inverted_index.product. | 254 |
| abstract_inverted_index.products | 124 |
| abstract_inverted_index.them.Few | 104 |
| abstract_inverted_index.Agencies. | 29 |
| abstract_inverted_index.altimeter | 41, 48 |
| abstract_inverted_index.altimetry | 132 |
| abstract_inverted_index.available | 117 |
| abstract_inverted_index.developed | 155 |
| abstract_inverted_index.different | 145, 171, 184 |
| abstract_inverted_index.including | 36, 69, 174 |
| abstract_inverted_index.mesoscale | 64 |
| abstract_inverted_index.processes | 91 |
| abstract_inverted_index.providing | 49 |
| abstract_inverted_index.Topography | 4 |
| abstract_inverted_index.altimetric | 34 |
| abstract_inverted_index.community, | 134 |
| abstract_inverted_index.consistent | 214 |
| abstract_inverted_index.contribute | 83 |
| abstract_inverted_index.estimation | 240 |
| abstract_inverted_index.mesoscale; | 205 |
| abstract_inverted_index.non-expert | 137 |
| abstract_inverted_index.processing | 172 |
| abstract_inverted_index.selection, | 220 |
| abstract_inverted_index.structures | 65 |
| abstract_inverted_index.vorticity. | 246 |
| abstract_inverted_index.wide-swath | 47 |
| abstract_inverted_index.Jason-class | 39 |
| abstract_inverted_index.altimeters; | 217 |
| abstract_inverted_index.cooperation | 16 |
| abstract_inverted_index.corrections | 186 |
| abstract_inverted_index.geophysical | 185 |
| abstract_inverted_index.geostrophic | 243 |
| abstract_inverted_index.measurement | 114, 143, 202 |
| abstract_inverted_index.observation | 60, 79 |
| abstract_inverted_index.opportunity | 57 |
| abstract_inverted_index.applications | 100 |
| abstract_inverted_index.calibration, | 208 |
| abstract_inverted_index.measurements | 213 |
| abstract_inverted_index.applications. | 146 |
| abstract_inverted_index.capabilities, | 80 |
| abstract_inverted_index.measurements; | 224 |
| abstract_inverted_index.multi-mission | 207 |
| abstract_inverted_index.understanding | 87 |
| abstract_inverted_index.noise-mitigation, | 229 |
| abstract_inverted_index.SAR-interferometric | 45 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 96 |
| corresponding_author_ids | https://openalex.org/A5039054609 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 10 |
| corresponding_institution_ids | https://openalex.org/I2799535048 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
| sustainable_development_goals[0].score | 0.8199999928474426 |
| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile.value | 0.91977215 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |