Academic Journal
A Statewide InSAR Velocity Map for California Produced by a Comprehensive Large Scale Analysis of ARIA Standard Products.
| Τίτλος: | A Statewide InSAR Velocity Map for California Produced by a Comprehensive Large Scale Analysis of ARIA Standard Products. |
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| Συγγραφείς: | Sangha, Simran S., Funning, Gareth J., Govorcin, Marin, Bekaert, David P. S. |
| Πηγή: | Earth & Space Science; Aug2026, Vol. 13 Issue 8, p1-21, 21p |
| Θεματικοί όροι: | Radar interferometry, Deformations (Mechanics), Global Positioning System, Artificial satellites, Time series analysis, Seismology |
| Γεωγραφικοί όροι: | California, San Andreas Fault (Calif.), Central Valley (Calif. : Valley) |
| Περίληψη: | Routine Synthetic Aperture Radar (SAR) acquisitions from the Sentinel‐1 constellation enable monitoring of slow surface deformation (millimeters to centimeters per year), yet consistent and accessible pathways for producing validated, user‐ready velocity products remain limited. Here we present (a) a statewide Interferometric SAR (InSAR) line‐of‐sight secular surface velocity map for California derived from standardized Advanced Rapid Imaging and Analysis Sentinel‐1 Geocoded Unwrapped Phase (ARIA‐S1‐GUNW) products spanning 2014–2023, and (b) the details of a scalable processing and validation workflow for producing similar maps. Our workflow leverages several open‐source software tools for post‐processing of GUNW products, time series analysis, corrections for noise, and removal of earthquakes and transient signals. We apply it to data from nine ascending and descending Sentinel‐1 tracks across California, and validate the output against Global Navigation Satellite Systems (GNSS) data. The resulting velocity fields resolve tectonic and anthropogenic deformation signals, including elastic strain accumulation and shallow creep along the San Andreas Fault system, rapid subsidence exceeding 10 cm/yr in the Central Valley, and localized deformation associated with groundwater withdrawal and landsliding. We find millimeter‐per‐year agreement with GNSS velocities, and estimate typical velocity uncertainties to be ≤1 mm/yr over coherent terrain, increasing locally in regions of strong deformation gradients and/or decorrelation. Our velocity map provides an accessible data set for non‐specialists to investigate multiple sources of slow secular deformation across California; our workflow can also be used with GUNW products from the NASA‐ISRO SAR (NISAR) mission, enabling the leveraging of that rich data source in the future. Plain Language Summary: Satellite radar observations provide a powerful way to monitor how Earth's surface moves over time, but turning these data into reliable, easy‐to‐use maps at large scales remains challenging. In this study, we use California as an example to demonstrate how regularly acquired and routinely processed satellite radar data can be used to produce validated maps of ground motion. We analyze observations from the European Commission Sentinel‐1 satellites over the period 2014–2023 using standardized Advanced Rapid Imaging and Analysis Sentinel‐1 Geocoded Unwrapped Phase (ARIA‐S1‐GUNW) products, which measure how the ground moves between satellite passes. By combining thousands of these products with time‐series analysis methods, we can measure the velocity of motion of the ground, accounting for earthquakes, seasonal signals, and atmospheric effects that can distort measurements. We then compare these velocities with Global Navigation Satellite System (GNSS) station data and find agreement within a few millimeters per year in most areas. The resulting maps capture motion from strain accumulation along the San Andreas Fault system, rapid subsidence in the Central Valley, and localized deformation from landslides and human activity. This approach provides a scalable way to monitor Earth's surface and can be extended to NASA‐ISRO SAR (NISAR) satellite observations. Key Points: We present a validated statewide map of secular InSAR surface velocity across California using ARIA‐S1‐GUNW InSAR products from 2014 to 2023Comparison between InSAR and GNSS velocities shows millimeter per year agreementLeveraging standard ARIA‐S1‐GUNW products enables accessible time‐series processing and validation via open‐source ARIA‐tools and MintPy [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Complementary Index |
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| Header | DbId: edb DbLabel: Complementary Index An: 196543152 RelevancyScore: 1082 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1082.42456054688 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Statewide InSAR Velocity Map for California Produced by a Comprehensive Large Scale Analysis of ARIA Standard Products. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sangha%2C+Simran+S%2E%22">Sangha, Simran S.</searchLink><br /><searchLink fieldCode="AR" term="%22Funning%2C+Gareth+J%2E%22">Funning, Gareth J.</searchLink><br /><searchLink fieldCode="AR" term="%22Govorcin%2C+Marin%22">Govorcin, Marin</searchLink><br /><searchLink fieldCode="AR" term="%22Bekaert%2C+David+P%2E+S%2E%22">Bekaert, David P. S.</searchLink> – Name: TitleSource Label: Source Group: Src Data: Earth & Space Science; Aug2026, Vol. 13 Issue 8, p1-21, 21p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Radar+interferometry%22">Radar interferometry</searchLink><br /><searchLink fieldCode="DE" term="%22Deformations+%28Mechanics%29%22">Deformations (Mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Global+Positioning+System%22">Global Positioning System</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+satellites%22">Artificial satellites</searchLink><br /><searchLink fieldCode="DE" term="%22Time+series+analysis%22">Time series analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Seismology%22">Seismology</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22California%22">California</searchLink><br /><searchLink fieldCode="DE" term="%22San+Andreas+Fault+%28Calif%2E%29%22">San Andreas Fault (Calif.)</searchLink><br /><searchLink fieldCode="DE" term="%22Central+Valley+%28Calif%2E+%3A+Valley%29%22">Central Valley (Calif. : Valley)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Routine Synthetic Aperture Radar (SAR) acquisitions from the Sentinel‐1 constellation enable monitoring of slow surface deformation (millimeters to centimeters per year), yet consistent and accessible pathways for producing validated, user‐ready velocity products remain limited. Here we present (a) a statewide Interferometric SAR (InSAR) line‐of‐sight secular surface velocity map for California derived from standardized Advanced Rapid Imaging and Analysis Sentinel‐1 Geocoded Unwrapped Phase (ARIA‐S1‐GUNW) products spanning 2014–2023, and (b) the details of a scalable processing and validation workflow for producing similar maps. Our workflow leverages several open‐source software tools for post‐processing of GUNW products, time series analysis, corrections for noise, and removal of earthquakes and transient signals. We apply it to data from nine ascending and descending Sentinel‐1 tracks across California, and validate the output against Global Navigation Satellite Systems (GNSS) data. The resulting velocity fields resolve tectonic and anthropogenic deformation signals, including elastic strain accumulation and shallow creep along the San Andreas Fault system, rapid subsidence exceeding 10 cm/yr in the Central Valley, and localized deformation associated with groundwater withdrawal and landsliding. We find millimeter‐per‐year agreement with GNSS velocities, and estimate typical velocity uncertainties to be ≤1 mm/yr over coherent terrain, increasing locally in regions of strong deformation gradients and/or decorrelation. Our velocity map provides an accessible data set for non‐specialists to investigate multiple sources of slow secular deformation across California; our workflow can also be used with GUNW products from the NASA‐ISRO SAR (NISAR) mission, enabling the leveraging of that rich data source in the future. Plain Language Summary: Satellite radar observations provide a powerful way to monitor how Earth's surface moves over time, but turning these data into reliable, easy‐to‐use maps at large scales remains challenging. In this study, we use California as an example to demonstrate how regularly acquired and routinely processed satellite radar data can be used to produce validated maps of ground motion. We analyze observations from the European Commission Sentinel‐1 satellites over the period 2014–2023 using standardized Advanced Rapid Imaging and Analysis Sentinel‐1 Geocoded Unwrapped Phase (ARIA‐S1‐GUNW) products, which measure how the ground moves between satellite passes. By combining thousands of these products with time‐series analysis methods, we can measure the velocity of motion of the ground, accounting for earthquakes, seasonal signals, and atmospheric effects that can distort measurements. We then compare these velocities with Global Navigation Satellite System (GNSS) station data and find agreement within a few millimeters per year in most areas. The resulting maps capture motion from strain accumulation along the San Andreas Fault system, rapid subsidence in the Central Valley, and localized deformation from landslides and human activity. This approach provides a scalable way to monitor Earth's surface and can be extended to NASA‐ISRO SAR (NISAR) satellite observations. Key Points: We present a validated statewide map of secular InSAR surface velocity across California using ARIA‐S1‐GUNW InSAR products from 2014 to 2023Comparison between InSAR and GNSS velocities shows millimeter per year agreementLeveraging standard ARIA‐S1‐GUNW products enables accessible time‐series processing and validation via open‐source ARIA‐tools and MintPy [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Earth & Space Science is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1029/2026EA005214 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 1 Subjects: – SubjectFull: California Type: general – SubjectFull: San Andreas Fault (Calif.) Type: general – SubjectFull: Central Valley (Calif. : Valley) Type: general – SubjectFull: Radar interferometry Type: general – SubjectFull: Deformations (Mechanics) Type: general – SubjectFull: Global Positioning System Type: general – SubjectFull: Artificial satellites Type: general – SubjectFull: Time series analysis Type: general – SubjectFull: Seismology Type: general Titles: – TitleFull: A Statewide InSAR Velocity Map for California Produced by a Comprehensive Large Scale Analysis of ARIA Standard Products. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sangha, Simran S. – PersonEntity: Name: NameFull: Funning, Gareth J. – PersonEntity: Name: NameFull: Govorcin, Marin – PersonEntity: Name: NameFull: Bekaert, David P. S. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 23335084 Numbering: – Type: volume Value: 13 – Type: issue Value: 8 Titles: – TitleFull: Earth & Space Science Type: main |
| ResultId | 1 |