Sentinel-1 Consecutive Interferogram Stacking Approach (CISA) for High-Resolution and Near-Real-Time Ground Subsidence Mapping.
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| Title: | Sentinel-1 Consecutive Interferogram Stacking Approach (CISA) for High-Resolution and Near-Real-Time Ground Subsidence Mapping. |
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| Authors: | Hussain, Sajid1 (AUTHOR), Liu, Fei2 (AUTHOR), Pan, Bin1,3 (AUTHOR), Xu, Rui4 (AUTHOR) xiurui7@126.com, Afzal, Zeeshan5 (AUTHOR), Hussain, Wajid1 (AUTHOR), Pan, Yucheng1,2 (AUTHOR), Li, Heping1,3 (AUTHOR) |
| Source: | Remote Sensing. May2026, Vol. 18 Issue 10, p1486. 32p. |
| Subjects: | Land subsidence, Radar interferometry, Earthquake hazard analysis, Fault zones, Urbanization |
| Geographic Terms: | Pakistan |
| Abstract: | Highlights: What are the main findings? The Consecutive Interferogram Stacking Approach (CISA) generates interferograms between consecutive SAR acquisitions to minimize temporal decorrelation, significantly enhancing interferogram coherence and quality. Displacement patterns from multi-dimensional modeling are consistent with blind-fault-related structures, suggesting that fault zones may influence subsidence patterns, while groundwater withdrawal and urbanization likely contribute to observed periodic deformation cycles. What are the implications of the main findings? CISA enables near-real-time subsidence monitoring—new SAR acquisitions require only one additional interferogram with the previous image to update deformation velocities, eliminating the need to reprocess entire datasets as required by conventional techniques. Characterization of these deformation patterns offers insights for seismic hazard considerations in densely populated regions, supporting infrastructure resilience planning and informed urban development strategies. Interferometric Synthetic Aperture Radar (InSAR) is crucial for monitoring ground displacement, particularly in Pakistan's capital area, where urban expansion and active geotectonics converge. This study introduces the Consecutive Interferogram Stacking Approach (CISA), a processing framework optimized for near-real-time deformation monitoring using full-resolution Sentinel-1 data from adjacent acquisition pairs. Unlike conventional InSAR techniques that rely on spatial multilooking to suppress phase noise—which sacrifices spatial resolution for computational efficiency—CISA preserves native resolution through sequential interferogram stacking, accepting that short-interval interferograms retain geophysical phase instabilities (including fading signals) inherent to scatterer decorrelation. By minimizing temporal decorrelation through consecutive pairing, CISA enhances interferogram coherence (6–14% improvement) and reduces Root Mean Square Error (RMSE) by approximately 25% compared to conventional multilooked time series, while enabling the computational efficiency critical for operational applications. The framework's incremental architecture allows velocity updates within hours of new image acquisition—requiring only single interferogram addition rather than complete network reprocessing—making it suitable for rapid-response hazard assessment where latency constraints outweigh the need for long-baseline phase filtering. CISA reveals spatiotemporal subsidence patterns potentially reflecting the influence of fault zone geometry, groundwater fluctuation, and urbanization, with full-resolution analysis delineating linear deformation patterns spatially consistent with blind fault traces through multi-directional displacement modeling. These findings demonstrate that operational monitoring of geohazards can be achieved through strategic trade-offs between processing latency and geophysical noise suppression, providing actionable intelligence for infrastructure risk management in tectonically active urban environments. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI 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. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 194141011 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Sentinel-1 Consecutive Interferogram Stacking Approach (CISA) for High-Resolution and Near-Real-Time Ground Subsidence Mapping. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hussain%2C+Sajid%22">Hussain, Sajid</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Fei%22">Liu, Fei</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pan%2C+Bin%22">Pan, Bin</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Rui%22">Xu, Rui</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> xiurui7@126.com</i><br /><searchLink fieldCode="AR" term="%22Afzal%2C+Zeeshan%22">Afzal, Zeeshan</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hussain%2C+Wajid%22">Hussain, Wajid</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pan%2C+Yucheng%22">Pan, Yucheng</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Heping%22">Li, Heping</searchLink><relatesTo>1,3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. May2026, Vol. 18 Issue 10, p1486. 32p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Land+subsidence%22">Land subsidence</searchLink><br /><searchLink fieldCode="DE" term="%22Radar+interferometry%22">Radar interferometry</searchLink><br /><searchLink fieldCode="DE" term="%22Earthquake+hazard+analysis%22">Earthquake hazard analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Fault+zones%22">Fault zones</searchLink><br /><searchLink fieldCode="DE" term="%22Urbanization%22">Urbanization</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Pakistan%22">Pakistan</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? The Consecutive Interferogram Stacking Approach (CISA) generates interferograms between consecutive SAR acquisitions to minimize temporal decorrelation, significantly enhancing interferogram coherence and quality. Displacement patterns from multi-dimensional modeling are consistent with blind-fault-related structures, suggesting that fault zones may influence subsidence patterns, while groundwater withdrawal and urbanization likely contribute to observed periodic deformation cycles. What are the implications of the main findings? CISA enables near-real-time subsidence monitoring—new SAR acquisitions require only one additional interferogram with the previous image to update deformation velocities, eliminating the need to reprocess entire datasets as required by conventional techniques. Characterization of these deformation patterns offers insights for seismic hazard considerations in densely populated regions, supporting infrastructure resilience planning and informed urban development strategies. Interferometric Synthetic Aperture Radar (InSAR) is crucial for monitoring ground displacement, particularly in Pakistan's capital area, where urban expansion and active geotectonics converge. This study introduces the Consecutive Interferogram Stacking Approach (CISA), a processing framework optimized for near-real-time deformation monitoring using full-resolution Sentinel-1 data from adjacent acquisition pairs. Unlike conventional InSAR techniques that rely on spatial multilooking to suppress phase noise—which sacrifices spatial resolution for computational efficiency—CISA preserves native resolution through sequential interferogram stacking, accepting that short-interval interferograms retain geophysical phase instabilities (including fading signals) inherent to scatterer decorrelation. By minimizing temporal decorrelation through consecutive pairing, CISA enhances interferogram coherence (6–14% improvement) and reduces Root Mean Square Error (RMSE) by approximately 25% compared to conventional multilooked time series, while enabling the computational efficiency critical for operational applications. The framework's incremental architecture allows velocity updates within hours of new image acquisition—requiring only single interferogram addition rather than complete network reprocessing—making it suitable for rapid-response hazard assessment where latency constraints outweigh the need for long-baseline phase filtering. CISA reveals spatiotemporal subsidence patterns potentially reflecting the influence of fault zone geometry, groundwater fluctuation, and urbanization, with full-resolution analysis delineating linear deformation patterns spatially consistent with blind fault traces through multi-directional displacement modeling. These findings demonstrate that operational monitoring of geohazards can be achieved through strategic trade-offs between processing latency and geophysical noise suppression, providing actionable intelligence for infrastructure risk management in tectonically active urban environments. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI 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: 10.3390/rs18101486 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 32 StartPage: 1486 Subjects: – SubjectFull: Land subsidence Type: general – SubjectFull: Radar interferometry Type: general – SubjectFull: Earthquake hazard analysis Type: general – SubjectFull: Fault zones Type: general – SubjectFull: Urbanization Type: general – SubjectFull: Pakistan Type: general Titles: – TitleFull: Sentinel-1 Consecutive Interferogram Stacking Approach (CISA) for High-Resolution and Near-Real-Time Ground Subsidence Mapping. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hussain, Sajid – PersonEntity: Name: NameFull: Liu, Fei – PersonEntity: Name: NameFull: Pan, Bin – PersonEntity: Name: NameFull: Xu, Rui – PersonEntity: Name: NameFull: Afzal, Zeeshan – PersonEntity: Name: NameFull: Hussain, Wajid – PersonEntity: Name: NameFull: Pan, Yucheng – PersonEntity: Name: NameFull: Li, Heping IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 10 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
