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The Stepwise Multi-Temporal Interferometric Synthetic Aperture Radar with Partially Coherent Scatterers for Long-Time Series Deformation Monitoring.

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Title: The Stepwise Multi-Temporal Interferometric Synthetic Aperture Radar with Partially Coherent Scatterers for Long-Time Series Deformation Monitoring.
Authors: Zhang, Jinbao1,2,3,4 (AUTHOR), Duan, Wei2,5 (AUTHOR), Fu, Xikai1,2,3 (AUTHOR) fuxk@aircas.ac.cn, Yun, Ye1,2,3,4 (AUTHOR), Lv, Xiaolei1,2,3,4,5 (AUTHOR)
Source: Remote Sensing. Apr2025, Vol. 17 Issue 8, p1374. 18p.
Subjects: Coherent radar, Historical libraries, Time series analysis, Synthetic aperture radar, Interferometry, Land subsidence
Abstract: In recent decades, the interferometric synthetic aperture radar (InSAR) technique has emerged as a powerful tool for monitoring ground subsidence and geohazards. Various satellite SAR systems with different modes, such as Sentinel-1 and Lutan-1, have produced abundant SAR datasets with wide coverage and large historical archives, which have significantly influenced long-term deformation monitoring applications. However, large-scale InSAR data have posed significant challenges to conventional InSAR methods. These issues include the computational burden and storage of multi-temporal InSAR (MT-InSAR) methods, as well as temporal decorrelation for coherent scatterers with long temporal baselines. In this study, we propose a stepwise MT-InSAR with a temporal coherent scatterer method to address these problems. First, a batch sequential method is introduced in the algorithm by grouping the SAR dataset in the time domain based on the average coherence distribution and then applying permanent scatterer interferometry to each temporal subset. Second, a multi-layer network is employed to estimate deformation for partially coherent scatterers using small baseline subset interferograms, with permanent scatterer deformation parameters as the reference. Finally, the final deformation rate and displacement time series were obtained by incorporating all the temporal subsets. The proposed method efficiently generates high-density InSAR deformation measurements for long-time series analysis. The proposed method was validated using 9 years of Sentinel-1 data with 229 SAR images from Jakarta, Indonesia. The deformation results were compared with those of conventional methods and global navigation satellite system data to confirm the effectiveness of the proposed method. [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.)
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  Data: The Stepwise Multi-Temporal Interferometric Synthetic Aperture Radar with Partially Coherent Scatterers for Long-Time Series Deformation Monitoring.
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  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Apr2025, Vol. 17 Issue 8, p1374. 18p.
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  Data: <searchLink fieldCode="DE" term="%22Coherent+radar%22">Coherent radar</searchLink><br /><searchLink fieldCode="DE" term="%22Historical+libraries%22">Historical libraries</searchLink><br /><searchLink fieldCode="DE" term="%22Time+series+analysis%22">Time series analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Synthetic+aperture+radar%22">Synthetic aperture radar</searchLink><br /><searchLink fieldCode="DE" term="%22Interferometry%22">Interferometry</searchLink><br /><searchLink fieldCode="DE" term="%22Land+subsidence%22">Land subsidence</searchLink>
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  Data: In recent decades, the interferometric synthetic aperture radar (InSAR) technique has emerged as a powerful tool for monitoring ground subsidence and geohazards. Various satellite SAR systems with different modes, such as Sentinel-1 and Lutan-1, have produced abundant SAR datasets with wide coverage and large historical archives, which have significantly influenced long-term deformation monitoring applications. However, large-scale InSAR data have posed significant challenges to conventional InSAR methods. These issues include the computational burden and storage of multi-temporal InSAR (MT-InSAR) methods, as well as temporal decorrelation for coherent scatterers with long temporal baselines. In this study, we propose a stepwise MT-InSAR with a temporal coherent scatterer method to address these problems. First, a batch sequential method is introduced in the algorithm by grouping the SAR dataset in the time domain based on the average coherence distribution and then applying permanent scatterer interferometry to each temporal subset. Second, a multi-layer network is employed to estimate deformation for partially coherent scatterers using small baseline subset interferograms, with permanent scatterer deformation parameters as the reference. Finally, the final deformation rate and displacement time series were obtained by incorporating all the temporal subsets. The proposed method efficiently generates high-density InSAR deformation measurements for long-time series analysis. The proposed method was validated using 9 years of Sentinel-1 data with 229 SAR images from Jakarta, Indonesia. The deformation results were compared with those of conventional methods and global navigation satellite system data to confirm the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]
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  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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        Text: English
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      – SubjectFull: Time series analysis
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      – SubjectFull: Synthetic aperture radar
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      – SubjectFull: Interferometry
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      – SubjectFull: Land subsidence
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      – TitleFull: The Stepwise Multi-Temporal Interferometric Synthetic Aperture Radar with Partially Coherent Scatterers for Long-Time Series Deformation Monitoring.
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              Text: Apr2025
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