Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1
Sentinel-1 data has been widely employed for monitoring large-scale ground deformation with multi-temporal InSAR (MTI). The development of polarimetric MTI (PolMTI) methods has made it possible to combine both VV and VH channels for better ground deformation monitoring with Sentinel-1 data. However,...
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Taylor & Francis Group
2025-12-01
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| Series: | International Journal of Digital Earth |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2024.2447335 |
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| author | Leixin Zhang Feng Zhao Yunjia Wang Jordi J. Mallorqui Teng Wang Yuxuan Zhang Zhongbo Hu Sen Du José Fernández |
| author_facet | Leixin Zhang Feng Zhao Yunjia Wang Jordi J. Mallorqui Teng Wang Yuxuan Zhang Zhongbo Hu Sen Du José Fernández |
| author_sort | Leixin Zhang |
| collection | DOAJ |
| description | Sentinel-1 data has been widely employed for monitoring large-scale ground deformation with multi-temporal InSAR (MTI). The development of polarimetric MTI (PolMTI) methods has made it possible to combine both VV and VH channels for better ground deformation monitoring with Sentinel-1 data. However, traditional high-efficiency PolMTI methods cannot adaptively optimize both persistent scatterer (PS) and distributed scatterer (DS), while existing adaptive methods have high computational burdens. To address these challenges, we propose an adaptive coherency matrix decomposition method for PolMTI (ADCMD-PolMTI), a novel algorithm that adaptively and effectively optimizes phase of both PS and DS pixels. Applied to Southern California, ADCMD-PolMTI markedly improves interferometric phase quality and achieves a 494% increase in high-quality pixel density compared to the single-polarimetric VV method. Additionally, it demonstrates enhanced ground deformation monitoring accuracy, as evidenced by a lower average RMSE compared to the VV and minimum mean square error (MMSE) methods when comparing against GPS data. While achieving a nearly equivalent number of monitoring pixels as the optimal exhaustive search polarimetric optimization (ESPO) algorithm, ADCMD-PolMTI operates 235 and 13 times faster for PSs and DSs, respectively. With its good adaptive optimization capabilities and computational efficiency, ADCMD-PolMTI offers an advanced solution for large-scale ground deformation monitoring. |
| format | Article |
| id | doaj-art-b724389ad1e3426fbd6b55237b15a5c4 |
| institution | Kabale University |
| issn | 1753-8947 1753-8955 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj-art-b724389ad1e3426fbd6b55237b15a5c42025-01-07T02:38:41ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-12-0118110.1080/17538947.2024.2447335Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1Leixin Zhang0Feng Zhao1Yunjia Wang2Jordi J. Mallorqui3Teng Wang4Yuxuan Zhang5Zhongbo Hu6Sen Du7José Fernández8Key Laboratory of Land Environment and Disaster Monitoring, MNR, China University of Mining and Technology (CUMT), Xuzhou, People’s Republic of ChinaKey Laboratory of Land Environment and Disaster Monitoring, MNR, China University of Mining and Technology (CUMT), Xuzhou, People’s Republic of ChinaKey Laboratory of Land Environment and Disaster Monitoring, MNR, China University of Mining and Technology (CUMT), Xuzhou, People’s Republic of ChinaCommSensLab, Universitat Politècnica de Catalunya Barcelona, SpainKey Laboratory of Land Environment and Disaster Monitoring, MNR, China University of Mining and Technology (CUMT), Xuzhou, People’s Republic of ChinaKey Laboratory of Land Environment and Disaster Monitoring, MNR, China University of Mining and Technology (CUMT), Xuzhou, People’s Republic of ChinaInstituto de Geociencias (IGEO), CSIC-UCM, 7 Madrid, SpainInstituto de Geociencias (IGEO), CSIC-UCM, 7 Madrid, SpainInstituto de Geociencias (IGEO), CSIC-UCM, 7 Madrid, SpainSentinel-1 data has been widely employed for monitoring large-scale ground deformation with multi-temporal InSAR (MTI). The development of polarimetric MTI (PolMTI) methods has made it possible to combine both VV and VH channels for better ground deformation monitoring with Sentinel-1 data. However, traditional high-efficiency PolMTI methods cannot adaptively optimize both persistent scatterer (PS) and distributed scatterer (DS), while existing adaptive methods have high computational burdens. To address these challenges, we propose an adaptive coherency matrix decomposition method for PolMTI (ADCMD-PolMTI), a novel algorithm that adaptively and effectively optimizes phase of both PS and DS pixels. Applied to Southern California, ADCMD-PolMTI markedly improves interferometric phase quality and achieves a 494% increase in high-quality pixel density compared to the single-polarimetric VV method. Additionally, it demonstrates enhanced ground deformation monitoring accuracy, as evidenced by a lower average RMSE compared to the VV and minimum mean square error (MMSE) methods when comparing against GPS data. While achieving a nearly equivalent number of monitoring pixels as the optimal exhaustive search polarimetric optimization (ESPO) algorithm, ADCMD-PolMTI operates 235 and 13 times faster for PSs and DSs, respectively. With its good adaptive optimization capabilities and computational efficiency, ADCMD-PolMTI offers an advanced solution for large-scale ground deformation monitoring.https://www.tandfonline.com/doi/10.1080/17538947.2024.2447335Ground deformation monitoringInSARmulti-temporal InSARpolarimetric optimizationsentinel-1 |
| spellingShingle | Leixin Zhang Feng Zhao Yunjia Wang Jordi J. Mallorqui Teng Wang Yuxuan Zhang Zhongbo Hu Sen Du José Fernández Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1 International Journal of Digital Earth Ground deformation monitoring InSAR multi-temporal InSAR polarimetric optimization sentinel-1 |
| title | Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1 |
| title_full | Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1 |
| title_fullStr | Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1 |
| title_full_unstemmed | Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1 |
| title_short | Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1 |
| title_sort | adaptive polarimetric optimization for ground deformation monitoring using multi temporal insar with dual polarization sentinel 1 |
| topic | Ground deformation monitoring InSAR multi-temporal InSAR polarimetric optimization sentinel-1 |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2024.2447335 |
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