Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground Deformation
A stack of images is a prerequisite for the multi-temporal interferometric synthetic aperture radar (MT-InSAR) due to the wrapped nature of the interferometric phase. Although the SBAS technique can relieve the requirement of the amount of SAR data, dozens of SAR acquisitions could be regarded as th...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-07-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2022.929958/full |
| _version_ | 1811292236555485184 |
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| author | Chuanguang Zhu Sichun Long Jixian Zhang Wenhao Wu Liya Zhang |
| author_facet | Chuanguang Zhu Sichun Long Jixian Zhang Wenhao Wu Liya Zhang |
| author_sort | Chuanguang Zhu |
| collection | DOAJ |
| description | A stack of images is a prerequisite for the multi-temporal interferometric synthetic aperture radar (MT-InSAR) due to the wrapped nature of the interferometric phase. Although the SBAS technique can relieve the requirement of the amount of SAR data, dozens of SAR acquisitions could be regarded as the minimum requirement. However, due to the limitation of the imaging capability of the spaceborne SAR system, the amount of available SAR data acquired from only one SAR sensor is often not enough to satisfy the requirement for phase unwrapping based on the Nyquist sampling assumption. Fortunately, there sometimes may be more than one SAR stack, that is, stacks of SAR data acquired from different SAR systems. In this study, we propose a methodology to detect ground deformation by combining multiple SAR images acquired from different satellite systems for MT-InSAR analysis. First, the low-pass deformation is estimated based on time series SAR acquisitions with low spatial resolution and long wavelengths such as ENVISAT ASAR (ASAR). This information is then incorporated into the processing of time series of SAR acquisitions with high spatial resolution and short wavelength, such as TerraSAR-X (TSX). Specifically, the low-pass deformation will be subtracted from each differential interferogram generated from short-wavelength SAR images, and the rest of the MT-InSAR analysis will be based on the double-differentiation interferograms. Then, the residual deformation will be calculated from these double-differentiation interferograms and together with the low-pass deformation forms the full deformation. As the principal component of deformation has already been subtracted, the phase gradient of those double-differentiated interferograms will be smooth enough to facilitate the phase unwrapping. Between January 2009 and September 2010, 14 ASAR images and 11 TSX images acquired from Tianjin, China are selected as the test data. A root means square error (RMSE) of 9.1 mm/year is achieved from 11 TSX images, while a root means square error of 3.7 mm/year is achieved from 14 ASAR images. However, an RMSE of 1.6 mm/year is achieved when integrating 11 TSX images and 14 ASAR images for MT-InSAR analysis. The experiments show that the proposed method can effectively detect ground deformation. |
| first_indexed | 2024-04-13T04:42:23Z |
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| id | doaj.art-757503224404406dbb5cb5994aa9c136 |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-04-13T04:42:23Z |
| publishDate | 2022-07-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Environmental Science |
| spelling | doaj.art-757503224404406dbb5cb5994aa9c1362022-12-22T03:01:57ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2022-07-011010.3389/fenvs.2022.929958929958Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground DeformationChuanguang Zhu0Sichun Long1Jixian Zhang2Wenhao Wu3Liya Zhang4School of Earth Sciences and Geospatial Information Engineering, Hunan University of Science and Technology, Xiangtan, ChinaSchool of Earth Sciences and Geospatial Information Engineering, Hunan University of Science and Technology, Xiangtan, ChinaNational Quality Inspection and Testing Center for Surveying and Mapping Products, Ministry of Natural Resources of the People’s Republic of China, Beijing, ChinaSchool of Earth Sciences and Geospatial Information Engineering, Hunan University of Science and Technology, Xiangtan, ChinaSchool of Earth Sciences and Geospatial Information Engineering, Hunan University of Science and Technology, Xiangtan, ChinaA stack of images is a prerequisite for the multi-temporal interferometric synthetic aperture radar (MT-InSAR) due to the wrapped nature of the interferometric phase. Although the SBAS technique can relieve the requirement of the amount of SAR data, dozens of SAR acquisitions could be regarded as the minimum requirement. However, due to the limitation of the imaging capability of the spaceborne SAR system, the amount of available SAR data acquired from only one SAR sensor is often not enough to satisfy the requirement for phase unwrapping based on the Nyquist sampling assumption. Fortunately, there sometimes may be more than one SAR stack, that is, stacks of SAR data acquired from different SAR systems. In this study, we propose a methodology to detect ground deformation by combining multiple SAR images acquired from different satellite systems for MT-InSAR analysis. First, the low-pass deformation is estimated based on time series SAR acquisitions with low spatial resolution and long wavelengths such as ENVISAT ASAR (ASAR). This information is then incorporated into the processing of time series of SAR acquisitions with high spatial resolution and short wavelength, such as TerraSAR-X (TSX). Specifically, the low-pass deformation will be subtracted from each differential interferogram generated from short-wavelength SAR images, and the rest of the MT-InSAR analysis will be based on the double-differentiation interferograms. Then, the residual deformation will be calculated from these double-differentiation interferograms and together with the low-pass deformation forms the full deformation. As the principal component of deformation has already been subtracted, the phase gradient of those double-differentiated interferograms will be smooth enough to facilitate the phase unwrapping. Between January 2009 and September 2010, 14 ASAR images and 11 TSX images acquired from Tianjin, China are selected as the test data. A root means square error (RMSE) of 9.1 mm/year is achieved from 11 TSX images, while a root means square error of 3.7 mm/year is achieved from 14 ASAR images. However, an RMSE of 1.6 mm/year is achieved when integrating 11 TSX images and 14 ASAR images for MT-InSAR analysis. The experiments show that the proposed method can effectively detect ground deformation.https://www.frontiersin.org/articles/10.3389/fenvs.2022.929958/fullmultitemporal interferometric synthetic aperture radarground deformationNyquist samplingmultiple satellite systemsspaceborne SAR |
| spellingShingle | Chuanguang Zhu Sichun Long Jixian Zhang Wenhao Wu Liya Zhang Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground Deformation Frontiers in Environmental Science multitemporal interferometric synthetic aperture radar ground deformation Nyquist sampling multiple satellite systems spaceborne SAR |
| title | Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground Deformation |
| title_full | Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground Deformation |
| title_fullStr | Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground Deformation |
| title_full_unstemmed | Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground Deformation |
| title_short | Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground Deformation |
| title_sort | time series multi sensors of interferometry synthetic aperture radar for monitoring ground deformation |
| topic | multitemporal interferometric synthetic aperture radar ground deformation Nyquist sampling multiple satellite systems spaceborne SAR |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2022.929958/full |
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