Review of the SBAS InSAR Time-series algorithms, applications, and challenges
In the past 30 years, the small baseline subset (SBAS) InSAR time-series technique has emerged as an essential tool for measuring slow surface displacement and estimating geophysical parameters. Because of its ability to monitor large-scale deformation with millimeter accuracy, the SBAS method has b...
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KeAi Communications Co., Ltd.
2022
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Online Access: | https://doi.org/10.1016/j.geog.2021.09.007 https://doaj.org/article/db1229c264dc41a0a0f2edc2ac977a35 |
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ftdoajarticles:oai:doaj.org/article:db1229c264dc41a0a0f2edc2ac977a35 2023-05-15T17:57:50+02:00 Review of the SBAS InSAR Time-series algorithms, applications, and challenges Shaowei Li Wenbin Xu Zhiwei Li 2022-03-01T00:00:00Z https://doi.org/10.1016/j.geog.2021.09.007 https://doaj.org/article/db1229c264dc41a0a0f2edc2ac977a35 EN eng KeAi Communications Co., Ltd. http://www.sciencedirect.com/science/article/pii/S1674984721000860 https://doaj.org/toc/1674-9847 1674-9847 doi:10.1016/j.geog.2021.09.007 https://doaj.org/article/db1229c264dc41a0a0f2edc2ac977a35 Geodesy and Geodynamics, Vol 13, Iss 2, Pp 114-126 (2022) InSAR Small baseline subset Time-series InSAR Deformation Geodesy QB275-343 Geophysics. Cosmic physics QC801-809 article 2022 ftdoajarticles https://doi.org/10.1016/j.geog.2021.09.007 2022-12-31T07:03:25Z In the past 30 years, the small baseline subset (SBAS) InSAR time-series technique has emerged as an essential tool for measuring slow surface displacement and estimating geophysical parameters. Because of its ability to monitor large-scale deformation with millimeter accuracy, the SBAS method has been widely used in various geodetic fields, such as ground subsidence, landslides, and seismic activity. The obtained long-term time-series cumulative deformation is vital for studying the deformation mechanism. This article reviews the algorithms, applications, and challenges of the SBAS method. First, we recall the fundamental principle and analyze the shortcomings of the traditional SBAS algorithm, which provides a basic framework for the following improved time series methods. Second, we classify the current improved SBAS techniques from different perspectives: solving the ill-posed equation, increasing the density of high-coherence points, improving the accuracy of monitoring deformation and measuring the multi-dimensional deformation. Third, we summarize the application of the SBAS method in monitoring ground subsidence, permafrost degradation, glacier movement, volcanic activity, landslides, and seismic activity. Finally, we discuss the difficulties faced by the SBAS method and explore its future development direction. Article in Journal/Newspaper permafrost Directory of Open Access Journals: DOAJ Articles Geodesy and Geodynamics 13 2 114 126 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
InSAR Small baseline subset Time-series InSAR Deformation Geodesy QB275-343 Geophysics. Cosmic physics QC801-809 |
spellingShingle |
InSAR Small baseline subset Time-series InSAR Deformation Geodesy QB275-343 Geophysics. Cosmic physics QC801-809 Shaowei Li Wenbin Xu Zhiwei Li Review of the SBAS InSAR Time-series algorithms, applications, and challenges |
topic_facet |
InSAR Small baseline subset Time-series InSAR Deformation Geodesy QB275-343 Geophysics. Cosmic physics QC801-809 |
description |
In the past 30 years, the small baseline subset (SBAS) InSAR time-series technique has emerged as an essential tool for measuring slow surface displacement and estimating geophysical parameters. Because of its ability to monitor large-scale deformation with millimeter accuracy, the SBAS method has been widely used in various geodetic fields, such as ground subsidence, landslides, and seismic activity. The obtained long-term time-series cumulative deformation is vital for studying the deformation mechanism. This article reviews the algorithms, applications, and challenges of the SBAS method. First, we recall the fundamental principle and analyze the shortcomings of the traditional SBAS algorithm, which provides a basic framework for the following improved time series methods. Second, we classify the current improved SBAS techniques from different perspectives: solving the ill-posed equation, increasing the density of high-coherence points, improving the accuracy of monitoring deformation and measuring the multi-dimensional deformation. Third, we summarize the application of the SBAS method in monitoring ground subsidence, permafrost degradation, glacier movement, volcanic activity, landslides, and seismic activity. Finally, we discuss the difficulties faced by the SBAS method and explore its future development direction. |
format |
Article in Journal/Newspaper |
author |
Shaowei Li Wenbin Xu Zhiwei Li |
author_facet |
Shaowei Li Wenbin Xu Zhiwei Li |
author_sort |
Shaowei Li |
title |
Review of the SBAS InSAR Time-series algorithms, applications, and challenges |
title_short |
Review of the SBAS InSAR Time-series algorithms, applications, and challenges |
title_full |
Review of the SBAS InSAR Time-series algorithms, applications, and challenges |
title_fullStr |
Review of the SBAS InSAR Time-series algorithms, applications, and challenges |
title_full_unstemmed |
Review of the SBAS InSAR Time-series algorithms, applications, and challenges |
title_sort |
review of the sbas insar time-series algorithms, applications, and challenges |
publisher |
KeAi Communications Co., Ltd. |
publishDate |
2022 |
url |
https://doi.org/10.1016/j.geog.2021.09.007 https://doaj.org/article/db1229c264dc41a0a0f2edc2ac977a35 |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
Geodesy and Geodynamics, Vol 13, Iss 2, Pp 114-126 (2022) |
op_relation |
http://www.sciencedirect.com/science/article/pii/S1674984721000860 https://doaj.org/toc/1674-9847 1674-9847 doi:10.1016/j.geog.2021.09.007 https://doaj.org/article/db1229c264dc41a0a0f2edc2ac977a35 |
op_doi |
https://doi.org/10.1016/j.geog.2021.09.007 |
container_title |
Geodesy and Geodynamics |
container_volume |
13 |
container_issue |
2 |
container_start_page |
114 |
op_container_end_page |
126 |
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1766166339017244672 |