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Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry

Existing studies have shown that satellite synthetic aperture radar (SAR) interferometry has two apparent drawbacks, i.e., temporal decorrelation and atmospheric contamination, in the application of deformation mapping. It is however possible to improve deformation analysis by tracking some natural...

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Detalles Bibliográficos
Autores principales: Liu, Guoxiang, Luo, Xiaojun, Chen, Qiang, Huang, Dingfa, Ding, Xiaoli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3705468/
https://www.ncbi.nlm.nih.gov/pubmed/27873782
http://dx.doi.org/10.3390/s8084725
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author Liu, Guoxiang
Luo, Xiaojun
Chen, Qiang
Huang, Dingfa
Ding, Xiaoli
author_facet Liu, Guoxiang
Luo, Xiaojun
Chen, Qiang
Huang, Dingfa
Ding, Xiaoli
author_sort Liu, Guoxiang
collection PubMed
description Existing studies have shown that satellite synthetic aperture radar (SAR) interferometry has two apparent drawbacks, i.e., temporal decorrelation and atmospheric contamination, in the application of deformation mapping. It is however possible to improve deformation analysis by tracking some natural or man-made objects with steady radar reflectivity, i.e., permanent scatterers (PS), in the frame of time series of SAR images acquired over the same area. For detecting land subsidence in Shanghai, China, this paper presents an attempt to explore an approach of PS-neighborhood networking SAR interferometry. With use of 26 ERS-1/2 SAR images acquired 1992 through 2002 over Shanghai, the analysis of subsiding process in time and space is performed on the basis of a strong network which is formed by connecting neighboring PSs according to a distance threshold. The linear and nonlinear subsidence, atmospheric effects as well as topographic errors can be separated effectively in this way. The subsidence velocity field in 10 years over Shanghai is also derived. It was found that the annual subsidence rates in the study area range from -2.1 to -0.6 cm/yr, and the averaged subsidence rate reaches -1.1 cm/yr.
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spelling pubmed-37054682013-07-09 Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry Liu, Guoxiang Luo, Xiaojun Chen, Qiang Huang, Dingfa Ding, Xiaoli Sensors (Basel) Article Existing studies have shown that satellite synthetic aperture radar (SAR) interferometry has two apparent drawbacks, i.e., temporal decorrelation and atmospheric contamination, in the application of deformation mapping. It is however possible to improve deformation analysis by tracking some natural or man-made objects with steady radar reflectivity, i.e., permanent scatterers (PS), in the frame of time series of SAR images acquired over the same area. For detecting land subsidence in Shanghai, China, this paper presents an attempt to explore an approach of PS-neighborhood networking SAR interferometry. With use of 26 ERS-1/2 SAR images acquired 1992 through 2002 over Shanghai, the analysis of subsiding process in time and space is performed on the basis of a strong network which is formed by connecting neighboring PSs according to a distance threshold. The linear and nonlinear subsidence, atmospheric effects as well as topographic errors can be separated effectively in this way. The subsidence velocity field in 10 years over Shanghai is also derived. It was found that the annual subsidence rates in the study area range from -2.1 to -0.6 cm/yr, and the averaged subsidence rate reaches -1.1 cm/yr. Molecular Diversity Preservation International (MDPI) 2008-08-19 /pmc/articles/PMC3705468/ /pubmed/27873782 http://dx.doi.org/10.3390/s8084725 Text en © 2008 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the CreativeCommons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Liu, Guoxiang
Luo, Xiaojun
Chen, Qiang
Huang, Dingfa
Ding, Xiaoli
Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry
title Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry
title_full Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry
title_fullStr Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry
title_full_unstemmed Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry
title_short Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry
title_sort detecting land subsidence in shanghai by ps-networking sar interferometry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3705468/
https://www.ncbi.nlm.nih.gov/pubmed/27873782
http://dx.doi.org/10.3390/s8084725
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