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Monitoring and analysis of ground subsidence in Shanghai based on PS-InSAR and SBAS-InSAR technologies

Shanghai is susceptible to land subsidence due to its unique geological environment and frequent human activities. Traditional leveling techniques are not sufficient for monitoring large areas of land subsidence due to the time-consuming, labor-intensive, and expensive nature of the process. Further...

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Autores principales: Zhang, Zhihua, Hu, Changtao, Wu, Zhihui, Zhang, Zhen, Yang, Shuwen, Yang, Wang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10192325/
https://www.ncbi.nlm.nih.gov/pubmed/37198287
http://dx.doi.org/10.1038/s41598-023-35152-1
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author Zhang, Zhihua
Hu, Changtao
Wu, Zhihui
Zhang, Zhen
Yang, Shuwen
Yang, Wang
author_facet Zhang, Zhihua
Hu, Changtao
Wu, Zhihui
Zhang, Zhen
Yang, Shuwen
Yang, Wang
author_sort Zhang, Zhihua
collection PubMed
description Shanghai is susceptible to land subsidence due to its unique geological environment and frequent human activities. Traditional leveling techniques are not sufficient for monitoring large areas of land subsidence due to the time-consuming, labor-intensive, and expensive nature of the process. Furthermore, the results of conventional methods may not be timely, rendering them ineffective for monitoring purposes. Interferometric Synthetic Aperture Radar (InSAR) technology is a widely used method for monitoring ground subsidence due to its low cost, high efficiency, and ability to cover large areas. To monitor the surface sink condition of Shanghai over the past 2 years, monitoring data were obtained through the technical processing of 24 images from Sentinel-1A data covering Shanghai from 2019 to 2020 using the Persistent Scatterer (PS-InSAR) and Small Baseline Subset (SBAS-InSAR) technique. The ground subsidence (GS) results were extracted via PS and SBAS interferometry processing, while Shuttle Radar Topography Mission data were used to correct the residual phase. According to PS and SBAS methods, the maximum ground subsidence in the study area reached 99.8 mm and 47.2 mm, respectively. The subsidence rate and the accumulated amount of subsidence derived from the monitoring results revealed the urban area in Shanghai to be principally characterized by uneven GS, with multiple settlement funnels being found to be distributed across the main urban area. Moreover, when compared with the historical subsidence data, geological data, and urban construction distribution data, the individual settlement funnels were observed to correspond to those data concerning the historical surface settlement funnel in Shanghai. By randomly selecting GS time-series data regarding three feature points, it was determined that the morphological variables of the GS remained largely consistent at all time points and that their change trends exhibited a high degree of consistency, which verified the reliability of the PS-InSAR and SBAS-InSAR monitoring method. The results can provide data support for decision making in terms of geological disaster prevention and control in Shanghai.
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spelling pubmed-101923252023-05-19 Monitoring and analysis of ground subsidence in Shanghai based on PS-InSAR and SBAS-InSAR technologies Zhang, Zhihua Hu, Changtao Wu, Zhihui Zhang, Zhen Yang, Shuwen Yang, Wang Sci Rep Article Shanghai is susceptible to land subsidence due to its unique geological environment and frequent human activities. Traditional leveling techniques are not sufficient for monitoring large areas of land subsidence due to the time-consuming, labor-intensive, and expensive nature of the process. Furthermore, the results of conventional methods may not be timely, rendering them ineffective for monitoring purposes. Interferometric Synthetic Aperture Radar (InSAR) technology is a widely used method for monitoring ground subsidence due to its low cost, high efficiency, and ability to cover large areas. To monitor the surface sink condition of Shanghai over the past 2 years, monitoring data were obtained through the technical processing of 24 images from Sentinel-1A data covering Shanghai from 2019 to 2020 using the Persistent Scatterer (PS-InSAR) and Small Baseline Subset (SBAS-InSAR) technique. The ground subsidence (GS) results were extracted via PS and SBAS interferometry processing, while Shuttle Radar Topography Mission data were used to correct the residual phase. According to PS and SBAS methods, the maximum ground subsidence in the study area reached 99.8 mm and 47.2 mm, respectively. The subsidence rate and the accumulated amount of subsidence derived from the monitoring results revealed the urban area in Shanghai to be principally characterized by uneven GS, with multiple settlement funnels being found to be distributed across the main urban area. Moreover, when compared with the historical subsidence data, geological data, and urban construction distribution data, the individual settlement funnels were observed to correspond to those data concerning the historical surface settlement funnel in Shanghai. By randomly selecting GS time-series data regarding three feature points, it was determined that the morphological variables of the GS remained largely consistent at all time points and that their change trends exhibited a high degree of consistency, which verified the reliability of the PS-InSAR and SBAS-InSAR monitoring method. The results can provide data support for decision making in terms of geological disaster prevention and control in Shanghai. Nature Publishing Group UK 2023-05-17 /pmc/articles/PMC10192325/ /pubmed/37198287 http://dx.doi.org/10.1038/s41598-023-35152-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Zhang, Zhihua
Hu, Changtao
Wu, Zhihui
Zhang, Zhen
Yang, Shuwen
Yang, Wang
Monitoring and analysis of ground subsidence in Shanghai based on PS-InSAR and SBAS-InSAR technologies
title Monitoring and analysis of ground subsidence in Shanghai based on PS-InSAR and SBAS-InSAR technologies
title_full Monitoring and analysis of ground subsidence in Shanghai based on PS-InSAR and SBAS-InSAR technologies
title_fullStr Monitoring and analysis of ground subsidence in Shanghai based on PS-InSAR and SBAS-InSAR technologies
title_full_unstemmed Monitoring and analysis of ground subsidence in Shanghai based on PS-InSAR and SBAS-InSAR technologies
title_short Monitoring and analysis of ground subsidence in Shanghai based on PS-InSAR and SBAS-InSAR technologies
title_sort monitoring and analysis of ground subsidence in shanghai based on ps-insar and sbas-insar technologies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10192325/
https://www.ncbi.nlm.nih.gov/pubmed/37198287
http://dx.doi.org/10.1038/s41598-023-35152-1
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