Time-series InSAR deformation gradient estimation and urban buildings risk assessment: A case study in the Beijing Plain

Objective Differential deformation of urban land surfaces can threaten or damage surface infrastructure, leading to fractures and distortions. Monitoring spatial differential deformation and assessing associated risk levels are crucial for urban safety management. Methods This study employs Sentinel...

Full description

Saved in:
Bibliographic Details
Main Authors: Shicheng ZUO, Jie DONG, Mingsheng LIAO
Format: Article
Language:zho
Published: Editorial Department of Bulletin of Geological Science and Technology 2024-11-01
Series:地质科技通报
Subjects:
Online Access:https://dzkjqb.cug.edu.cn/en/article/doi/10.19509/j.cnki.dzkq.tb20240117
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850116734548180992
author Shicheng ZUO
Jie DONG
Mingsheng LIAO
author_facet Shicheng ZUO
Jie DONG
Mingsheng LIAO
author_sort Shicheng ZUO
collection DOAJ
description Objective Differential deformation of urban land surfaces can threaten or damage surface infrastructure, leading to fractures and distortions. Monitoring spatial differential deformation and assessing associated risk levels are crucial for urban safety management. Methods This study employs Sentinel-1 satellite data and the time series InSAR techniques to analyze surface deformation over time, enabling the derivation of spatial-temporal deformation gradients. Hazard and vulnerability assessment factors are calculated using an analytic hierarchy process, integrating data such as nighttime light remote sensing, land use, and Chinese building height datasets.A macroscopic risk assessment is conducted, with supplementary microscopic-levelanalysis to assess building risks and identify potential high-risk areas. Comparison experiments verify the effectiveness of the research. Conclusion Significant deformation disparities are identified between the eastern Chaoyang District and the northwestern Tongzhou District. In addition, high-risk areas are observed around the Capital International Airport region and the vicinity of Anding South Street. Therefore, the study highlights the importance of multisource data for effectively monitoring differential deformation to ensureurban safe.
format Article
id doaj-art-e52f1147ae52468b8c56090c0adf50fc
institution OA Journals
issn 2096-8523
language zho
publishDate 2024-11-01
publisher Editorial Department of Bulletin of Geological Science and Technology
record_format Article
series 地质科技通报
spelling doaj-art-e52f1147ae52468b8c56090c0adf50fc2025-08-20T02:36:15ZzhoEditorial Department of Bulletin of Geological Science and Technology地质科技通报2096-85232024-11-0143617118310.19509/j.cnki.dzkq.tb20240117dzkjtb-43-6-171Time-series InSAR deformation gradient estimation and urban buildings risk assessment: A case study in the Beijing PlainShicheng ZUO0Jie DONG1Mingsheng LIAO2State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaObjective Differential deformation of urban land surfaces can threaten or damage surface infrastructure, leading to fractures and distortions. Monitoring spatial differential deformation and assessing associated risk levels are crucial for urban safety management. Methods This study employs Sentinel-1 satellite data and the time series InSAR techniques to analyze surface deformation over time, enabling the derivation of spatial-temporal deformation gradients. Hazard and vulnerability assessment factors are calculated using an analytic hierarchy process, integrating data such as nighttime light remote sensing, land use, and Chinese building height datasets.A macroscopic risk assessment is conducted, with supplementary microscopic-levelanalysis to assess building risks and identify potential high-risk areas. Comparison experiments verify the effectiveness of the research. Conclusion Significant deformation disparities are identified between the eastern Chaoyang District and the northwestern Tongzhou District. In addition, high-risk areas are observed around the Capital International Airport region and the vicinity of Anding South Street. Therefore, the study highlights the importance of multisource data for effectively monitoring differential deformation to ensureurban safe.https://dzkjqb.cug.edu.cn/en/article/doi/10.19509/j.cnki.dzkq.tb20240117time-series insarbeijing plainspatial deformation gradientnight-time light remote sensingrisk assessmenturban building
spellingShingle Shicheng ZUO
Jie DONG
Mingsheng LIAO
Time-series InSAR deformation gradient estimation and urban buildings risk assessment: A case study in the Beijing Plain
地质科技通报
time-series insar
beijing plain
spatial deformation gradient
night-time light remote sensing
risk assessment
urban building
title Time-series InSAR deformation gradient estimation and urban buildings risk assessment: A case study in the Beijing Plain
title_full Time-series InSAR deformation gradient estimation and urban buildings risk assessment: A case study in the Beijing Plain
title_fullStr Time-series InSAR deformation gradient estimation and urban buildings risk assessment: A case study in the Beijing Plain
title_full_unstemmed Time-series InSAR deformation gradient estimation and urban buildings risk assessment: A case study in the Beijing Plain
title_short Time-series InSAR deformation gradient estimation and urban buildings risk assessment: A case study in the Beijing Plain
title_sort time series insar deformation gradient estimation and urban buildings risk assessment a case study in the beijing plain
topic time-series insar
beijing plain
spatial deformation gradient
night-time light remote sensing
risk assessment
urban building
url https://dzkjqb.cug.edu.cn/en/article/doi/10.19509/j.cnki.dzkq.tb20240117
work_keys_str_mv AT shichengzuo timeseriesinsardeformationgradientestimationandurbanbuildingsriskassessmentacasestudyinthebeijingplain
AT jiedong timeseriesinsardeformationgradientestimationandurbanbuildingsriskassessmentacasestudyinthebeijingplain
AT mingshengliao timeseriesinsardeformationgradientestimationandurbanbuildingsriskassessmentacasestudyinthebeijingplain