Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series Interferometry

Revealing the land subsidence in Beijing, China, induced by the massive groundwater extraction in the past three decades, is important to mitigate the hazards and protect the residences and infrastructure. Many SAR (Synthetic Aperture Radar) datasets have been successfully applied to reveal the land...

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Main Authors: Yakun Han, Tao Li, Keren Dai, Zhong Lu, Xinzhe Yuan, Xianlin Shi, Chen Liu, Ningling Wen, Xi Zhang
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/15/14/3665
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author Yakun Han
Tao Li
Keren Dai
Zhong Lu
Xinzhe Yuan
Xianlin Shi
Chen Liu
Ningling Wen
Xi Zhang
author_facet Yakun Han
Tao Li
Keren Dai
Zhong Lu
Xinzhe Yuan
Xianlin Shi
Chen Liu
Ningling Wen
Xi Zhang
author_sort Yakun Han
collection DOAJ
description Revealing the land subsidence in Beijing, China, induced by the massive groundwater extraction in the past three decades, is important to mitigate the hazards and protect the residences and infrastructure. Many SAR (Synthetic Aperture Radar) datasets have been successfully applied to reveal the land subsidence over Beijing in previous research, while few works were achieved on land subsidence revealed by time-series InSAR (Interferometric Synthetic Aperture Radar) with Gaofen-3 SAR images. In this study, we successfully perform the time-series InSAR analysis with Gaofen-3 SAR images to extract the land subsidence in Beijing from 2020 to 2021. The Sentinel-1 SAR images were used to assess the accuracy of Gaofen-3 images. The subsidence scale and extent are consistent in detected major subsidence bowls between the two datasets. The spatial–temporal evolution and the deceleration of Beijing land subsidence were revealed by comparing with the Sentinel-1 results from 2017 to 2020. Moreover, we evaluated the interferometric performance of Gaofen-3 satellite SAR imagery and analyzed the main factors that mostly influence the coherence and quality of interferograms. Our results proved that the long perpendicular baselines decrease the coherence seriously over the study area, and the artifacts induced by inaccurate orbit information reduce the quality of the Gaofen-3 interferograms. Refining and removing the two main artifacts could improve the quality of interferograms formed by Gaofen-3 SAR images.
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spelling doaj.art-2c1849eb4cfe4a48ba48e38c479f2ad42023-11-18T21:13:59ZengMDPI AGRemote Sensing2072-42922023-07-011514366510.3390/rs15143665Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series InterferometryYakun Han0Tao Li1Keren Dai2Zhong Lu3Xinzhe Yuan4Xianlin Shi5Chen Liu6Ningling Wen7Xi Zhang8College of Earth Science, Chengdu University of Technology, Chengdu 610059, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, ChinaCollege of Earth Science, Chengdu University of Technology, Chengdu 610059, ChinaHuffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275, USANational Satellite Ocean Application Service, Beijing 100081, ChinaCollege of Earth Science, Chengdu University of Technology, Chengdu 610059, ChinaCollege of Earth Science, Chengdu University of Technology, Chengdu 610059, ChinaCollege of Earth Science, Chengdu University of Technology, Chengdu 610059, ChinaCollege of Earth Science, Chengdu University of Technology, Chengdu 610059, ChinaRevealing the land subsidence in Beijing, China, induced by the massive groundwater extraction in the past three decades, is important to mitigate the hazards and protect the residences and infrastructure. Many SAR (Synthetic Aperture Radar) datasets have been successfully applied to reveal the land subsidence over Beijing in previous research, while few works were achieved on land subsidence revealed by time-series InSAR (Interferometric Synthetic Aperture Radar) with Gaofen-3 SAR images. In this study, we successfully perform the time-series InSAR analysis with Gaofen-3 SAR images to extract the land subsidence in Beijing from 2020 to 2021. The Sentinel-1 SAR images were used to assess the accuracy of Gaofen-3 images. The subsidence scale and extent are consistent in detected major subsidence bowls between the two datasets. The spatial–temporal evolution and the deceleration of Beijing land subsidence were revealed by comparing with the Sentinel-1 results from 2017 to 2020. Moreover, we evaluated the interferometric performance of Gaofen-3 satellite SAR imagery and analyzed the main factors that mostly influence the coherence and quality of interferograms. Our results proved that the long perpendicular baselines decrease the coherence seriously over the study area, and the artifacts induced by inaccurate orbit information reduce the quality of the Gaofen-3 interferograms. Refining and removing the two main artifacts could improve the quality of interferograms formed by Gaofen-3 SAR images.https://www.mdpi.com/2072-4292/15/14/3665interferometric performanceGaofen-3InSARsubsidenceBeijing
spellingShingle Yakun Han
Tao Li
Keren Dai
Zhong Lu
Xinzhe Yuan
Xianlin Shi
Chen Liu
Ningling Wen
Xi Zhang
Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series Interferometry
Remote Sensing
interferometric performance
Gaofen-3
InSAR
subsidence
Beijing
title Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series Interferometry
title_full Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series Interferometry
title_fullStr Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series Interferometry
title_full_unstemmed Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series Interferometry
title_short Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series Interferometry
title_sort revealing the land subsidence deceleration in beijing china by gaofen 3 time series interferometry
topic interferometric performance
Gaofen-3
InSAR
subsidence
Beijing
url https://www.mdpi.com/2072-4292/15/14/3665
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