Sequential Estimation of Dynamic Deformation Parameters for SBAS-InSAR

Wang, Baohang; Zhao, Chaoying; Zhang, Qin; Lü, Zhong; Li, Zhenhong; Liu, Yuanyuan

doi:10.1109/lgrs.2019.2938330

Cited by 24 publications

(22 citation statements)

References 13 publications

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“…(2) Therefore, we can take X (1) and Q X (1) as a priori information of the estimated parameter X (2) to calculate the equivalent weight matrix P 2 and update the deformation time series [X (2) Y ] T and its cofactor matrix Q [X (2) ;Y ] as follows [38]:…”

Section: A Updating Multisensor Insar Deformation Time Seriesmentioning

confidence: 99%

“…To avoid obtaining a large-scale inverse matrix, we use matrix inversion theory [38], [53] to solve (3)…”

Section: A Updating Multisensor Insar Deformation Time Seriesmentioning

confidence: 99%

“…Sequential SAR data registration [36], [37] has been proposed for Sentinel-1 TOPSAR images. Sequential least squares (SLS) and complex SLS methods have been used to dynamically update deformation parameters for single SAR sensors, including line-of-sight (LOS) deformation time series [38] and 2-D offset tracking deformation time series [39], without the loss of accuracy as compared with conventional SBAS-InSAR and PO-SBAS (Pixel offset SBAS), respectively.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Long-Term Continuously Updated Deformation Time Series From Multisensor InSAR in Xi'an, China From 2007 to 2021

Wang

Zhao

Zhang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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According to historical records, land subsidence has been occurring in Xi'an, China, since the 1960s, characterized by complex land subsidence patterns. This subsidence has the potential to cause serious societal and economic problems during the process of urbanization. Long-term, large-scale monitoring and dynamic high precision tracking of the evolution of surface deformation associated with geohazards is a prerequisite for effective prevention or advance warning of geological disasters. Synthetic aperture radar interferometry (InSAR), a satellite remote sensing technology, can facilitate such monitoring. Both currently operating and planned SAR satellites would provide extensive amounts of SAR data. In this article, we describe an approach for continuously updating long-term multisensor InSAR deformation time series using robust sequential least squares. It is successfully applied to near-real-time monitoring of the long-term evolution of surface deformation in Xi'an, China, from January 3, 2007 to February 12, 2021, using four SAR satellites: ALOS/PALSAR-1, TerraSAR-X, ALOS/PALSAR-2, and Sentinel-1A. In order to analyze deformation evolution, temporal independent component analysis was used to interpret deformation patterns. We found that land subsidence in Xi'an has slowed and even halted in some areas. However, large areas are uplifting, which presents a potential for geohazards. We conclude that the proposed approach using continuously updated deformation time series from multisensor InSAR can provide nearreal-time deformation measurements, which are necessary for an early warning system.

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Section: A Updating Multisensor Insar Deformation Time Seriesmentioning

confidence: 99%

“…To avoid obtaining a large-scale inverse matrix, we use matrix inversion theory [38], [53] to solve (3)…”

Section: A Updating Multisensor Insar Deformation Time Seriesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Long-Term Continuously Updated Deformation Time Series From Multisensor InSAR in Xi'an, China From 2007 to 2021

Wang

Zhao

Zhang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Therefore, we can update the deformation parameters as quickly as possible, once a new SAR image is presented. For a more detailed discussion of sequential estimation of SBAS-InSAR dynamic deformation parameter methods, readers can refer to [28].…”

Section: Of 17mentioning

confidence: 99%

Sequential InSAR Time Series Deformation Monitoring of Land Subsidence and Rebound in Xi’an, China

et al. 2019

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“…Nonetheless, the retrieval of the deformation signal from time-series InSAR data is limited by several decorrelation factors including atmospheric delay, geometrical, temporal, orbital inaccuracies, and topographic errors [23,24]. To overcome this limitation, the persistent scatterers InSAR (PS-InSAR) [24,25] and small baseline subsets (SBAS) methods [26,27] have been introduced with recent advancements in time-series InSAR analysis such as SqueeSAR [28] and sequential estimator [29,30]. With the large archive of current generation SAR acquisitions such as Sentinel-1 A/B, Cosmo-SkyMed, and TerraSAR-X, multi-temporal InSAR analysis has gained further notice in monitoring the vertical ground motions over large areas [31].…”

Section: Introductionmentioning

confidence: 99%

Monitoring the Vertical Land Motion of Tide Gauges and Its Impact on Relative Sea Level Changes in Korean Peninsula Using Sequential SBAS-InSAR Time-Series Analysis

et al. 2020

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The relative sea-level changes from tide gauges in the Korean peninsula provide essential information to understand the regional and global mean sea-level changes. Several corrections to raw tide gauge records are required to account for coastal vertical land motion (VLM), regional and local coastal variability. However, due to the lack of in-situ measurements such as leveling data and the Global Navigation Satellite System (GNSS), making precise assessments of VLM at the tide gauges is still challenging. This study aims to address the above limitation to assess the VLM in the Korean tide gauges using the time-series Interferometric Synthetic Aperture Radar (InSAR) technique. For 10 tide gauges selected in the Korean peninsula, we applied the Stanford Method for Persistent Scatterers (StaMPS)—Small Baseline Subset (SBAS) method to C-band Sentinel-1 A/B Synthetic Aperture Radar (SAR) data acquired during 2014/10–2020/05, with the novel sequential interferograms pair selection approach to increase the slowly decorrelating filtered phase (SDFP) pixels density near the tide gauges. Our findings show that overall the tide gauges in the Korean peninsula are stable, besides the largest VLM observed at Pohang tide gauge station (East Sea) of about −26.02 mm/year; also, higher rates of uplift (>1 mm/year) were observed along the coast of Yellow Sea (Incheon TG and Boryeong TG) and higher rates of subsidence (<−2 mm/year) were observed at Jeju TG and Seogwipo TG. Our approach estimates the rate of VLM at selected tide gauges with an unprecedented spatial and temporal resolution and is applicable when the in-situ and GNSS observations are not available.

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Sequential Estimation of Dynamic Deformation Parameters for SBAS-InSAR

Cited by 24 publications

References 13 publications

Long-Term Continuously Updated Deformation Time Series From Multisensor InSAR in Xi'an, China From 2007 to 2021

Long-Term Continuously Updated Deformation Time Series From Multisensor InSAR in Xi'an, China From 2007 to 2021

Sequential InSAR Time Series Deformation Monitoring of Land Subsidence and Rebound in Xi’an, China

Monitoring the Vertical Land Motion of Tide Gauges and Its Impact on Relative Sea Level Changes in Korean Peninsula Using Sequential SBAS-InSAR Time-Series Analysis

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