Land subsidence and ground fissures in Xi'an, China 2005–2012 revealed by multi-band InSAR time-series analysis

Qu, Feifei; Zhang, Qin; Lü, Zhong; Zhao, Chaoying; Yang, Chengsheng; Zhang, Jing

doi:10.1016/j.rse.2014.09.008

Cited by 151 publications

(73 citation statements)

References 40 publications

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“…Satellites (e.g., InSAR, DInSAR, and TimeSAR) (Chaussard et al, 2014;Herrera et al, 2007;Grzovic and Ghulam, 2015;Perski et al, 2009;Qu et al, 2014;Zhang et al, 2015) and aerial imagery (LiDAR) (Ao et …”

Section: Mining Operationsmentioning

confidence: 99%

Influence of model parameter uncerainties on forecasted subsidence

Gruszczyński¹

2018

Acta Geodynamica Et Geomaterialia

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Surface deformation due to underground exploitation affects the safety of overlying structures. Forecasting can predict risks to surface structures and facilitates actions designed to improve their resilience and reduce the potential impact of mining activities. However, forecasting accuracy is limited. Therefore, in practice, model parameters are determined within a certain margin to ensure that critical values of deformation indicators for surface objects are not exceeded. For economic reasons, it is important to minimize these margins while also ensuring that safety is maintained. One important factor influencing forecasting accuracy is the uncertainty in deformation model parameters used for calculations. Therefore, it is critical to adopt an appropriate methodology for determining and addressing the uncertainties in deformation model parameters used in forecasting. This study presents methods for estimating the Knothe's model parameters needed to forecast surface deformation caused by underground mining and defining the uncertainties in those forecasts. Depending on the parameter uncertainties, one of two methods for propagation is proposed: the Monte Carlo method or the law of propagation of uncertainty. Using this approach, it is possible to account for uncertainty and reduce forecast margins. A case study of hard coal mining in the Upper Silesian Coal Basin region of Poland is presented. ARTICLE INFO

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Section: Mining Operationsmentioning

confidence: 99%

Influence of model parameter uncerainties on forecasted subsidence

Gruszczyński¹

2018

Acta Geodynamica Et Geomaterialia

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“…A series of normal faults have been developed around this city, among which the Lintong-Chang'an fault is the most active one (Peng et al, 2016). Along with the economic development and urban extension, severe land subsidence and ground fissures have occurred in Xi'an since 1960s Zhao et al, 2008;Qu et al, 2014). The maximum cumulative land subsidence has reached approximately 3 m, and 14 ground fissures have emerged throughout the city in an east-north-east (ENE) direction, which have caused severe damages to the infrastructures, such as buildings, municipal pipelines, roads, bridges and metro railway.…”

Section: Introductionmentioning

confidence: 99%

“…Since the beginning of 1990s, Interferometric SAR (InSAR) has become a powerful tool for measuring surface deformation induced by various hazards (Massonnet et al, 1993;Lu & Dzurisin, 2014;Qu et al, 2014;Kang et al, 2017). To overcome the limitations of conventional InSAR including decorrelation and atmospheric artifacts, advanced multiinterferogram InSAR (MT-InSAR) techniques such as Persistent Scatterers InSAR (PSInSAR) and Small Baseline Subset (SBAS) InSAR have been developed to map timeseries land surface displacements (Ferretti et al, 2001;Berardino et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

“…Zhao et al (2008Zhao et al ( , 2009) studied the evolution of land subsidence during 1992-2007 by using 15 ERS-1/2 and Envisat data, and analyzed the land subsidence during 2005-2006 by using 7 Envisat images. Qu et al (2014) studied the spatiotemporal evolution of land subsidence and ground fissures during 2005-2012 with multiple SAR datasets as well as leveling, GPS and groundwater data. With the urban extension, land subsidence and ground fissure develop continuously over Xi'an.…”

Section: Introductionmentioning

confidence: 99%

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GROUND SUBSIDENCE MONITORING WITH MT-InSAR AND MECHANISM INVERSION OVER XI’AN, CHINA

Peng¹,

Zhao²,

Zhang³

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The ancient Xi'an, China, has been suffering severe land subsidence and ground fissure hazards since the 1960s, which has affected the safety of Subways. Multi-sensor SAR data are conducted to monitor the latest complex ground deformation and its influence on subway line No.3 over Xi'an. Annual deformation rates have been retrieved to reveal the spatiotemporal evolution of ground subsidence in Xi'an city from 2013 to 2017. Meanwhile, the correlation between land subsidence and ground fissures are analyzed by retrieving the deformation differences in both sides of the fissures. Besides, the deformation along subway line No. 3 is analyzed, and the fast deformation section is quantitatively studied. Finally, a flat lying sill model with distributed contractions is implemented to model the InSAR deformation over YHZ subsidence center, which manifests that the ground deformation is mainly caused by groundwater withdrawal.

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“…These methods are time-consuming, labor-intensive, costly, and limited in spatial coverage and precision. With the rapid progress in Earth observation techniques in recent years, different interferometric synthetic aperture radar (D-InSAR) and time-series InSAR methods such as PS-InSAR [5][6][7][8], SBAS-InSAR [9][10][11][12][13][14][15][16], TCP-InSAR [17][18][19][20], and ITPA-InSAR [21,22] have been proven to be effective methods with an accuracy of millimeters to centimeters for mapping ground deformation induced by various natural and anthropogenic causes. However, those methods are based on phase unwrapping and have significant limitations based on deformation gradient.…”

Section: Introductionmentioning

confidence: 99%

An Improved Adaptive Template Size Pixel-Tracking Method for Monitoring Large-Gradient Mining Subsidence

et al. 2017

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The monitoring of large-gradient deformation caused by coal mining is of great significance to the prevention and management of disasters in mining areas. The interferometric synthetic aperture radar (InSAR) method captures the small-gradient ground deformation on the edge of the subsidence basin accurately but is unreliable for capturing large-gradient deformation. The intensitybased pixel-tracking method (e.g., the normalized cross-correlation (NCC) method) can overcome the limitations of InSAR's maximum detectable displacement gradient and incoherence. However, the pixel-tracking method is sensitive to template size. It is difficult to estimate ground subsidence accurately by the conventional pixel-tracking method with fixed template size. In this paper, the signal-to-noise ratio (SNR) is redefined and an improved locally adaptive template size method is proposed by identifying optimal template adaptively based on maximization of the redefined SNR. The constraint radius is used to constrain the search area in this improved method. The frequency of misrepresentation is reduced by finding the peak of the correlation coefficient surface within the search area. Both simulation data and real ground subsidence data are used to test this algorithm. The results show that this method can improve monitoring accuracy compared with the traditional pixel-tracking method for fixed template size.

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Land subsidence and ground fissures in Xi'an, China 2005–2012 revealed by multi-band InSAR time-series analysis

Cited by 151 publications

References 40 publications

Influence of model parameter uncerainties on forecasted subsidence

Influence of model parameter uncerainties on forecasted subsidence

GROUND SUBSIDENCE MONITORING WITH MT-InSAR AND MECHANISM INVERSION OVER XI’AN, CHINA

An Improved Adaptive Template Size Pixel-Tracking Method for Monitoring Large-Gradient Mining Subsidence

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