Application of the method for prediction of the failure location and time based on monitoring of a slope using synthetic aperture radar

AbstractSynthetic aperture radar (SAR) technology has been widely used in landslide deformation monitoring in the past decade. It has the advantages of high monitoring accuracy, a wide range, and flexibility allowing all-weather continuous monitoring. The self-developed S-SAR synthetic aperture radar (slope radar) is the first completely domestic-made radar used in slope deformation monitoring equipment in China, and its performance and technical parameters are equal to or better than similar products made abroad. The characteristics of deformation data collected by S-SAR slope radar deployed in the front open pit mine are analyzed to further develop a spatio-temporal landslide prediction method which is applicable to the massive monitoring data within the monitoring range of slope radar. The intersection points of short-term moving average velocity curve and long-term moving average velocity curve of slope deformation, which are onset of acceleration (OOA) and termination of acceleration (TOA). When OOA occurs, the deformation will accelerate, and when TOA occurs, the deformation will tend to stabilize. The OOA can identify areas at risk in the monitored area before failure, so that the spatial position prediction of landslide early warning can be realized. Based on the assumptions of the inverse velocity method, a T-log (t) logarithmic model is established, and the updated monitoring data are corrected to approximate the time of failure, thus improving the accuracy of landslide location and time prediction. In an open-pit copper mine in Serbia, the accurate prediction of landslide location and time has been successfully applied, guaranteeing safe mining.

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Deformation information extraction method based on differential synthetic aperture radar interferometry

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189016 ◽

2020 ◽

Vol 39 (4) ◽

pp. 5311-5318

Author(s):

Zhengquan Hu ◽

Yu Liu ◽

Xiaowei Niu ◽

Guoping Lei

Keyword(s):

Remote Sensing ◽

Synthetic Aperture Radar ◽

Adaptive Filtering ◽

Extraction Method ◽

Deformation Monitoring ◽

Radar Interferometry ◽

Synthetic Aperture ◽

Filtering Method ◽

Synthetic Aperture Radar Interferometry ◽

Aperture Radar

As aerospace technology, computer technology, network communication technology and information technology become more and more perfect, a variety of sensors for measurement and remote sensing are constantly emerging, and the ability to acquire remote sensing data is also continuously enhanced. Synthetic Aperture Radar Interferometry (InSAR) technology greatly expands the function and application field of imaging radar. Differential InSAR (DInSAR) developed based on InSAR technology has the advantages of high precision and all-weather compared with traditional measurement methods. However, DInSAR-based deformation monitoring is susceptible to spatiotemporal coherence, orbital errors, atmospheric delays, and elevation errors. Since phase noise is the main error of InSAR, to determine the appropriate filtering parameters, an iterative adaptive filtering method for interferogram is proposed. For the limitation of conventional DInSAR, to improve the accuracy of deformation monitoring as much as possible, this paper proposes a deformation modeling based on ridge estimation and regularization as a constraint condition, and introduces a variance component estimation to optimize the deformation results. The simulation experiment of the iterative adaptive filtering method and the deformation modeling proposed in this paper shows that the deformation information extraction method based on differential synthetic aperture radar has high precision and feasibility.

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Ground based synthetic aperture radar for land deformation monitoring: Preliminary result

2016 Progress in Electromagnetic Research Symposium (PIERS) ◽

10.1109/piers.2016.7735040 ◽

2016 ◽

Author(s):

Yee-Kit Chan ◽

Chih-Yuen Chu

Keyword(s):

Synthetic Aperture Radar ◽

Deformation Monitoring ◽

Synthetic Aperture ◽

Land Deformation ◽

Aperture Radar

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EVALUATION OF DATA APPLICABILITY FOR D-INSAR IN AREAS COVERED BY ABUNDANT VEGETATION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-2277-2018 ◽

2018 ◽

Vol XLII-3 ◽

pp. 2277-2281

Author(s):

P. Zhang ◽

Z. Zhao

Keyword(s):

Synthetic Aperture Radar ◽

Surface Deformation ◽

Deformation Monitoring ◽

Guizhou Province ◽

Synthetic Aperture ◽

Economic Losses ◽

Large Area ◽

Disaster Assessment ◽

Evaluation Of Data ◽

Aperture Radar

In the past few years, the frequent geological disasters have caused enormous casualties and economic losses. Therefore, D-InSAR (differential interferometry synthetic aperture radar) has been widely used in early-warning and post disaster assessment. However, large area of decorrelation often occurs in the areas covered with abundant vegetation, which seriously affects the accuracy of surface deformation monitoring. In this paper, we analysed the effect of sensor parameters and external environment parameters on special decorrelation. Then Synthetic Aperture Radar (SAR) datasets acquired by X-band TerraSAR-X, Phased Array type L-band Synthetic Aperture Satellite-2 (ALOS-2), and C-band Sentinel-1 in Guizhou province were collected and analysed to generate the maps of coherence, which were used to evaluating the applicability of datasets of different wavelengths for D-InSAR in forest area. Finally, we found that datasets acquired by ALOS-2 had the best monitoring effect.

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A SHORT REVIEW ON PERSISTENT SCATTERER INTERFEROMETRY TECHNIQUES FOR SURFACE DEFORMATION MONITORING

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlvi-4-w3-2021-23-2022 ◽

2022 ◽

Vol XLVI-4/W3-2021 ◽

pp. 23-31

Author(s):

A. M. H. Ansar ◽

A. H. M. Din ◽

A. S. A. Latip ◽

M. N. M. Reba

Keyword(s):

Synthetic Aperture Radar ◽

Surface Deformation ◽

Deformation Monitoring ◽

Synthetic Aperture ◽

Structural Development ◽

Interferometric Synthetic Aperture Radar ◽

Persistent Scatterer Interferometry ◽

Persistent Scatterers ◽

Persistent Scatterer ◽

Aperture Radar

Abstract. Technology advancement has urged the development of Interferometric Synthetic Aperture Radar (InSAR) to be upgraded and transformed. The main contribution of the InSAR technique is that the surface deformation changes measurements can achieve up to millimetre level precision. Environmental problems such as landslides, volcanoes, earthquakes, excessive underground water production, and other phenomena can cause the earth's surface deformation. Deformation monitoring of a surface is vital as unexpected movement, and future behaviour can be detected and predicted. InSAR time series analysis, known as Persistent Scatterer Interferometry (PSI), has become an essential tool for measuring surface deformation. Therefore, this study provides a review of the PSI techniques used to measure surface deformation changes. An overview of surface deformation and the basic principles of the four techniques that have been developed from the improvement of Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), which is Small Baseline Subset (SBAS), Stanford Method for Persistent Scatterers (StaMPS), SqueeSAR and Quasi Persistent Scatterer (QPS) were summarised to perceive the ability of these techniques in monitoring surface deformation. This study also emphasises the effectiveness and restrictions of each developed technique and how they suit Malaysia conditions and environment. The future outlook for Malaysia in realising the PSI techniques for structural monitoring also discussed in this review. Finally, this review will lead to the implementation of appropriate techniques and better preparation for the country's structural development.

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Landslide Deformation Monitoring by Adaptive Distributed Scatterer Interferometric Synthetic Aperture Radar

Remote Sensing ◽

10.3390/rs11192273 ◽

2019 ◽

Vol 11 (19) ◽

pp. 2273 ◽

Cited By ~ 2

Author(s):

Hongguo Jia ◽

Hao Zhang ◽

Luyao Liu ◽

Guoxiang Liu

Keyword(s):

Time Series ◽

Synthetic Aperture Radar ◽

Deformation Monitoring ◽

Synthetic Aperture ◽

Economic Losses ◽

Interferometric Synthetic Aperture Radar ◽

Mountainous Areas ◽

Landslide Area ◽

Landslide Deformation ◽

Aperture Radar

Landslide is the second most frequent geological disaster after earthquake, which causes a large number of casualties and economic losses every year. China frequently experiences devastating landslides in mountainous areas. Interferometric Synthetic Aperture Radar (InSAR) technology has great potential for detecting potentially unstable landslides across wide areas and can monitor surface displacement of a single landslide. However traditional time series InSAR technology such as persistent scatterer interferometry (PSI) and small-baseline subset (SBAS) cannot identify enough points in mountainous areas because of dense vegetation and steep terrain. In order to improve the accuracy of landslide hazard detection and the reliability of landslide deformation monitoring in areas lacking high coherence stability point targets, this study proposes an adaptive distributed scatterer interferometric synthetic aperture radar (ADS-InSAR) method based on the spatiotemporal coherence of the distributed scatterer (DS), which automatically adjusts its detection threshold to improve the spatial distribution density and reliability of DS detection in the landslide area. After time series network modeling and deformation calculation of the ADS target, the displacement deformation of the landslide area can be accurately extracted. Shuibuya Town in Enshi Prefecture, Hubei Province, China, was used as a case study, along with 18 Sentinal-1A images acquired from March 2016 to April 2017. The ADS-InSAR method was used to obtain regional deformation data. The deformation time series was combined with hydrometeorological and related data to analyze landslide deformation. The results show that the ADS-InSAR method can effectively improve the density of DS distribution, successfully detect existing ancient landslide groups and determine multiple potential landslide areas, enabling early warning for landslide hazards. This study verifies the reliability and accuracy of ADS-InSAR for landslide disaster prevention and mitigation.

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A-Differential Synthetic Aperture Radar Interferometry analysis of a Deep Seated Gravitational Slope Deformation occurring at Bisaccia (Italy)

The Science of The Total Environment ◽

10.1016/j.scitotenv.2016.01.102 ◽

2016 ◽

Vol 550 ◽

pp. 556-573 ◽

Cited By ~ 20

Author(s):

Diego Di Martire ◽

Alessandro Novellino ◽

Massimo Ramondini ◽

Domenico Calcaterra

Keyword(s):

Synthetic Aperture Radar ◽

Slope Deformation ◽

Radar Interferometry ◽

Synthetic Aperture ◽

Synthetic Aperture Radar Interferometry ◽

Aperture Radar

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Reclaimed-Airport Surface-Deformation Monitoring by Improved Permanent-Scatterer Interferometric Synthetic-Aperture Radar: A Case Study of Shenzhen Bao'an International Airport, China

Photogrammetric Engineering & Remote Sensing ◽

10.14358/pers.87.2.105 ◽

2021 ◽

Vol 87 (2) ◽

pp. 105-116

Author(s):

Lu Miao ◽

Kailiang Deng ◽

Guangcai Feng ◽

Kaifeng Li ◽

Zhiqiang Xiong ◽

...

Keyword(s):

Synthetic Aperture Radar ◽

Dynamic Load ◽

Surface Deformation ◽

Deformation Monitoring ◽

Synthetic Aperture ◽

Interferometric Synthetic Aperture Radar ◽

Filling Material ◽

Reclaimed Land ◽

International Airport ◽

Aperture Radar

Reclaimed airports usually have fragile geological structures and are susceptible to the uneven ground settlements caused by filling-material consolidation, underground construction, and dynamic loading from takeoff and landing of aircrafts. Therefore, deformation monitoring is of great significance to the safe operation of reclaimed airports. This study adopts an improved permanent-scatterer interferometric synthetic-aperture radar strategy to map the spatiotemporal deformation of Shenzhen Bao'an International Airport in China using ascending and descending Envisat/ASAR data acquired from 2007 to 2010 and Sentinel-1 data from 2015 to 2019. The results show that uneven settlements of the airport concentrate in the new reclaimed land. Then we explore the settlement characteristics of each functional area. Furthermore, we separate out the dynamic-load settlement of runway No. 2 and confirm the settlements caused by dynamic load. This study provides new ideas for studying deformation in similar fields, and technical references for the future construction of Shenzhen Airport.

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Time- and Space-Varying Atmospheric Phase Correction in Discontinuous Ground-Based Synthetic Aperture Radar Deformation Monitoring

Sensors ◽

10.3390/s18113883 ◽

2018 ◽

Vol 18 (11) ◽

pp. 3883 ◽

Cited By ~ 2

Author(s):

Zengshu Huang ◽

Jinping Sun ◽

Qing Li ◽

Weixian Tan ◽

Pingping Huang ◽

...

Keyword(s):

Synthetic Aperture Radar ◽

Microwave Remote Sensing ◽

Phase Correction ◽

Deformation Monitoring ◽

Synthetic Aperture ◽

Time And Space ◽

Atmospheric Effect ◽

Trend Extraction ◽

Phase Signal ◽

Aperture Radar

Ground-based synthetic aperture radar (GB-SAR) uses active microwave remote-sensing observation mode to achieve two-dimensional deformation measurement and deformation trend extraction, which shows great prospects in the field of deformation monitoring. However, in the process of GB-SAR deformation monitoring, the disturbances caused by atmospheric effect cannot be neglected, and the atmospheric phases will seriously affect the precision of deformation monitoring. In discontinuous GB-SAR deformation monitoring mode, the atmospheric phases are particularly affected by changes of time and space, so the traditional models of atmospheric phase correction are no longer applicable. In this paper, the interferometric phase signal model considering atmospheric phase is first established. Then, the time- and space-varying characteristics of the atmospheric phase are analyzed, and a novel time- and space-varying atmospheric phase correction algorithm, based on coherent scatterers analysis, is proposed. Finally, slope deformation monitoring experiments are carried out to verify the validity and robustness of the proposed algorithm.

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Frequency Domain Panoramic Imaging Algorithm for Ground-Based ArcSAR

Sensors ◽

10.3390/s20247027 ◽

2020 ◽

Vol 20 (24) ◽

pp. 7027

Author(s):

Yun Lin ◽

Yutong Liu ◽

Yanping Wang ◽

Shengbo Ye ◽

Yuan Zhang ◽

...

Keyword(s):

Synthetic Aperture Radar ◽

Frequency Domain ◽

Matched Filter ◽

Deformation Monitoring ◽

Polar Coordinates ◽

Fast Imaging ◽

Synthetic Aperture ◽

Imaging Algorithm ◽

Imaging Algorithms ◽

Aperture Radar

The ground-based arc-scanning synthetic aperture radar (ArcSAR) is capable of 360° scanning of the surroundings with the antenna fixed on a rotating arm. ArcSAR has much wider field of view when compared with conventional ground-based synthetic aperture radar (GBSAR) scanning on a linear rail. It has already been used in deformation monitoring applications. This paper mainly focuses on the accurate and fast imaging algorithms for ArcSAR. The curvature track makes the image focusing challenging and, in the classical frequency domain, fast imaging algorithms that are designed for linear rail SAR cannot be readily applied. This paper proposed an efficient frequency domain imaging algorithm for ArcSAR. The proposed algorithm takes advantage of the angular shift-invariant property of the ArcSAR signal, and it deduces the accurate matched filter in the angular-frequency domain, so panoramic images in polar coordinates with wide swath can be obtained at one time without segmenting strategy. When compared with existing ArcSAR frequency domain algorithms, the proposed algorithm is more accurate and efficient, because it has neither far range nor narrow beam antenna restrictions. The proposed method is validated by both simulation and real data. The results show that our algorithm brings the quality of image close to the time domain back-projection (BP) algorithm at a processing efficiency about two orders of magnitude better, and it has better image quality than the existing frequency domain Lee’s algorithm at a comparable processing speed.

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