Slope Monitoring within Open‐Pit Mines by Ground‐Based Radar: Methodology, Data Processing and Case Studies Review

Mariotti, Francesco; Amoroso, Giovanni; Giudici, Davide; D’Aria, Davide; Farina, Paolo

doi:10.4133/1.4721697

Cited by 3 publications

(3 citation statements)

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“…For the two different processing schemes different software were used, respectively the software GRAPeS (Aresys, 2014) and the software Repeat Pass (Aresys, 2015) both based on Persistent Scatterers (PS) interferometry. The detailed description of the continuous processing scheme and the software GRAPeS is out of the scope of this paper and can be found in Antolini (2014), Barla et al (2010) and Mariotti et al (2012).…”

Section: Gbinsar Images Processingmentioning

confidence: 99%

Remote monitoring of the Comba Citrin landslide using discontinuous GBInSAR campaigns

Barla

Antolini

Bertolo

et al. 2017

Engineering Geology

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This paper describes the use of the discontinuous Ground-Based Interferometric Synthetic Aperture Radar technique (GBInSAR) to monitor the displacement of the Comba Citrin landslide in the North Western Italian Alps. Two GBInSAR surveys were carried out respectively during the summer and the fall of 2015 separated by a temporal baseline of 63 days. For each GBInSAR survey, which lasted respectively 166.2 h (6 dd, 22 h, 12') and 238.3 h (9 dd, 22 h, 18'), two sets of 139 and 275 SAR images were acquired. After the selection of a specific stack of Persistent Scatterers, the SAR images of each survey were analyzed separately and in combination with the images of the other survey to detect the possible displacements occurred both in every single survey as well as in the elapsed time between the two different campaigns. The displacement maps showed that two different sectors of the monitored slope were affected by millimetres to centimetres movements during the monitoring period. The results obtained for the Comba Citrin landslide show that the discontinuous GBInSAR can be reliably adopted to monitor the displacement of landslides moving at an average rate of few centimetres per year.

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Section: Gbinsar Images Processingmentioning

confidence: 99%

Remote monitoring of the Comba Citrin landslide using discontinuous GBInSAR campaigns

Barla

Antolini

Bertolo

et al. 2017

Engineering Geology

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“…persistent scatterers). Atmospheric artefacts were removed from the interferometric signal based on a procedure derived from the PSs approach adapted to process GBInSAR data (Mariotti et al 2012), and the corrected interferograms were finally converted into displacement measurements. The cumulated l.o.s.…”

Section: Comparison Of Gbinsar With Alternative Slope Monitoring Techmentioning

confidence: 99%

Early Warning Monitoring of Natural and Engineered Slopes with Ground-Based Synthetic-Aperture Radar

et al. 2014

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The first application of ground-based interferometric synthetic-aperture radar (GBInSAR) for slope monitoring dates back 13 years. Today, GBInSAR is used internationally as a leading-edge tool for near-real-time monitoring of surface slope movements in landslides and open pit mines. The success of the technology relies mainly on its ability to measure slope movements rapidly with sub-millimetric accuracy over wide areas and in almost any weather conditions. In recent years, GBInSAR has experienced significant improvements, due to the development of more advanced radar techniques in terms of both data processing and sensor performance. These improvements have led to widespread diffusion of the technology for early warning monitoring of slopes in both civil and mining applications. The main technical features of modern SAR technology for slope monitoring are discussed in this paper. A comparative analysis with other monitoring technologies is also presented along with some recent examples of successful slope monitoring.

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“…GBSAR can continuously monitor the deformation of an area for a long period of time. Furthermore, it enables real-time data analysis with exceptional monitoring accuracy at the sub-millimeter level [3][4][5][6]. The whole GBSAR deformation monitoring process can be highly automated.…”

Section: Introductionmentioning

confidence: 99%

Fast Detection of Moving Targets by Refocusing in GBSAR Imagery Based on Enlightend Search

Wang,

Shen

et al. 2023

Remote Sensing

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Ground-based synthetic aperture radar (GBSAR) is widely used in mountains, mines, and other areas because it can get the sub-millimeter deformation information of monitoring scenes. This technology plays a vital role in safeguarding production operations, providing accurate disaster projections, and facilitating timely early warning dissemination. However, the moving target’s defocus/displaced signal will mask the image of GBSAR, which affects the accuracy of deformation inversion. Hence, the detection of moving targets in GBSAR imagery is essential. An algorithm for moving target detection based on refocusing is proposed in this paper to address this problem. The algorithm establishes a two-dimensional parameter search space for squint angle and relative speed. Based on the parameter searching, the improved Range Doppler (RD) algorithm is used for refocusing. The optimal 2D parameters are searched via an algorithm combining the entropy minimization principle and the enlightend search. The presence of a moving target in the observation area is determined based on whether there is an optimal parameter to minimize the entropy value of the refocused image. This approach enables the detection of moving targets in GBSAR imagery. The proposed method is verified by the synthetic data.

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Slope Monitoring within Open‐Pit Mines by Ground‐Based Radar: Methodology, Data Processing and Case Studies Review

Cited by 3 publications

References 0 publications

Remote monitoring of the Comba Citrin landslide using discontinuous GBInSAR campaigns

Remote monitoring of the Comba Citrin landslide using discontinuous GBInSAR campaigns

Early Warning Monitoring of Natural and Engineered Slopes with Ground-Based Synthetic-Aperture Radar

Fast Detection of Moving Targets by Refocusing in GBSAR Imagery Based on Enlightend Search

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