Landslide monitoring in southwestern China via time-lapse electrical resistivity tomography

Xu, Dong; Hu, Xiangyun; Shan, Chunling; Li, Rui-Heng

doi:10.1007/s11770-016-0543-3

Cited by 37 publications

(8 citation statements)

References 43 publications

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“…The use of SP methods is also noted, although in a much reduced capacity to ER (Colangelo et al, ). In total, 20 time‐lapse ER monitoring surveys are identified in the literature: Bièvre et al (), Crawford and Bryson (), Friedel et al (), Gance et al (), Grandjean et al (), Jomard et al (), Lebourg et al (), Lehmann et al (), Lucas et al (), Luongo et al (), Merritt et al (), Palis, Lebourg, Vidal, et al (), Palis, Lebourg, Tric, et al (), Supper et al (), Travelletti et al (), Uhlemann et al (), and Xu et al (). One time‐lapse SP monitoring survey is identified, by Colangelo et al ().…”

Section: Geophysical Monitoring Of Landslides: Methods and Case Studiesmentioning

confidence: 99%

Geophysical Monitoring of Moisture‐Induced Landslides: A Review

Whiteley

Chambers

Uhlemann

et al. 2019

Reviews of Geophysics

203

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Geophysical monitoring of landslides can provide insights into spatial and temporal variations of subsurface properties associated with slope failure. Recent improvements in equipment, data analysis, and field operations have led to a significant increase in the use of such techniques in monitoring. Geophysical methods complement intrusive approaches, which sample only a very small proportion of the subsurface, and walk-over or remotely sensed data, which principally provide information only at the ground surface. In particular, recent studies show that advances in geophysical instrumentation, data processing, modeling, and interpretation in the context of landslide monitoring are significantly improving the characterization of hillslope hydrology and soil and rock hydrology and strength and their dynamics over time. This review appraises the state of the art of geophysical monitoring, as applied to moisture-induced landslides. Here we focus on technical and practical uses of time-lapse methods in geophysics applied to monitoring moisture-induced landslide. The case studies identified in this review show that several geophysical techniques are currently used in the monitoring of subsurface landslide processes. These geophysical contributions to monitoring and predicting the evolution of landslide processes are currently underrealized. Hence, the further integration of multiple-parametric and geotechnically coupled geophysical monitoring systems has considerable potential. The complementary nature of certain methods to map the distribution of subsurface moisture and elastic moduli will greatly increase the predictive and monitoring capacity of early warning systems in moisture-induced landslide settings. Figure 4. The geophysical methods identified in the 31 case studies, shown by mode of acquisition and method. The acronyms for each method are shown in the lower boxes.

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Section: Geophysical Monitoring Of Landslides: Methods and Case Studiesmentioning

confidence: 99%

Geophysical Monitoring of Moisture‐Induced Landslides: A Review

Whiteley

Chambers

Uhlemann

et al. 2019

Reviews of Geophysics

203

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“…Landslide boundaries are defined by the topography and geomorphology, i.e. cracks, scarps, surface deformation, and bedrock (Xu et al 2016). Facing south-west, it lies with a leading-edge elevation H 1 being 1,500 m and a trailing edge elevation H 2 being 2,900 m, the relative relief is 1,400 m. Its maximum length L 1 is 4,000 m, and its maximum width L 2 is 1,700 m. The general thickness is 55 m, and the earth volume is approximately 170 million cubic metres.…”

Section: Parameters Determination In Pcscmentioning

confidence: 99%

Giant landslide displacement analysis using a point cloud set conflict technique: a case in Xishancun landslide, Sichuan, China

Liu

Shao

et al. 2018

International Journal of Remote Sensing

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2019) Giant landslide displacement analysis using a point cloud set conflict technique: a case in ABSTRACT Landslides, threatening millions of human lives, are geological phenomena on earth, occurred frequently. An increasing number of techniques are being used to monitor landslide deformation. Among these, Light Detection and Ranging (LiDAR) stands out for its high efficiency and accuracy in displacement detection, particularly for giant landslides. In this work, we collected two temporal datasets of terrain laser scanning and proposed a flowchart for giant landslide displacement analysis using the point cloud set conflict(PCSC) technique. First, the terrestrial points were obtained by performing registration and off-terrain point filtering. Second, the landslide displacement field was acquired using the proposed method based on its surface roughness. The displacement results from our established methodological system are comparable with the ones of Interferometric Synthetic Aperture Radar (InSAR)-derived deformations. The differences estimated from two systems are at the centimetre level. Cross-analysis on the trigger factor with landslide occurred mechanism could be achieved based on the results as well. Therefore, this work provides a novel system to analyse the displacement of a giant landslide in the future study. ARTICLE HISTORY

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“…It is 22 km from Wenchuan City, and is one of the most prone to severe geo-hazard areas, after being exposed to the 5.12 Wenchuan Earthquake in 2008 (Cui et al 2011;Dai et al 2011). The specifically considered 'Xishancun Landslide' located north of the Zagunao River is a large soil accumulation with a relative elevation of about 1790 m, slope length of about 3800 m, and average width of approximately 700 m (Xu et al 2016).…”

Section: Description Of Experimental Areamentioning

confidence: 99%

Multi-sensor observation fusion scheme based on 3D variational assimilation for landslide monitoring

Liu

Shao

2018

Geomatics, Natural Hazards and Risk

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Multi-sensor observation is very important for monitoring landslide disasters. Since various surveying techniques are currently available for detecting variational slope activities from different perspectives, studies have focused on integration of multi-source information for the analysing landslide displacements. In this study, a general multi-source data fusion scheme for landslide monitoring based on three-dimensional variation (3DVar) data assimilation was developed. The scheme was used to fuse different observations of Xishancun Landslide in Li County, Sichuan Province, China. First, the displacement observations obtained by a Global Positioning System (GPS) and Borehole Inclinometers (BIs) were assimilated for accurate evaluation of slope activities. Then, slope Stability Index (SI) was introduced to validate the assimilation results within a time interval. SI Assi values calculated using the integration model developed in the present study were compared with SI FS simulated by a physically based landslide model. The correlation coefficient between them ss 0.75, which is larger than those with SI GPS (0.45) or SI BIs (0.41) values determined by the GPS and BIs respectively. The assimilation results are thus confirmed to be more credible for slope stability simulation.

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Landslide monitoring in southwestern China via time-lapse electrical resistivity tomography

Cited by 37 publications

References 43 publications

Geophysical Monitoring of Moisture‐Induced Landslides: A Review

Geophysical Monitoring of Moisture‐Induced Landslides: A Review

Giant landslide displacement analysis using a point cloud set conflict technique: a case in Xishancun landslide, Sichuan, China

Multi-sensor observation fusion scheme based on 3D variational assimilation for landslide monitoring

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