Forecasting the time of failure of landslides at slope-scale: A literature review

Intrieri, Emanuele; Carlà, Tommaso; Gigli, Giovanni

doi:10.1016/j.earscirev.2019.03.019

Cited by 215 publications

(130 citation statements)

References 129 publications

Supporting

Mentioning

104

Contrasting

Unclassified

Order By: Relevance

“…Distinct from the synchronous model, some correlation errors cannot be eliminated in the following asynchronous double difference observation model [18,20]:…”

Section: Methodsologymentioning

confidence: 99%

See 1 more Smart Citation

Asynchronous RTK Method for Detecting the Stability of the Reference Station in GNSS Deformation Monitoring

Huang

Zhang

et al. 2020

Sensors

View full text Add to dashboard Cite

The real-time kinematic (RTK) positioning technique of global navigation satellite systems (GNSS) has been widely used for deformation monitoring in the past several decades. The RTK technique can provide relative displacements in a local reference frame defined by a highly stable reference station. However, the traditional RTK solution does not account for reference stations that experience displacement. This presents a challenge for establishing a near real-time GNSS monitoring system, as since the displacement of a reference station can be easily misinterpreted as a sign of rapid movement at the monitoring station. In this study, based on the reference observations in different time domains, asynchronous and synchronous RTK are proposed and applied together to address this issue, providing more reliable displacement information. Using the asynchronously generated time difference of a reference frame, the proposed approach can detect whether a measured displacement has occurred in the reference or the monitoring station in the current epoch. This allows for the separation of reference station movements from monitoring station movements. The results based on both simulated and landslide monitoring data demonstrate that the proposed method can provide reliable displacement determinations, which are critical in deformation monitoring applications, such as the early warning of landslides.

show abstract

“…Distinct from the synchronous model, some correlation errors cannot be eliminated in the following asynchronous double difference observation model [18,20]:…”

Section: Methodsologymentioning

confidence: 99%

“…The accuracy of the ARTK model is significantly lower than that of the SRTK model [18]; hence, the difference between the two must be calculated by σ MSE(X ARTK −X SRTK ) before setting the detection threshold. Thereafter, the ∆X(t) term obtained by each epoch will be compared with the previous statistical value of 3*σ MSE(X ARTK −X SRTK ) .…”

mentioning

confidence: 99%

Asynchronous RTK Method for Detecting the Stability of the Reference Station in GNSS Deformation Monitoring

Huang

Zhang

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Rainfall-triggered landslides pose a severe threat to societies on all continents [1,2]. Rainfall thresholds are therefore essential for characterizing landslide hazard and developing early warning systems [3][4][5]. Empirical approaches define thresholds on scales ranging from local [6,7] to regional and global [8,9], based on the observed relation between dated landslides and rainfall characteristics such as intensity, accumulation, duration, or antecedent rainfall (AR) conditions [10].…”

Section: Introductionmentioning

confidence: 99%

“…parameters through a spatially extended infinite-slope stability model [25]. However, the large required data input for well-calibrated process-based thresholds explains their current limitation to mostly applications at the hillslope scale or through numerical simulations [4,21,[25][26][27].The estimation of empirical rainfall thresholds is also associated with additional sources of uncertainty. Firstly, landslide inventories are inherently biased towards high-impact landslide events and regions that are most accessible, while their accuracy is constrained by the scientific validity of the reporting sources, especially in data-scarce low-capacity environments [1,[28][29][30][31].…”

mentioning

confidence: 99%

See 1 more Smart Citation

Towards a Transferable Antecedent Rainfall—Susceptibility Threshold Approach for Landsliding

Monsieurs

Dewitte

Depicker

et al. 2019

Water

View full text Add to dashboard Cite

Determining rainfall thresholds for landsliding is crucial in landslide hazard evaluation and early warning system development, yet challenging in data-scarce regions. Using freely available satellite rainfall data in a reproducible automated procedure, the bootstrap-based frequentist threshold approach, coupling antecedent rainfall (AR) and landslide susceptibility data as proposed by Monsieurs et al., has proved to provide a physically meaningful regional AR threshold equation in the western branch of the East African Rift. However, previous studies could only rely on globaland continental-scale rainfall and susceptibility data. Here, we use newly available regional-scale susceptibility data to test the robustness of the method to different data configurations. This leads us to improve the threshold method through using stratified data selection to better exploit the data distribution over the whole range of susceptibility. In addition, we discuss the effect of outliers in small data sets on the estimation of parameter uncertainties and the interest of not using the bootstrap technique in such cases. Thus improved, the method effectiveness shows strongly reduced sensitivity to the used susceptibility data and is satisfyingly validated by new landslide occurrences in the East African Rift, therefore successfully passing first transferability tests. parameters through a spatially extended infinite-slope stability model [25]. However, the large required data input for well-calibrated process-based thresholds explains their current limitation to mostly applications at the hillslope scale or through numerical simulations [4,21,[25][26][27].The estimation of empirical rainfall thresholds is also associated with additional sources of uncertainty. Firstly, landslide inventories are inherently biased towards high-impact landslide events and regions that are most accessible, while their accuracy is constrained by the scientific validity of the reporting sources, especially in data-scarce low-capacity environments [1,[28][29][30][31]. Secondly, rainfall data comprise uncertainties related to the spatial representativeness of rain gauges or biases in satellite-derived estimates [32,33]. Thirdly, the definition of rainfall parameters, with intensity and duration forming the most frequently used parameter couple [3,5], varies strongly across studies [3]. Finally, the latter parameters' interdependence is problematic, obscuring the physical processes associated with the calculated thresholds [34].In order to account for and characterize threshold uncertainties, a growing number of reproducible statistical techniques have been developed [3]. A weakness of such methods is, however, that they are generally tailored to a specific area and available data sets, which often prevents straightforward transferability to other regions and data sets [35]. Nevertheless, transferability is not only essential for evaluating and comparing landslide hazard over different regions of the world [10,36], but also valuable in the context of the in...

show abstract

Early detection of potential landslides along high‐speed railway lines: A pressing issue

Zhu,

Qiu,

Cui

et al. 2023

Earth Surf Processes Landf

View full text Add to dashboard Cite

Early detection of landslides is important for prevention and mitigation of landslide disasters. Especially, accurately identifying potential landslides along high‐speed railway is becoming a pressing issue for operation safety of high‐speed railway. Here, 161 Sentinel‐1A satellite images from March 2017 to September 2022 were acquired to detect potential landslides along the Lanzhou‐Urumqi high‐speed railway (LUHR) in Qinghai. Results show that rainfall is the main cause for the transition from secondary creep (steady state) to tertiary creep (accelerated) at the Jiujiawan landslide. The hot spot analysis method was used to cluster the average line‐of‐sight deformation velocity along the LUHR, effectively extracting five deformation zones that may pose a threat. Optical satellite image analysis revealed four potential landslides and one unstable slope. Furthermore, the rescaled range analysis documented that the Hurst exponent is greater than 0.8 for all four potential landslide instability points, implying that the identified potential landslide areas are still in motion and may pose a threat to the operation of the LUHR. On this basis, we propose a framework for early identification and monitoring of landslides along the high‐speed railway lines that supports landslide hazard managing with the goal to reduce landslide risk.

show abstract

Forecasting the time of failure of landslides at slope-scale: A literature review

Cited by 215 publications

References 129 publications

Asynchronous RTK Method for Detecting the Stability of the Reference Station in GNSS Deformation Monitoring

Asynchronous RTK Method for Detecting the Stability of the Reference Station in GNSS Deformation Monitoring

Towards a Transferable Antecedent Rainfall—Susceptibility Threshold Approach for Landsliding

Early detection of potential landslides along high‐speed railway lines: A pressing issue

Contact Info

Product

Resources

About