Forecasting the landslide evolution: from theory to practice

Cascini, Leonardo; Scoppettuolo, Maria Rosaria; Babilio, Enrico

doi:10.1007/s10346-022-01934-3

Cited by 19 publications

(5 citation statements)

References 33 publications

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“…There has been recent progress in forecasting both location and time [5,8]. Linking kinematic data and the underlying micromechanics of granular failure together has shown to be effective in forecasting the location and time of granular failure [5,9,10].…”

Section: Introductionmentioning

confidence: 99%

Forecasting landslides using community detection on geophysical satellite data

et al. 2023

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Section: Introductionmentioning

confidence: 99%

Forecasting landslides using community detection on geophysical satellite data

et al. 2023

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“…In SSA, the population size was set to 100, the maximum number of iterations was set to 50, the optimization range of the penalty factor was set to [6,1000], and the optimization range of the modal number was set to [3,10]. During the iteration process, the fitness value dropped rapidly to the optimal value of 0.00596, and the convergence effect was obvious, as shown in Figure 4.…”

Section: Vmd Parameter Optimizationmentioning

confidence: 99%

“…The empirical prediction model is a prediction method based on the observed sharp increase in deformation before landslide destabilization [8,9]. The time of landslide destabilization is predicted by analysis and derivation on a physical model [10]. This prediction method is based on specific experimental observations.…”

Section: Introductionmentioning

confidence: 99%

Displacement Prediction Method for Bank Landslide Based on SSA-VMD and LSTM Model

Xie,

Huang

2024

Mathematics

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Landslide displacement prediction is of great significance for the prevention and early warning of slope hazards. In order to enhance the extraction of landslide historical monitoring signals, a landslide displacement prediction method is proposed based on the decomposition of monitoring data before prediction. Firstly, based on the idea of temporal addition, the sparrow search algorithm (SSA) coupled with the variational modal decomposition (VMD) algorithm is used to decompose the total landslide displacement into trend item, periodic item and random item; then, the displacement values of the subitems are fitted by using the long and short-term memory (LSTM) neural network, and the predicted cumulative landslide displacement is obtained by adding up the predicted values of the three subsequences. Finally, the historical measured data of the Shuping landslide is taken as an example. Considering the effects of seasonal rainfall and reservoir water level rise and fall, the displacement of this landslide is predicted, and the prediction results of other traditional models are compared. The results show that the landslide displacement prediction model of SSA-VMD coupled with LSTM can predict landslide displacement more accurately and capture the characteristics of historical signals, which can be used as a reference for landslide displacement prediction.

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“…Due to the different lithology of the stratum, the number of geological disasters developed on the surface has obvious distribution differences. The structure and occurrence of the rock mass directly affect the formation and development of the landslide 32 . In terms of lithology, the rock landslide disasters in the western part of Henan Province are mainly developed in sandstone, shale, and mudstone.…”

Section: Slope Locking Section Settingmentioning

confidence: 99%

Study on deformation and failure characteristics of oblique-cut locked rock slope under rainfall conditions

Wang,

Yuan,

Huang

et al. 2024

Sci Rep

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Based on the disaster-pregnant environment and development characteristics of landslide disasters in the western region of Henan Province, a generalized model was established by taking the “oblique-cut” locking rock slope in the layered rock slope as the research object. The numerical simulation method was used to analyze the deformation and failure mechanism and stability influence law of the oblique-cut locking rock slope in western Henan under rainfall conditions. The results show that the inclination angle of the weak interlayer directly affects the deformation and failure characteristics of the slope rock mass. With the increase of the geometric parameters of the slope and the inclination angle of the weak interlayer, the failure mechanism is manifested as the slip shear failure along the level at the foot of the slope → the slip shear failure along the level at the foot of the slope (the sliding surface moves upward) → the shear failure in the middle of the slope surface → the slip shear failure along the level at the foot of the slope (the sliding surface moves downward) → the uplift shear failure at the lower edge of the rock layer. When the dip angle of the weak interlayer is constant, the slope stability decreases gradually with the increase in slope gradient and slope height, and the geometric factors of the slope control the overall change trend of the slope stability coefficient. When the slope is greater than 55° and the slope height is greater than 55 m, the shear stress of the slope locking section exceeds its shear strength, and the probability of landslide instability is greatly increased.

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Forecasting the landslide evolution: from theory to practice

Cited by 19 publications

References 33 publications

Forecasting landslides using community detection on geophysical satellite data

Forecasting landslides using community detection on geophysical satellite data

Displacement Prediction Method for Bank Landslide Based on SSA-VMD and LSTM Model

Study on deformation and failure characteristics of oblique-cut locked rock slope under rainfall conditions

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