scholarly journals Shallow Landslide Susceptibility Mapping in Sochi Ski-Jump Area Using GIS and Numerical Modelling

2019 ◽  
Vol 8 (3) ◽  
pp. 148 ◽  
Author(s):  
Kai Kang ◽  
Andrey Ponomarev ◽  
Oleg Zerkal ◽  
Shiyuan Huang ◽  
Qigen Lin
Keyword(s):  
Numerical Modelling ◽  
Safety Factor ◽  
Slope Angle ◽  
Shallow Landslide ◽  
Slope Instability ◽  
Northern Caucasus ◽  
Landslide Susceptibility Mapping ◽  
Regression Equations ◽  
Displacement Maps ◽  
Newmark Displacement

The mountainous region of Greater Sochi, including the Olympic ski-jump complex area, located in the northern Caucasus, is always subjected to landslides. The weathered mudstone of low strength and potential high-intensity earthquakes are considered as the crucial factors causing slope instability in the ski-jump complex area. This study aims to conduct a seismic slope instability map of the area. A slope map was derived from a digital elevation model (DEM) and calculated using ArcGIS. The numerical modelling of slope stability with various slope angles was conducted using Geostudio. The Spencer method was applied to calculate the slope safety factors (Fs). The pseudostatic analysis was used to compute Fs considering seismic effect. A good correlation between Fs and slope angle was found. Combining these data, sets slope instability maps were achieved. Newmark displacement maps were also drawn according to empirical regression equations. The result shows that the static safety factor map corresponds to the existing slope instability locations in a shallow landslide inventory map. The seismic safety factor maps and Newmark displacement maps may be applied to predict potential landslides of the study area in the case of earthquake occurrence.

Shallow Landslide Susceptibility Mapping for Zagreb Hilly Area, Croatia

2014 ◽  
pp. 527-531
Author(s):  
Chunxiang Wang ◽  
Snjezana Mihalić Arbanas ◽  
Hideaki Marui ◽  
Naoki Watanabe ◽  
Gen Furuya
Keyword(s):  
Landslide Susceptibility ◽  
Shallow Landslide ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Hilly Area

scholarly journals ANALISIS KESTABILAN LERENG HIGHWALL MENGGUNAKAN METODE BISHOP SIMPLIFIED PADA PIT 13 PT BELAYAN INTERNASIONAL COAL KECAMATAN MARANGKAYU KABUPATEN KUTAI KARTANEGARA

2021 ◽  
pp. 46-54
Author(s):  
Muhammad Amin Syam ◽  
Heriyanto Heriyanto ◽  
Hamzah Umar
Keyword(s):  
Stability Analysis ◽  
Slope Stability ◽  
Safety Factor ◽  
Slope Angle ◽  
Stable Condition ◽  
Physical And Mechanical Properties ◽  
Slope Stability Analysis ◽  
Open Pit ◽  
Mining Company ◽  
Water Saturated

PT Belayan Internasional Coal is an open-pit system mining company, one of its geotechnical activities is the construction of the slopes. Slope stability analysis used the Bishop Simplified method to obtain the value of the dynamic safety factor (≥ 1,1). Currently, the value of the Safety Factor (FK) is an indicator in determining whether the slope is stable or not. The parameters used in the slope stability analysis are the physical and mechanical properties of the rock, namely weight (ɣ), cohesion value (c), and internal shear angle (∅). From the results of dynamic overall slope calculations, the recommended overall slope is constructed with an individual slope angle of 55°, a bench width of 5 meters, a height of 10 meters, and the number of individual slopes of 8 slopes. This design will produce dimensions of the overall slope with 41° slope angle, 80 meters high, and has a dynamic safety factor value of 1,102 with the water-saturated condition. Thus, the slopes are in stable condition.

Landslide susceptibility mapping using GIS and Remote Sensing: A case study of the Rangamati District, Bangladesh

2020 ◽  
Author(s):  
Afruja Begum ◽  
Md Shofiqul Islam ◽  
Md. Muyeed Hasan
Keyword(s):  
Remote Sensing ◽  
Water Pressure ◽  
Research Work ◽  
Slope Angle ◽  
Steep Slope ◽  
Landslide Susceptibility Mapping ◽  
Dominant Factor ◽  
Natural Phenomenon ◽  
Slope Aspect ◽  
Gis And Remote Sensing

Abstract The landslide is a natural phenomenon and one of the most commonplace disasters in the Rangamati Hill tract area which appeals for better forecasting and specify the landslide susceptible zonation. This research work examines the application of GIS and Remote Sensing techniques based on different parameters such as altitude, slope angle, slope aspect, rainfall, land-use land-cover (LULC), geology and stream distance by heuristic model to identify the landslide susceptible zones for the study area. Among the parameters, rainfall, steep slope, geology and LULC are the dominant factor that triggering the landslide. Clayey or silty soils of the study area during heavy and prolong rainfall behave a flow of debris due to water pressure within the soil, resulting landslides. Steep slope has greater influences for weather zones of the rock-masses for susceptible landslides. Result and field observation indicate that the population density and LULC has a vital effect on landslide within the study area. However, landslide susceptible zones were created based on the susceptibility map of the study area which shows that about 19.43% of the area are at low susceptible zone, 56.55% of the area are at medium susceptible zone, 19.19% of the area are in the high susceptible zone and 4.81% of the area is at the very high susceptible zone.

scholarly journals Aveiro Canyon Head (Portugal) Submarine Slope Instability Assessment

2020 ◽  
Vol 10 (24) ◽  
pp. 9038
Author(s):  
Nuno Lapa ◽  
Fernando M. F. S. Marques ◽  
Aurora Rodrigues
Keyword(s):  
Marine Environment ◽  
Regional Scale ◽  
Slope Angle ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Information Value ◽  
Slope Instability ◽  
Landslide Inventory ◽  
Spatial And Temporal Variability ◽  
Sedimentary Dynamics

Mass wasting events are the main processes of sedimentary dynamics that affect the marine environment and which, due to their spatial and temporal variability, are difficult to study and evaluate. Affecting the marine floor, between the coastline and the abyssal plain, these processes are triggered by multiple causes, having different magnitudes and causing drastic changes and impacts on the marine environment and human activities. In this paper, the submarine landslide susceptibility affecting the upper course of the Aveiro canyon (West Iberian Margin) is addressed using statistical models which are based on the statistical relations between a landslide inventory and the landslide predisposing factors bathymetry, sediment cover, slope angle, aspect and curvature. The statistical methods were the widely proven bivariate information value (IV) and the multivariate logistic regression (LR). The model results were validated against the landslide inventory using receiver operating characteristic (ROC) curves and the corresponding area under the curve (AUC), which provided satisfactory results, with IV AUC = 0.79 and LR AUC = 0.83, in spite of the limitations of the databases used in this study. The results obtained suggest that these methods may be useful for the preliminary assessment of sea floor slope instability at a regional scale of analysis, enabling the selection of sites to be studied with much more detailed and expensive methods.

scholarly journals Landslide Susceptibility Mapping Using Different GIS-Based Bivariate Models

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1402 ◽  
Author(s):  
Nohani ◽  
Moharrami ◽  
Sharafi ◽  
Khosravi ◽  
Pradhan ◽  
...  
Keyword(s):  
Land Use ◽  
Landslide Susceptibility ◽  
Vegetation Index ◽  
Slope Angle ◽  
Aerial Photographs ◽  
Landslide Susceptibility Mapping ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Conditioning Factors ◽  
Bivariate Models

Landslides are the most frequent phenomenon in the northern part of Iran, which cause considerable financial and life damages every year. One of the most widely used approaches to reduce these damages is preparing a landslide susceptibility map (LSM) using suitable methods and selecting the proper conditioning factors. The current study is aimed at comparing four bivariate models, namely the frequency ratio (FR), Shannon entropy (SE), weights of evidence (WoE), and evidential belief function (EBF), for a LSM of Klijanrestagh Watershed, Iran. Firstly, 109 locations of landslides were obtained from field surveys and interpretation of aerial photographs. Then, the locations were categorized into two groups of 70% (74 locations) and 30% (35 locations), randomly, for modeling and validation processes, respectively. Then, 10 conditioning factors of slope aspect, curvature, elevation, distance from fault, lithology, normalized difference vegetation index (NDVI), distance from the river, distance from the road, the slope angle, and land use were determined to construct the spatial database. From the results of multicollinearity, it was concluded that no collinearity existed between the 10 considered conditioning factors in the occurrence of landslides. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used for validation of the four achieved LSMs. The AUC results introduced the success rates of 0.8, 0.86, 0.84, and 0.85 for EBF, WoE, SE, and FR, respectively. Also, they indicated that the rates of prediction were 0.84, 0.83, 0.82, and 0.79 for WoE, FR, SE, and EBF, respectively. Therefore, the WoE model, having the highest AUC, was the most accurate method among the four implemented methods in identifying the regions at risk of future landslides in the study area. The outcomes of this research are useful and essential for the government, planners, decision makers, researchers, and general land-use planners in the study area.

scholarly journals Landslide Susceptibility Mapping for the Muchuan County (China): A Comparison Between Bivariate Statistical Models (WoE, EBF, and IoE) and Their Ensembles with Logistic Regression

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 762 ◽  
Author(s):  
Renwei Li ◽  
Nianqin Wang
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Statistical Models ◽  
Landslide Susceptibility ◽  
Slope Angle ◽  
Susceptibility Mapping ◽  
Aerial Photographs ◽  
Weight Of Evidence ◽  
Landslide Susceptibility Mapping ◽  
Topographic Wetness Index

The main purpose of this study is to apply three bivariate statistical models, namely weight of evidence (WoE), evidence belief function (EBF) and index of entropy (IoE), and their ensembles with logistic regression (LR) for landslide susceptibility mapping in Muchuan County, China. First, a landslide inventory map contained 279 landslides was obtained through the field investigation and interpretation of aerial photographs. Next, the landslides were randomly divided into two parts for training and validation with the ratio of 70/30. In addition, according to the regional geological environment characteristics, twelve landslide conditioning factors were selected, including altitude, plan curvature, profile curvature, slope angle, distance to roads, distance to rivers, topographic wetness index (TWI), normalized different vegetation index (NDVI), land use, soil, and lithology. Subsequently, the landslide susceptibility mapping was carried out by the above models. Eventually, the accuracy of this research was validated by the area under the receiver operating characteristic (ROC) curve and the results indicated that the landslide susceptibility map produced by EBF-LR model has the highest accuracy (0.826), followed by IoE-LR model (0.825), WoE-LR model (0.792), EBF model (0.791), IoE model (0.778), and WoE model (0.753). The results of this study can provide references of landslide prevention and land use planning for local government.

scholarly journals Prediction of the sliding type and critical factor of safety in homogeneous finite slopes

2019 ◽  
Vol 9 (7) ◽  
Author(s):  
Farzin Salmasi ◽  
Biswajeet Pradhan ◽  
Bahram Nourani
Keyword(s):  
Safety Factor ◽  
Factor Of Safety ◽  
Critical Factor ◽  
Specific Weight ◽  
Regression Equations ◽  
Plane Failure ◽  
Angle Of Internal Friction ◽  
Modes Of Failure ◽  
Constant Slope

Abstract In this paper, the effect of soil material parameters including soil specific weight (γ), cohesion (C), angle of internal friction ($$\emptyset$$ ∅ ), and geometric parameter of slope including angle with the horizontal (β) for a constant slope height (H) on factor of safety (Fs) was investigated. Fs was considered in two scenarios: (1) slope with dry condition, and (2) with steady-state saturated condition that comprises water level drawdown circumstances. In addition, the type of slip circle was also investigated. For this purpose, the SLOPE/W software as a subgroup of Geo-Studio software was implemented. Results showed that decreasing of water table level and omitting the hydrostatic pressure on the slope consequently would result in safety factor decrement. Comparison of the plane and circular failure surfaces showed that plane failure method produced good results for near-vertical slopes only. Determination of slip type showed that for state (30° < β < 45°), the three types of failure circles (toe, slope or midpoint circle) may occur. For state (45° < β < 60°), two modes of failure may occur: midpoint circle and toe circle. For state (β > 60°), the mode of failure circle is only toe circle. Linear and nonlinear regression equations were obtained for estimation of slope safety factor.

scholarly journals Landslide susceptibility mapping by using a geographic information system (GIS) along the China–Pakistan Economic Corridor (Karakoram Highway), Pakistan

2019 ◽  
Vol 19 (5) ◽  
pp. 999-1022 ◽  
Author(s):  
Sajid Ali ◽  
Peter Biermanns ◽  
Rashid Haider ◽  
Klaus Reicherter
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Landslide Susceptibility ◽  
Slope Angle ◽  
Active Faults ◽  
Geographic Information ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Susceptibility Map ◽  
Karakoram Highway

Abstract. The Karakoram Highway (KKH) is an important route, which connects northern Pakistan with Western China. Presence of steep slopes, active faults and seismic zones, sheared rock mass, and torrential rainfall make the study area a unique geohazards laboratory. Since its construction, landslides constitute an appreciable threat, having blocked the KKH several times. Therefore, landslide susceptibility mapping was carried out in this study to support highway authorities in maintaining smooth and hazard-free travelling. Geological and geomorphological data were collected and processed using a geographic information system (GIS) environment. Different conditioning and triggering factors for landslide occurrences were considered for preparation of the susceptibility map. These factors include lithology, seismicity, rainfall intensity, faults, elevation, slope angle, aspect, curvature, land cover and hydrology. According to spatial and statistical analyses, active faults, seismicity and slope angle mainly control the spatial distribution of landslides. Each controlling parameter was assigned a numerical weight by utilizing the analytic hierarchy process (AHP) method. Additionally, the weighted overlay method (WOL) was employed to determine landslide susceptibility indices. As a result, the landslide susceptibility map was produced. In the map, the KKH was subdivided into four different susceptibility zones. Some sections of the highway fall into high to very high susceptibility zones. According to results, active faults, slope gradient, seismicity and lithology have a strong influence on landslide events. Credibility of the map was validated by landslide density analysis (LDA) and receiver operator characteristics (ROC), yielding a predictive accuracy of 72 %, which is rated as satisfactory by previous researchers.

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