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

Abstract

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.

Flood Management in Aqala through an Agent-Based Solution and Crowdsourcing Services in an Enterprise Geospatial Information System

“…The application of numerical models in crisis management is common [44], but in this research, a framework for these models was defined. To implement mathematical models, a framework is used in tensor space (Figure 3, parts 5-7).…”

Research on Search Method of Potential Sliding Surface of Rock Slope with Embedded Structural Plane

“…e calculation of the slope stability coefficient should be based on the sliding surface obtained by random search, and the potential sliding surface of the slope is determined by comparing the safety factors of sliding surfaces obtained from all searches. Among the calculation methods of slope stability, the most commonly used method is the limit equilibrium method, including Spencer method [1,2], Bishop method [3,4], Janbu method, transfer coefficient method, Morgenstern-Price method, Sarma method, as well as various methods to improve and optimize the above methods [5][6][7][8]. Tang et al [9] considered the influence of the locked section in the rock slope and analyzed the dissipated power inside the slope.…”

Exploring Influence of Sampling Strategies on Event-Based Landslide Susceptibility Modeling

“…It is used to assess the likelihood (0 to 1) or degree (e.g., low, moderate, and high) of landslide occurrence in an area with given local terrain attributes [13]. Traditionally, modeling methods can be classified into three main categories [14][15][16] of approaches: deterministic [17][18][19], heuristic [20,21], and statistical [22][23][24][25][26][27]. A review of the literature indicates that continuing improvements in remote sensing and geographic information systems (GIS) have led to the incorporation of machine learning (and data mining) models for the evaluation of regional landslide susceptibility; examples include decision tree [28][29][30], rough set [31,32], support vector machine [16,33], neural network [16,[34][35][36][37][38][39][40][41][42][43], fuzzy theory [35,[44][45][46][47][48], neural fuzzy systems [35,42,[49][50][51], and entropyand evolution-based algorithms…”