Landslide susceptibility mapping using machine learning for Wenchuan County, Sichuan province, China [PDF]
E3S Web of Conferences, 2020 Landslide susceptibility mapping is a method used to assess the probability and spatial distribution of landslide occurrences. Machine learning methods have been widely used in landslide susceptibility in recent years.
Yang Xin +4 more
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Landslide Susceptibility Mapping of Phewa Watershed, Kaski, Nepal
Mathematical Models in Engineering, 2023 Abstract The objective of this study was to assess the quantities of association between landslide events and causal factors in order to generate an accurate, updated landslide susceptibility map (LSM) of the Phewa watershed in Kaski, Gandaki District, Nepal.
Bimal Bahadur Kunwar +3 more
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A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS. [PDF]
, 2013 he purpose of the present study is to compare the prediction performances of three different approaches such as decision tree (DT), support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) for landslide susceptibility mapping at ...
Pradhan, Biswajeet
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Regional Rainfall-Induced Landslide Risk Assessment Using Susceptibility Mapping and Unexpected High-Intensity Rainfall [PDF]
BIO Web of ConferencesLandslides are one of the most common natural hazards in Malaysia, and besides geological conditions, rainfall intensity and duration are critical factors in assessing landslide risk.
Anees Mohd Talha +2 more
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Mapping landslide susceptibility using data-driven methods
Science of The Total Environment, 2017 Most epistemic uncertainty within data-driven landslide susceptibility assessment results from errors in landslide inventories, difficulty in identifying and mapping landslide causes and decisions related with the modelling procedure. In this work we evaluate and discuss differences observed on landslide susceptibility maps resulting from: (i) the ...
Zêzere, José +4 more
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Spatial prediction of landslide hazard at the Luxi area (China) using support vector machines [PDF]
, 2015 The main objective of this study is to investigate the potential application of GIS-based Support Vector Machines (SVM) with four kernel functions, i.e., radial basis function (RBF), polynomial (PL), sigmoid (SIG), and linear (LN) for landslide ...
Akgun, Aykut +5 more
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, 2017 We develop a stochastic modeling approach based on spatial point processes of log-Gaussian Cox type for a collection of around 5000 landslide events provoked by a precipitation trigger in Sicily, Italy.
Huser, Raphael +2 more
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Evaluation and comparison of bivariate and multivariate statistical methods for landslide susceptibility mapping (case study: Zab Basin) [PDF]
, 2012 Landslides are among the great destructive factors which cause lots of fatalities and financial losses all over the world every year. Studying of the factors affecting occurrence of landslides in a region and zoning the resulting damages will certainly ...
Ahmad, Baharin, Khezri, S., Shahabi, H.
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Geosciences, 2023 Naïve Bayes classification is widely used for landslide susceptibility analysis, especially in the form of weights-of-evidence. However, when significant conditional dependence is present, the probabilities derived from weights-of-evidence are biased ...
Florimond De Smedt +2 more
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Landslide Inventory, Susceptibility, Hazard and Risk Mapping
, 2022 Landslide is that the downslope movement of debris, rocks, or earth material under the influence of the force of gravity. Although the causes and mechanisms of landslides are complicated, human action, earthquakes, and severe rainfall can trigger them. It can happen when the driving force surpasses the resisting force due to natural soil or rock slope ...
openaire +3 more sources