Application of an evidential belief function model in landslide susceptibility mapping

By Omar F. Althuwaynee, Biswajeet Pradhan, Saro Lee. Computational Geosciences, 2012

351 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Management, Monitoring, Policy and Law, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/adba8c8c5833ba43dd80d4d69a7be8652bc12b72

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In Global and Planetary Change

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Citations in the corpus

Ensemble machine-learning-based geospatial approach for flood risk assessment using multi-sensor remote-sensing data and GIS (2017, methodology): “The area under the curve (AUC) method has been widely used in numerous studies to estimate the performance of probability modelling (Althuwaynee et al. 2012).”
Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron neural networks, and functional trees methods (2017, background): “2008; Ohlmacher and Davis 2003), evidential belief function (Althuwaynee et al. 2012; Jebur et al. 2015; Pradhan et al. 2014), fuzzy logic (Aksoy and Ercanoglu 2012; Pourghasemi et al.”
A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India) (2016, background): “Landslide is one of the most serious geo-hazards causing the loss of life and property all over the world, therefore, landslide susceptibility assessment and mitigation of its harmful impactions has been turning into urgent tasks to government and nongovernment agencies (Althuwaynee et al., 2012).”
Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran (2013, background): “…and Turk 2010; Nefeslioglu et al. 2010; Akgun 2011), spatial multicriteria evaluation (Pourghasemi et al. 2012d), evidential belief function model (Althuwaynee et al. 2012; Bui et al. 2012c), and support vector machine (SVM) (Yao et al. 2008; Yilmaz 2010b; Marjanović et al. 2011; Xu et al. 2012;…”