Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey)

By Hakan Ahmet Nefeslioglu, T. Duman, S. Durmaz. 2008

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Citations in the corpus

An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: a case study of Duzkoy district (2015, background): “It should be mentioned that recent studies conducted in the Black Sea region also considered similar conditioning factors (Yalcin et al. 2011; Akgun et al. 2008; Nefeslioglu et al. 2008).”
GIS-based landslide susceptibility mapping using analytical hierarchy process (AHP) and certainty factor (CF) models for the Baozhong region of Baoji City, China (2015, methodology): “The plan curvature is widely used in landslide susceptibility mapping (Nefeslioglu et al. 2008; Pourghasemi et al. 2012a, b).”
A comparative assessment of canonical correlation forest, random forest, rotation forest and logistic regression methods for landslide susceptibility mapping (2018, background): “For instance, Nefeslioglu, Duman, and Durmaz (2008) proposed two sampling methods, one of which considers the landslide area with depletion and accumulation zones, and the other uses a zone representing pre-failure conditions at that point.”
Artificial Neural Network (ANN) and Regression Tree (CART) applications for the indirect estimation of unsaturated soil shear strength parameters (2014, methodology): “ANN models (Arora et al., 2004; Gómez and Kavzoglu, 2005; Yesilnacar and Topal, 2005; Kanungo et al., 2006; Nefeslioglu et al., 2008) have been implemented for LSZ studies.”
Application of statistical index and index of entropy methods to landslide susceptibility assessment in Gongliu (Xinjiang, China) (2016, background): “The characterization of slope morphology and flow can be analyzed with the help of the general curvature map (Nefeslioglu et al. 2008).”
Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey) (2008, methodology): “In literature, the logistic regression technique is widely used in producing landslide susceptibility maps (e.g., Atkinson and Massari 1998; Gorsevski et al. 2000; Lee and Min 2001; Ohlmacher and Davis 2003; Lee 2004, 2005; Ayalew and Yamagishi 2005; Can et al. 2005; Duman et al. 2006; Nefeslioglu ”
An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm (2012, background): “…into consideration in almost all landslide susceptibility, hazard, and risk assessment studies (i.e., Atkinson and Massari, 1998; Can et al., 2005; Nefeslioglu et al., 2008a, 2010; Yilmaz, 2010b; Akgun and Turk, 2010; Pradhan et al., 2010), and the slope gradient is also considered as a…”