GIS techniques and statistical models in evaluating landslide hazard

By A. Carrara, M. Cardinali, R. Detti, Fausto Guzzetti, V. Pasqui, P. Reichenbach. 1991

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy (1999, methodology): “The most favored are discriminant analysis, linear and logistic regression, and Žneural networks Neuland, 1976; Carrara, 1983; Carrara et al., 1991; Carrara et al., 1995; Roth, 1983; Yin and Yan, 1988; Neeley and Rice, 1990; Mark, .1992; van Westen, 1993, 1994; Chung et al., 1995 .”
Comparative evaluation of landslide susceptibility in Minamata area, Japan (2005, methodology): “Landslide hazard and risk zoning and mapping for urban and rural areas is widely performed around the world, as the GIS technique was applied to deal with this problem decades ago ( Carrara et al. 1991, 1992; van Westen 1993; Hansen et al. 1995; Cruden and Fell 1997; Aleotti and Chowdhury 1999; Gup”
Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey (2006, background): “Although, the relation between slope aspect and mass movement has long been investigated, no general agreement exists on the effect of aspect on landslide occurrence ( Carrara et al. 1991 ).”
Validation and Evaluation of Predictive Models in Hazard Assessment and Risk Management (2006, methodology): “…the most commonly addressed by the methods mentioned above (i.e., Neuland, 1976; Rice and Pillsbury, 1982; Carrara, 1983; Furbish and Rice, 1983; Carrara et al., 1991; Chung et al., 1995; van Westen et al., 1997; Rowbotham and Dudycha, 1998; Chung and Fabbri, 1999; Dai and Lee, 2002; Santacana…”
A comparative assessment of canonical correlation forest, random forest, rotation forest and logistic regression methods for landslide susceptibility mapping (2018, background): “Therefore, landslide susceptibility mapping (LSM) has been the most concentrated topic in landslide related studies (Carrara et al. 1991; Guzzetti et al. 2005; Wang et al. 2015; Kutlug Sahin, Ipbuker, and Kavzoglu CONTACT Emrehan Kutlug Sahin e.sahin@gtu.edu.tr 2018 Informa UK Limited, trading as…”
Scaling properties of rainfall induced landslides predicted by a physically based model (2013, background): “…relationship between the magnitude of the rainfall trigger (i.e., I and D) we first partitioned the study area into sub-basins i.e., hydrological ensembles of slope units, where a slope unit is a hydrological region bounded by drainage and divide lines (Carrara et al., 1991; Guzzetti et al., 1999).”
Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat - Turkey) (2009, background): “…and statistical bivariate analysis (Brabb et al., 1972; DeGraff and Romesburg, 1980; Jade and Sarkar, 1993; Chung and Fabbri, 1999; Irigaray, 1995; Fernández et al., 2003; Yilmaz and Yildirim, 2006) and multivariate analysis (Carrara, 1983a; Carrara et al., 1991; Baeza, 1994; Chung et al., 1995).”