Exploring the effect of absence selection on landslide susceptibility models: A case study in Sicily, Italy
暂无分享,去创建一个
[1] L B Lusted,et al. Radiographic applications of receiver operating characteristic (ROC) curves. , 1974, Radiology.
[2] G. Wahba. Smoothing noisy data with spline functions , 1975 .
[3] Peter Craven,et al. Smoothing noisy data with spline functions , 1978 .
[4] K. Beven,et al. A physically based, variable contributing area model of basin hydrology , 1979 .
[5] J. Hanley,et al. The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.
[6] Alberto Carrara,et al. Multivariate models for landslide hazard evaluation , 1983 .
[7] E. E. Brabb. Innovative approaches to landslide hazard and risk mapping , 1985 .
[8] C. Thorne,et al. Quantitative analysis of land surface topography , 1987 .
[9] David W. Hosmer,et al. Applied Logistic Regression , 1991 .
[10] J. Friedman. Multivariate adaptive regression splines , 1990 .
[11] P. Reichenbach,et al. GIS techniques and statistical models in evaluating landslide hazard , 1991 .
[12] J. Freidman,et al. Multivariate adaptive regression splines , 1991 .
[13] P. Reichenbach,et al. Gis Technology in Mapping Landslide Hazard , 1995 .
[14] P. Reichenbach,et al. Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy , 1999 .
[15] P. Aleotti,et al. Landslide hazard assessment: summary review and new perspectives , 1999 .
[16] A. Clerici,et al. A procedure for landslide susceptibility zonation by the conditional analysis method , 2002 .
[17] Joseph D Conklin,et al. Applied Logistic Regression , 2002, Technometrics.
[18] John C. Davis,et al. Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA , 2003 .
[19] Andrea G. Fabbri,et al. Validation of Spatial Prediction Models for Landslide Hazard Mapping , 2003 .
[20] S. Weiss,et al. GLM versus CCA spatial modeling of plant species distribution , 1999, Plant Ecology.
[21] Lionel C. Briand,et al. Using multiple adaptive regression splines to support decision making in code inspections , 2004, J. Syst. Softw..
[22] T. Hastie,et al. Using multivariate adaptive regression splines to predict the distributions of New Zealand ’ s freshwater diadromous fish , 2005 .
[23] Lucila Ohno-Machado,et al. The use of receiver operating characteristic curves in biomedical informatics , 2005, J. Biomed. Informatics.
[24] Saro Lee,et al. Application and cross-validation of spatial logistic multiple regression for landslide susceptibility analysis , 2005 .
[25] A. Brenning. Spatial prediction models for landslide hazards: review, comparison and evaluation , 2005 .
[26] R. Soeters,et al. Landslide hazard and risk zonation—why is it still so difficult? , 2006 .
[27] M. Eeckhaut,et al. Prediction of landslide susceptibility using rare events logistic regression: A case-study in the Flemish Ardennes (Belgium) , 2006 .
[28] P. Reichenbach,et al. Estimating the quality of landslide susceptibility models , 2006 .
[29] H. A. Nefeslioglu,et al. An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps , 2008 .
[30] P. Frattini,et al. Comparing models of debris-flow susceptibility in the alpine environment , 2008 .
[31] S. L. Kuriakose,et al. Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview , 2008 .
[32] S. Schnabel,et al. Using and comparing two nonparametric methods (CART and MARS) to model the potential distribution of gullies , 2009 .
[33] Ángel M. Felicísimo,et al. Modelling the occurrence of gullies in rangelands of southwest Spain , 2009 .
[34] Manfred F. Buchroithner,et al. A GIS-based back-propagation neural network model and its cross-application and validation for landslide susceptibility analyses , 2010, Comput. Environ. Urban Syst..
[35] Christian Conoscenti,et al. Exporting a Google Earth™ aided earth-flow susceptibility model: a test in central Sicily , 2012, Natural Hazards.
[36] Christian Conoscenti,et al. The role of the diagnostic areas in the assessment of landslide susceptibility models: a test in the sicilian chain , 2011 .
[37] Peter M. Atkinson,et al. Autologistic modelling of susceptibility to landsliding in the Central Apennines, Italy , 2011 .
[38] Norman Kerle,et al. Object-based gully feature extraction using high spatial resolution imagery , 2011 .
[39] Peter Lehmann,et al. Spatial statistical modeling of shallow landslides—Validating predictions for different landslide inventories and rainfall events , 2011 .
[40] Farrokh Nadim,et al. Statistical modelling of Europe-wide landslide susceptibility using limited landslide inventory data , 2012, Landslides.
[41] T. Groen,et al. Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling , 2011 .
[42] M. Seta,et al. Landslide susceptibility assessment in the Upper Orcia Valley (Southern Tuscany, Italy) through conditional analysis: A contribution to the unbiased selection of causal factors , 2011 .
[43] D. Costanzo,et al. Slope units-based flow susceptibility model: using validation tests to select controlling factors , 2012, Natural Hazards.
[44] Vicki G. Moon,et al. Comparison of bivariate and multivariate statistical approaches in landslide susceptibility mapping at a regional scale , 2012 .
[45] F. Guzzetti,et al. Landslide inventory maps: New tools for an old problem , 2012 .
[46] C. Irigaray,et al. Factors selection in landslide susceptibility modelling on large scale following the gis matrix method: application to the river Beiro basin (Spain) , 2012 .
[47] Boris Schröder,et al. How can statistical models help to determine driving factors of landslides , 2012 .
[48] Á. Felicísimo,et al. Mapping landslide susceptibility with logistic regression, multiple adaptive regression splines, classification and regression trees, and maximum entropy methods: a comparative study , 2013, Landslides.
[49] C. Irigaray,et al. Forward logistic regression for earth-flow landslide susceptibility assessment in the Platani river basin (southern Sicily, Italy) , 2014, Landslides.
[50] M. Becht,et al. Sample size matters: investigating the effect of sample size on a logistic regression susceptibility model for debris flows , 2014 .
[51] Mustafa Neamah Jebur,et al. Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale , 2014 .
[52] S. Pascale,et al. Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy) , 2014 .
[53] E. Rotigliano,et al. A test of transferability for landslides susceptibility models under extreme climatic events: application to the Messina 2009 disaster , 2014, Natural Hazards.
[54] Biswajeet Pradhan,et al. Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree , 2016, Landslides.
[55] E. Rotigliano,et al. Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice River basin (western Sicily, Italy) , 2015 .
[56] Luigi Borrelli,et al. Shallow landslides triggered by consecutive rainfall events at Catanzaro strait (Calabria–Southern Italy) , 2015 .
[57] Alexander Brenning,et al. Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling , 2015, Comput. Geosci..
[58] E. Rotigliano,et al. Using topographical attributes to evaluate gully erosion proneness (susceptibility) in two mediterranean basins: advantages and limitations , 2015, Natural Hazards.
[59] E. Rotigliano,et al. Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messina (Sicily, southern Italy) , 2015, Natural Hazards.
[60] E. Rotigliano,et al. Predicting storm-triggered debris flow events: application to the 2009 Ionian Peloritan disaster (Sicily, Italy) , 2015 .
[61] Deo Raj Gurung,et al. Abe Barek landslide and landslide susceptibility assessment in Badakhshan Province, Afghanistan , 2015, Landslides.