Articles | Volume 17, issue 7
https://doi.org/10.5194/nhess-17-1091-2017
https://doi.org/10.5194/nhess-17-1091-2017
Research article
 | 
10 Jul 2017
Research article |  | 10 Jul 2017

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

Sérgio C. Oliveira, José L. Zêzere, Sara Lajas, and Raquel Melo

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Cited articles

Aleotti, P. and Chowdhury, R.: Landslide hazard assessment: summary review and new perspectives, B. Eng. Geol. Environ., 58, 21–44, https://doi.org/10.1007/s100640050066, 1999.
Baptista, V.: Estudo das condições geológico-geotécnicas ocorrentes ao longo do sub-lanço Arruda dos Vinhos/Carregado da auto-estrada A10, Relatório de Estágio, Faculdade de Ciências da Universidade de Lisboa, Lisboa, Portugal, 81 pp., 2004.
Brenning, A.: Spatial prediction models for landslide hazards: review, comparison and evaluation, Nat. Hazards Earth Syst. Sci., 5, 853–862, https://doi.org/10.5194/nhess-5-853-2005, 2005.
Bui, D. T., Tuan, T. A., Klempe, H., Pradhan, B., and Revhaug, I.: 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, Landslides, 13, 361–378, https://doi.org/10.1007/s10346-015-0557-6, 2016.
Carrara, A., Cardinali, M., Detti, R., Guzzetti, F., Pasqui, V., and Reichenbach, P.: GIS techniques and statistical models in evaluating landslide hazard, Earth Surf. Proc. Land., 16, 427–445, 1991.
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Short summary
Approaches to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. Two hypotheses are tested: (i) both methods generate similar shallow slide susceptibility results and (ii) the combination of both susceptibility maps generates a more reliable susceptibility model. Model combinations registered a higher predictive capacity and the identification of areas where the results from both models are uncertain.
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