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Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea

Park, Soyoung ; Choi, Chuluong ; Kim, Byungwoo ; Kim, Jinsoo

Environmental earth sciences, 2013-03, Vol.68 (5), p.1443-1464 [Periódico revisado por pares]

Berlin/Heidelberg: Springer-Verlag

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Título:
Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea
Autor: Park, Soyoung ; Choi, Chuluong ; Kim, Byungwoo ; Kim, Jinsoo
Assuntos: Biogeosciences ; Earth and Environmental Science ; Earth Sciences ; Earth, ocean, space ; Engineering and environment geology. Geothermics ; Environmental Science and Engineering ; Exact sciences and technology ; Geochemistry ; Geology ; Hydrology/Water Resources ; landslides ; Landslides & mudslides ; Mapping ; Natural hazards: prediction, damages, etc ; Neural networks ; Original Article ; Regression analysis ; Terrestrial Pollution
É parte de: Environmental earth sciences, 2013-03, Vol.68 (5), p.1443-1464
Notas: http://dx.doi.org/10.1007/s12665-012-1842-5
ObjectType-Article-1
SourceType-Scholarly Journals-1
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Descrição: Every year, the Republic of Korea experiences numerous landslides, resulting in property damage and casualties. This study compared the abilities of frequency ratio (FR), analytic hierarchy process (AHP), logistic regression (LR), and artificial neural network (ANN) models to produce landslide susceptibility index (LSI) maps for use in predicting possible landslide occurrence and limiting damage. The areas under the relative operating characteristic (ROC) curves for the FR, AHP, LR, and ANN LSI maps were 0.794, 0.789, 0.794, and 0.806, respectively. Thus, the LSI maps developed by all the models had similar accuracy. A cross-tabulation analysis of landslide occurrence against non-occurrence areas showed generally similar overall accuracies of 65.27, 64.35, 65.51, and 68.47 % for the FR, AHP, LR, and ANN models, respectively. A correlation analysis between the models demonstrated that the LR and ANN models had the highest correlation (0.829), whereas the FR and AHP models had the lowest correlation (0.619).
Editor: Berlin/Heidelberg: Springer-Verlag
Idioma: Inglês

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Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea

Park, Soyoung ; Choi, Chuluong ; Kim, Byungwoo ; Kim, Jinsoo

Berlin/Heidelberg: Springer-Verlag

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