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Erschienen in: Environmental Earth Sciences 5/2013

01.03.2013 | Original Article

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

verfasst von: Soyoung Park, Chuluong Choi, Byungwoo Kim, Jinsoo Kim

Erschienen in: Environmental Earth Sciences | Ausgabe 5/2013

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Abstract

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).

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Metadaten
Titel
Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea
verfasst von
Soyoung Park
Chuluong Choi
Byungwoo Kim
Jinsoo Kim
Publikationsdatum
01.03.2013
Verlag
Springer-Verlag
Erschienen in
Environmental Earth Sciences / Ausgabe 5/2013
Print ISSN: 1866-6280
Elektronische ISSN: 1866-6299
DOI
https://doi.org/10.1007/s12665-012-1842-5

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