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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2016.1
- 수록면
- 117 - 136 (20page)
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초록· 키워드
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For the purpose of comparing susceptibility mapping methods in Mizunami City, Japan, the landslide inventory was partitioned into three groups as various training and test datasets to identify the most appropriate method for creating a landslide susceptibility map. A total of fifteen landslide susceptibility maps were produced using frequency ratio, logistic regression, decision tree, weights of evidence and artificial neural network models, and the results were assessed using existing test landside points and areas under the relative operative characteristic curve (AUC). The validation results indicated that the logistic regression model could provide the highest AUC value (0.865), and a relatively high percentage of landslide points fell in the high and very high landslide susceptibility classes in this study. Furthermore, the paper also suggested that the model performances would be increased if appropriate landslide points were used for the calculation.
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등록된 정보가 없습니다.
참고문헌 (38)
참고문헌 신청
Ayalew, L. / 2005 / The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakudayahiko Mountains, Central Japan / Geomorphology 65:15~31
Omar F. Althuwaynee / 2014 / A novel ensemble bivariate statistical evidential belief function with knowledge-based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping / CATENA 114:21~36
Bai, S. B. / 2010 / GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the Three Gorgesarea, China / Geomorphology 115:23~31
Dieu Tien Bui / 2012 / Landslide susceptibility assessment in the Hoa Binh province of Vietnam: A comparison of the Levenberg–Marquardt and Bayesian regularized neural networks / Geomorphology 171-172:12~29
Massimo Conforti / 2014 / Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy) / CATENA 113:236~250
Omar F. Althuwaynee / 2014 / A novel ensemble bivariate statistical evidential belief function with knowledge-based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping / CATENA 114:21~36
Bai, S. B. / 2010 / GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the Three Gorgesarea, China / Geomorphology 115:23~31
Dieu Tien Bui / 2012 / Landslide susceptibility assessment in the Hoa Binh province of Vietnam: A comparison of the Levenberg–Marquardt and Bayesian regularized neural networks / Geomorphology 171-172:12~29
Massimo Conforti / 2014 / Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy) / CATENA 113:236~250
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