| Modeling the potential distribution of shallow-seated landslides using the weights of evidence method and a logistic regression model： a case study of the Sabae Area, Japan |
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| 作者单位： | Department of Soil and Water Conservation Forestry and Forest Products Research Institute，Ibaraki 305-8687，Japan，Head，College of Bioresource Sciences，Nihon University，Kanagawa 252-8510，Japan，Prof，Department of Soil and Water Conservation，Forestry and Forest Products Research Institute，Ibaraki 305-8687，Japan，Senior Researcher，Department of Soil and Water Conservation，Forestry and Forest Products Research Institute，Ibaraki 305-8687，Japan，Chief |
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| 基金项目： | Acknowledgments This research was financially supported by JSPS （the Japan Society for the Promotion of Science） Postdoctoral Fellowship Program for Foreign Researchers （04587）, and the Forestry and Forest Products Research Institute. We are also grateful to Yoshitsugu Takeuchi and Kanji Mizutani of the Forestry and Forest Products Research Institute, Japan for their support. |
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| 摘 要： | A number of statistical methods are typically used to effectively predict potential landslide distributions. In this study two multivariate statistical analysis methods were used （weights of evidence and logistic regression） to predict the potential distribution of shallow-seated landslides in the Kamikawachi area of Sabae City, Fukui Prefecture, Japan. First, the dependent variable （shallow-seated landslides） was divided into presence and absence, and the independent variables （environmental factors such as slope and altitude） were categorized according to their characteristics. Then, using the weights of evidence （WE） method, the weights of pairs comprising presence （w^＋（i）） or absence （w^-（i））, and the contrast values for each category of independent variable （evidence）, were calculated, Using the method that integrated the weights of evidence method and a logistic regression model, score values were calculated for each category of independent variable. Based on these contrast values, three models were selected to sum the score values of every gird in the study area. According to a receiver operating characteristic curve analysis （ROC）, model 2 yielded the best fit for predicting the potential distribution of shallow-seated landslide hazards, with 89% correctness and a 54.5% hit ratio when the occurrence probability （OP） of landslides was 70%. The model was tested using data from an area close to the study region, and showed 94% correctness and a hit ratio of 45.7% when the OP of landslides was 70%. Finally, the potential distribution of shallow-seated landslides, based on the OP, was mapped using a geographical information system.
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| 关 键 词： | 后勤回归模型 ROC曲线分析 滑坡 分布区域 |
| 收稿时间： | 1 July 2007 |
Modeling the potential distribution of shallow-seated landslides using the weights of evidence method and a logistic regression model:a case study of the Sabae Area, Japan |
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| Authors: | Ru-Hua SONG Daimaru HIROMU Abe KAZUTOKI Kurokawa USIO Matsuura SUMIO |
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| Institution: | [1]Chinese Society of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China [2]Head Department of Soil and Water Conservation, Forestry and Forest Products Research Institute, Ibaraki 305-8687, Japan [3]College of Bioresource Sciences, Nihon University, Kanagawa 252-8510, Japan [4]Senior Researcher Department of Soil and Water Conservation, Forestry and Forest Products Research Institute, Ibaraki 305-8687, Japan [5]Chief Department of Soil and Water Conservation, Forestry and Forest Products Research Institute, Ibaraki 305-8687, Japan |
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| Abstract: | A number of statistical methods are typically used to effectively predict potential landslide distributions. In this study two multivariate statistical analysis methods were used (weights of evidence and logistic regression) to predict the potential distribution of shallow-seated landslides in the Kamikawachi area of Sabae City, Fukui Prefecture, Japan. First, the dependent variable (shallow-seated landslides) was divided into presence and absence, and the independent variables (environmental factors such as slope and altitude) were categorized according to their characteristics. Then, using the weights of evidence (WE) method, the weights of pairs comprising presence (w+(i)) or absence (w?(i)), and the contrast values for each category of independent variable (evidence), were calculated. Using the method that integrated the weights of evidence method and a logistic regression model, score values were calculated for each category of independent variable. Based on these contrast values, three models were selected to sum the score values of every gird in the study area. According to a receiver operating characteristic curve analysis (ROC), model 2 yielded the best fit for predicting the potential distribution of shallow-seated landslide hazards, with 89% correctness and a 54.5% hit ratio when the occurrence probability (OP) of landslides was 70%. The model was tested using data from an area close to the study region, and showed 94% correctness and a hit ratio of 45.7% when the OP of landslides was 70%. Finally, the potential distribution of shallow-seated landslides, based on the OP, was mapped using a geographical information system. |
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| Keywords: | Weights of evidence method Logistic regression model ROC curve analysis Landslides |
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