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Landslide Susceptibility Mapping using Relative Frequency and Predictor Rate along Araniko Highway
Abstract Roads are important infrastructure that brings economic development in a nation by connecting different places. But, in Nepal, many roads are very vulnerable to landslides due to various reasons. Araniko Highway is one of the most landslide affected major road in Nepal lacking study in past. In this study, landslide susceptibility mapping along Dolalghat - Kodari section in Araniko Highway, Nepal, was done by integrating Relative Frequency (RF) and Predictor Rate (PR). PR was applied to the RF to quantify the prediction ability of the conditioning factors while producing Landslide Susceptibility Index (LSI). First, landslide inventory map of 314 landslides was prepared. Then, the database was divided into 70/30 ratio for the training and validating the model. After analysing thirteen landslide conditioning factors, susceptibility map produced using LSI was categorized into five classes. Finally, overall performance of the resulting map was assessed using the receiver operating characteristic curve technique. The success rate and prediction rate curve showed that the area under the curve for RF was 0.606 and 0.581 respectively. The result of this study showed a successful mapping of landslide susceptibility by integrating RF and PR.
Landslide Susceptibility Mapping using Relative Frequency and Predictor Rate along Araniko Highway
Abstract Roads are important infrastructure that brings economic development in a nation by connecting different places. But, in Nepal, many roads are very vulnerable to landslides due to various reasons. Araniko Highway is one of the most landslide affected major road in Nepal lacking study in past. In this study, landslide susceptibility mapping along Dolalghat - Kodari section in Araniko Highway, Nepal, was done by integrating Relative Frequency (RF) and Predictor Rate (PR). PR was applied to the RF to quantify the prediction ability of the conditioning factors while producing Landslide Susceptibility Index (LSI). First, landslide inventory map of 314 landslides was prepared. Then, the database was divided into 70/30 ratio for the training and validating the model. After analysing thirteen landslide conditioning factors, susceptibility map produced using LSI was categorized into five classes. Finally, overall performance of the resulting map was assessed using the receiver operating characteristic curve technique. The success rate and prediction rate curve showed that the area under the curve for RF was 0.606 and 0.581 respectively. The result of this study showed a successful mapping of landslide susceptibility by integrating RF and PR.
Landslide Susceptibility Mapping using Relative Frequency and Predictor Rate along Araniko Highway
Acharya, Tri Dev (author) / Lee, Dong Ha (author)
KSCE Journal of Civil Engineering ; 23 ; 763-776
2018-12-17
14 pages
Article (Journal)
Electronic Resource
English
Landslide Susceptibility Mapping using Relative Frequency and Predictor Rate along Araniko Highway
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