Landslide susceptibility assessment along the major transport corridor using decision tree model: a case study of Kullu-Rohtang Pass
- Publisher:
- Inderscience Publishers
- Publication Type:
- Journal Article
- Citation:
- International Journal of Business Intelligence and Data Mining, 2023, 24, (1), pp. 1-24
- Issue Date:
- 2023-12-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| nirbhav-et-al-2023-landslide-susceptibility-assessment-along-the-major-transport-corridor-using-decision-tree-model-a.pdf | Published version | 1.94 MB |
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To lessen damages from landslides, the key challenge is to predict the events precisely and accurately. The objective of this study is to assess landslide susceptibility in the study area. To achieve this objective, a detailed landslide inventory has been prepared based on imagery data and frequent field visits of 153 rock slides and 44 debris slides. Nine landslide factors were prepared initially and their relationships with each other and with the type of landslide was analysed. Information gain ratio measure is used to eliminate triggering factors with least score. Train_test_split method was used to classify the dataset into training and testing groups. Decision tree classification model of machine learning was applied for landslide susceptibility model (LSM). The performance was evaluated using classification report and receiver operating characteristic (ROC) curve. Results obtained have proven that the decision tree classification model performed well with good accuracy in forecasting landslide susceptibility.
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