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EnglishIn this work a data-driven methodology for shallow landslide susceptibility assessment is presented. The procedure is based on the Generalized Additive Model (Hastie and Tibshirani, 1990) and it is developed to be applied in different contexts, using terrain attributes, land use and lithological data. The application of the method in three different contexts in Italy shows the good forecasting capability of the model. The implementation of this method allows for building landslide susceptibility maps, which are a fundamental basis in hazard and risk assessment.
| Titolo: | Developing and testing a data-driven methodology for shallow landslide susceptibility assessment: Preliminary results |
| Autori: | |
| Data di pubblicazione: | 2015 |
| Rivista: | |
| Abstract: | In this work a data-driven methodology for shallow landslide susceptibility assessment is presented. The procedure is based on the Generalized Additive Model (Hastie and Tibshirani, 1990) and it is developed to be applied in different contexts, using terrain attributes, land use and lithological data. The application of the method in three different contexts in Italy shows the good forecasting capability of the model. The implementation of this method allows for building landslide susceptibility maps, which are a fundamental basis in hazard and risk assessment. |
| Handle: | http://hdl.handle.net/11567/817559 |
| Appare nelle tipologie: | 01.01 - Articolo su rivista |
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