A QGIS framework for physically-based probabilistic modelling of landslide susceptibility: QGIS-FORM
Earthquake-induced regional landslides frequently result in substantial economic losses and casualties. Conducting landslide susceptibility assessments is essential for mitigating these risks and minimizing potential damage. To address the diverse needs of professionals in various disciplines, we ha...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/421136 |
| Acceso en línea: | https://hdl.handle.net/2117/421136 https://dx.doi.org/10.1016/j.envsoft.2024.106258 |
| Access Level: | acceso abierto |
| Palabra clave: | Landslide susceptibility Slope stability QGIS Physically-based model Probability of failure First order reliability method (FORM) Àrees temàtiques de la UPC::Enginyeria civil::Geotècnia::Mecànica de sòls |
| Sumario: | Earthquake-induced regional landslides frequently result in substantial economic losses and casualties. Conducting landslide susceptibility assessments is essential for mitigating these risks and minimizing potential damage. To address the diverse needs of professionals in various disciplines, we have developed an open-source plugin for QGIS, named QGIS-FORM. This plugin integrates functions of both physically-based model (PM) and physically-based probabilistic model (PPM). The PM employs pseudo-static infinite slope stability model, while the PPM utilizes an improved first order reliability method (FORM) to perform landslide probability analysis over a spatial region. To verify its effectiveness, the plugin was applied to the Maerkang landslide event in 2022. Based on the PM and the PPM, the landslide susceptibility assessments were evaluated using several parameters including slope, aspect, stratum, and PGA. In addition, the Receiver Operating Characteristic (ROC) curve and Balanced Accuracy were employed to assess their predictive performance. The landslide susceptibility results indicate that landslides in Maerkang are mostly concentrated in slopes between 30° and 50°, and the geological conditions of the Xinduqiao Formation (T_3X) are more prone to landslides. Compared to PM, the PPM can achieve higher AUC values when the parameter uncertainties are properly characterized. Overall, the PPM exhibits higher accuracy and is more capable of identifying potential landslides than the physically-based model, thereby providing a more reliable way and/or offering a scientific basis for the management and mitigation of landslide disaster risks. |
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