Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/183482
Title: FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides
Author: Guo, Zizheng
Torra, Ona
Hürlimann, Marcel
Abancó i Martínez de Arenzana, Clàudia
Medina, Vicente
Keywords: Esllavissades
Inundacions
Pirineus
Landslides
Floods
Pyrenees
Issue Date: 6-Feb-2022
Publisher: Elsevier B.V.
Abstract: Shallow slope failures triggered by rainfall commonly pose considerable risks in mountainous areas. In order to delineate areas where landslides are more prone to occur within a region, we have designed and developed a Python QGIS plugin named Fast Shallow Landslide Assessment Model (FSLAM). The plugin integrates a simplified hydrological model and a geotechnical model based on the infinite slope theory and contains two principal modules: runoff and slope stability modelling. It can output up to 15 raster maps describing the hydrological and stability conditions in a short computational time. Firstly, we explain the design of graphical user interface and the elements of the plugin. Then, the Berguedà area in NE Spain is used as case study to present the procedure of the plugin application. The results show that the accuracy of landslide susceptibility assessment performed by FSLAM-plugin is high and the computing time is only a few minutes.
Note: Versió postprint del document publicat a: https://doi.org/10.1016/j.envsoft.2022.105354
It is part of: Environmental Modelling & Software, 2022, vol. 150, num. 105354
URI: http://hdl.handle.net/2445/183482
Related resource: https://doi.org/10.1016/j.envsoft.2022.105354
ISSN: 1364-8152
Appears in Collections:Articles publicats en revistes (Mineralogia, Petrologia i Geologia Aplicada)

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