Articles | Volume 7, issue 6
https://doi.org/10.5194/gmd-7-2969-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-2969-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
15 Dec 2014
Development and technical paper |
| 15 Dec 2014
A strategy for GIS-based 3-D slope stability modelling over large areas
Institute of Applied Geology, BOKU University, Vienna, Austria
I. Marchesini
CNR-IRPI, Perugia, Italy
M. Alvioli
CNR-IRPI, Perugia, Italy
M. Metz
Fondazione Edmund Mach, San Michele all'Adige, Italy
B. Schneider-Muntau
Division of Geotechnical and Tunnel Engineering, University of Innsbruck, Innsbruck, Austria
CNR-IRPI, Perugia, Italy
Department of Geosciences, University of Perugia, Perugia, Italy
F. Guzzetti
CNR-IRPI, Perugia, Italy
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- INSPIRE standards as a framework for artificial intelligence applications: a landslide example G. Roberti et al. 10.5194/nhess-20-3455-2020
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- A review of statistically-based landslide susceptibility models P. Reichenbach et al. 10.1016/j.earscirev.2018.03.001
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Latest update: 01 Apr 2023
Short summary
The article deals with strategies to (i) reduce computation time and to (ii) appropriately account for uncertain input parameters when applying an open source GIS sliding surface model to estimate landslide susceptibility for a 90km² study area in central Italy. For (i), the area is split into a large number of tiles, enabling the exploitation of multi-processor computing environments. For (ii), the model is run with various parameter combinations to compute the slope failure probability.
The article deals with strategies to (i) reduce computation time and to (ii) appropriately...
