Estimating global landslide susceptibility and  its uncertainty through ensemble modeling

Felsberg, Anne; Poesen, Jean; Bechtold, Michel; Vanmaercke, Matthias; De Lannoy, Gabriëlle J. M.

doi:https://doi.org/10.5194/nhess-22-3063-2022

Articles | Volume 22, issue 9

https://doi.org/10.5194/nhess-22-3063-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-22-3063-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 9

Research article

|

19 Sep 2022

Research article |

| 19 Sep 2022

Estimating global landslide susceptibility and its uncertainty through ensemble modeling

Anne Felsberg, Jean Poesen, Michel Bechtold, Matthias Vanmaercke, and Gabriëlle J. M. De Lannoy

Data sets

Ensemble of global landslide susceptibility A. Felsberg, G. J. M. De Lannoy, J., Poesen, M. Bechtold, M., and M. Vanmaercke https://doi.org/10.5281/zenodo.6893230

Global Topographic 30 Arc-Second Hydrologic Digital Elevation Model 1 Km EROS https://doi.org/10.5066/F77P8WN0

FraneItalia: A Catalog of Recent Italian Landslides (Version 2.0) M. Calvello and G. Pecoraro https://doi.org/10.17632/zygb8jygrw.2

Short summary

In this study we assessed global landslide susceptibility at the coarse 36 km spatial resolution of global satellite soil moisture observations to prepare for a subsequent combination of the two. Specifically, we focus therefore on the susceptibility of hydrologically triggered landslides. We introduce ensemble techniques, common in, for example, meteorology but not yet in the landslide community, to retrieve reliable estimates of the total prediction uncertainty.