Skip to main content
zenodoopen

Ensemble of global landslide susceptibility

<p>This ensemble of global landslide susceptibility maps at a 36-km spatial resolution on the EASEv2 grid has been created through a combination of blocked random cross validation and predictor variable perturbation. In total, the ensemble has 2500 members, each obtained from a logistic regression equation with 5 predictor variables. Note that these predictor variables vary between ensemble members, as do the logistic regression parameters (study design of data-driven predictor variable selection with cross validation). For details, please see Felsberg, A., Poesen, J., Bechtold, M., Vanmaercke, M., and De Lannoy, G. J. M. (2022): Estimating global landslide susceptibility and its uncertainty through ensemble modelling, Natural Hazards and Earth System Sciences.</p> <p>Provided are the individual ensemble member maps (FelsbergEtAl2022_LSS_ensMemb_all.nc4c), as well as the ensemble average and standard deviation maps (FelsbergEtAl2022_LSS_ensavg.nc4c,&nbsp;FelsbergEtAl2022_LSS_ensstd.nc4c). More details can be found in the README.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

Dataset details

Repository
zenodo
Published
July 23, 2022
License
cc-by-4.0
DOI
10.5281/zenodo.6893229

Scored with release 0.9.0

ScienceDex for faculty

Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.