Publication Date:
2021-10-15
Description:
Abstract
Description:
The file corresponds to a code written using the R software version 4.0.5 (R Core Team, 2021). We used a Bayesian robust regression to predict the posterior probability P(L) at which a given location yi in our study areas (north Patagonia, Chile) is classified as part of a landslide source, transport, or deposition area.
We used the NUTS sampling scheme implemented in the STAN probabilistic programming language (Carpenter et al., 2017) to draw samples from the joint posterior distribution via the R package brms (Bürkner, 2017). We ran four independent Hamiltonian Monte Carlo chains based on 2000 iterations including 500 warm-up samples and checked each chain for convergence. We assessed the performance of this classifier based on its posterior predictive distribution and recorded the fraction of correct classifications compared to the observed frequency of landslides in all study areas and for all landform types.
We find that higher crown openness and wind speeds credibly predict higher probabilities of detecting landslides regardless of topographic location, though much better in low-order channels and on midslope locations than on open slopes. Wind speed has less predictive power in areas that were impacted by tephra fall from recent volcanic eruptions, while the influence of forest cover in terms of crown openness remains.
Description:
Other
Description:
Copyright (C) 2021 University Potsdam (Oliver Korup).
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Keywords:
Landslide prediction
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EARTH SCIENCE 〉 LAND SURFACE 〉 LANDSCAPE 〉 LANDSCAPE PROCESSES
;
EARTH SCIENCE SERVICES 〉 MODELS 〉 GEOLOGIC/TECTONIC/PALEOCLIMATE MODELS
Type:
Model
,
Model
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