Investigating causal factors of shallow landslides in grassland regions of Switzerland
<p>Mountainous grassland slopes can be severely affected by soil erosion, among which shallow landslides are a crucial process, indicating instability of slopes. We determine the locations of shallow landslides across different sites to better understand regional differences and to identify th...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/aa72bfc3be2e439092c341b04df9c897 |
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| Sumario: | <p>Mountainous grassland slopes can be severely affected by soil erosion, among
which shallow landslides are a crucial process, indicating instability of
slopes. We determine the locations of shallow landslides across different
sites to better understand regional differences and to identify their
triggering causal factors. Ten sites across Switzerland located in the Alps
(eight sites), in foothill regions (one site) and the Jura Mountains (one site) were
selected for statistical evaluations. For the shallow-landslide inventory, we
used aerial images (0.25 <span class="inline-formula">m</span>) with a deep learning approach (U-Net) to map the
locations of eroded sites. We used logistic regression with a group lasso
variable selection method to identify important explanatory variables for
predicting the mapped shallow landslides. The set of variables consists of
traditional susceptibility modelling factors and climate-related factors to
represent local as well as cross-regional conditions. This set of explanatory
variables (predictors) are used to develop individual-site models (local
evaluation) as well as an all-in-one model (cross-regional evaluation) using
all shallow-landslide points simultaneously. While the local conditions of the
10 sites lead to different variable selections, consistently slope and aspect
were selected as the essential explanatory variables of shallow-landslide
susceptibility. Accuracy scores range between 70.2 % and 79.8 <span class="inline-formula">%</span> for individual
site models. The all-in-one model confirms these findings by selecting slope,
aspect and roughness as the most important explanatory variables
(accuracy <span class="inline-formula">=</span> 72.3 <span class="inline-formula">%</span>). Our findings suggest that traditional susceptibility
variables describing geomorphological and geological conditions yield
satisfactory results for all tested regions. However, for two sites with lower
model accuracy, important processes may be under-represented with the
available explanatory variables. The regression models for sites with an
east–west-oriented valley axis performed slightly better than models for
north–south-oriented valleys, which may be due to the influence of exposition-related processes. Additionally, model performance is higher for alpine sites,
suggesting that core explanatory variables are understood for these areas.</p> |
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