Landslide Susceptibility in Turkish Northewesternmost Sector: Distinctive Patterns of Inactive and Active Landslides
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F24%3A10486368" target="_blank" >RIV/00216208:11310/24:10486368 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-981-99-9061-0_44" target="_blank" >https://doi.org/10.1007/978-981-99-9061-0_44</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-981-99-9061-0_44" target="_blank" >10.1007/978-981-99-9061-0_44</a>
Alternative languages
Result language
angličtina
Original language name
Landslide Susceptibility in Turkish Northewesternmost Sector: Distinctive Patterns of Inactive and Active Landslides
Original language description
The Western Pontides, an active neo-tectonic region in Northwestern Turkey, are particularly rich in slope movements. Here, data-driven modelling is challenging owing to a prominent variability in geological and geomorphological features, which hinders a straightforward comprehension of ongoing and past processes. Statistical models can indeed be used to recognise portions of the landscape that are more susceptible to landslides, whereas inferring possible causation from spatial correlations with a number of other spatial characteristics typically requires knowledge of triggers and mechanisms. Here, we present results that we obtained using a dataset of active and relict landslides in the Western Pontides, for which we produced two distinct landslide susceptibility models. We subdivided the area in slope units, chich are geomorphologically consistent, and worked in R-INLA with a Bayesian version of binomial Generalised Additive Model. By doing so, we were able to evaluate the effect of the variables in the two models and identify effects of geomorphological factors that depend on the state of activity. Furthermore, we could describe and compare linearities and nonlinearities to better capture differences in spatial patterns possibly related to distinct triggers. We argue that our approach may also serve to assess the reliability of an inventory classification, as the presence of biases would make the emergence of distinctive patterns less likely.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10505 - Geology
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Engineering Geology for a Habitable Earth: IAEG XIV Congress 2023 Proceedings Vol. 2
ISBN
978-981-9990-60-3
ISSN
1863-5520
e-ISSN
1863-5539
Number of pages
16
Pages from-to
613-628
Publisher name
Springer - Verlag Singapore PTE Ltd
Place of publication
Singapore
Event location
Chengdu, China
Event date
Sep 21, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001315804700044