Soltanpour, Heidieh, Serrhini, Kamal, Gill, Joel C.  ORCID: https://orcid.org/0000-0002-8721-863X, Fuchs, Sven and Mohadjer, Solmaz
2026.
Multi-hazard susceptibility mapping in a karst context using a machine learning method (MaxEnt).
Natural Hazards and Earth System Sciences
26
, pp. 2743-2763.
10.5194/nhess-26-2743-2026
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Official URL: https://doi.org/10.5194/nhess-26-2743-2026
Abstract
In this study, we extend the application of the Maximum Entropy model (MaxEnt), traditionally applied to ecological research and less explored in natural hazard studies, to a novel context by characterising a multi-hazard scenario (i.e., flood-triggered sinkholes) in the Orléans karst region (Val d'Orléans) of France. Many regions of the world exhibit complex hazard landscapes where networks of multi-hazard interrelationships (cascades) pose challenges due to the potential interactions between hazards and the different temporal and spatial scales of hazard events...
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Earth and Environmental Sciences |
| Publisher: | Copernicus Publications |
| ISSN: | 1561-8633 |
| Date of First Compliant Deposit: | 28 May 2026 |
| Date of Acceptance: | 28 April 2026 |
| Last Modified: | 02 Aug 2026 01:17 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/187251 |
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