Landslide topology uncovers failure movements.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
25 Mar 2024
25 Mar 2024
Historique:
received:
19
04
2023
accepted:
08
03
2024
medline:
26
3
2024
pubmed:
26
3
2024
entrez:
26
3
2024
Statut:
epublish
Résumé
The death toll and monetary damages from landslides continue to rise despite advancements in predictive modeling. These models' performances are limited as landslide databases used in developing them often miss crucial information, e.g., underlying movement types. This study introduces a method of discerning landslide movements, such as slides, flows, and falls, by analyzing landslides' 3D shapes. By examining landslide topological properties, we discover distinct patterns in their morphology, indicating different movements including complex ones with multiple coupled movements. We achieve 80-94% accuracy by applying topological properties in identifying landslide movements across diverse geographical and climatic regions, including Italy, the US Pacific Northwest, Denmark, Turkey, and Wenchuan in China. Furthermore, we demonstrate a real-world application on undocumented datasets from Wenchuan. Our work introduces a paradigm for studying landslide shapes to understand their underlying movements through the lens of landslide topology, which could aid landslide predictive models and risk evaluations.
Identifiants
pubmed: 38528016
doi: 10.1038/s41467-024-46741-7
pii: 10.1038/s41467-024-46741-7
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2633Informations de copyright
© 2024. The Author(s).
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