Landslide topology uncovers failure movements

Kushanav Bhuyan (), Kamal Rana (), Joaquin V. Ferrer, Fabrice Cotton, Ugur Ozturk, Filippo Catani and Nishant Malik
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Kushanav Bhuyan: University of Padova
Kamal Rana: Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
Joaquin V. Ferrer: University of Potsdam
Fabrice Cotton: Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
Ugur Ozturk: Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
Filippo Catani: University of Padova
Nishant Malik: Rochester Institute of Technology

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract 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.

Date: 2024
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DOI: 10.1038/s41467-024-46741-7

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