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Abstract:
The death toll andmonetary 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.
