Brief Communication: AI-driven rapid landslides mapping following the 2024 Hualien City Earthquake in Taiwan

On April 2nd, 2024, a Mw 7.4 earthquake struck Taiwan's eastern coast, triggering numerous landslides and severely impacting infrastructure. To create a preliminary inventory of the earthquake-induced landslides in Eastern Taiwan (~3,300 km²) we deployed automated landslide detection methods by combining Earth Observation (EO) data with Artificial Intelligence models. The models identified ~7,090 landslide events covering >75 km\textsuperscript{2}, in $\approx$ 3 hours after the acquisition of the EO imagery. This research showcase AI’s role for rapid landslide detection for disaster response. The generated landslide inventory can also be used to improve the understanding of earthquake-landslide interactions to improve seismic hazard mitigation.

Publication Details

Journal
Apollo (University of Cambridge)
Published
2025-04-29
DOI
https://doi.org/10.17863/cam.117785
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
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article

Brief Communication: AI-driven rapid landslides mapping following the 2024 Hualien City Earthquake in Taiwan

Apollo (University of Cambridge)
Landslides and related hazards
article

Brief Communication: AI-driven rapid landslides mapping following the 2024 Hualien City Earthquake in Taiwan

article en

Abstract

On April 2nd, 2024, a Mw 7.4 earthquake struck Taiwan's eastern coast, triggering numerous landslides and severely impacting infrastructure. To create a preliminary inventory of the earthquake-induced landslides in Eastern Taiwan (~3,300 km²) we deployed automated landslide detection methods by combining Earth Observation (EO) data with Artificial Intelligence models. The models identified ~7,090 landslide events covering >75 km\textsuperscript{2}, in $\approx$ 3 hours after the acquisition of the EO imagery. This research showcase AI’s role for rapid landslide detection for disaster response. The generated landslide inventory can also be used to improve the understanding of earthquake-landslide interactions to improve seismic hazard mitigation.

Apollo (University of Cambridge)
Climate action
Openalex Percentile: Top 44%
Landslides and related hazards
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