Brief communication: AI-driven rapid landslide mapping following the 2024 Hualien earthquake in Taiwan

Nava, Lorenzo ORCID: https://orcid.org/0000-0002-2327-8721; Novellino, Alessandro ORCID: https://orcid.org/0000-0001-9682-9056; Fang, Chengyong; Bhuyan, Kushanav ORCID: https://orcid.org/0000-0002-6173-8696; Leeming, Kathryn; Alvarez, Itahisa Gonzalez ORCID: https://orcid.org/0000-0002-4702-2800; Dashwood, Claire; Doward, Sophie; Chahel, Rahul ORCID: https://orcid.org/0009-0000-7040-5570; McAllister, Emma; Meena, Sansar Raj ORCID: https://orcid.org/0000-0001-6175-6491; Catani, Filippo ORCID: https://orcid.org/0000-0001-5185-4725. 2025 Brief communication: AI-driven rapid landslide mapping following the 2024 Hualien earthquake in Taiwan. Natural Hazards and Earth System Sciences, 25 (7). 2371-2377. 10.5194/nhess-2024-146

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Abstract/Summary

On April 2nd, 2024, a Mw 7.4 earthquake struck Taiwan’s eastern coast, triggering numerous landslides and severely impacting infrastructure. To create the preliminary inventory of earthquake-induced landslides in Eastern Taiwan ( 3,300 km2) we deployed automated landslide detection methods by combining Earth Observation (EO) data with Artificial Intelligence (AI) models. The models allowed us to 5 identify 7,090 landslide events covering >75 km2, in about 3 hours after the acquisition of the EO imagery. This research underscores AI’s role in enhancing landslide detection for disaster response and situational awareness, and the landslide inventory can improve the understanding of earthquake-landslide interactions to improve seismic hazard mitigation.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.5194/nhess-2024-146
ISSN:	15618633
Additional Keywords:	IGRD
Date made live:	24 Sep 2025 13:39 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/539015

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