Brief communication: AI-driven rapid landslide mapping following the 2024 Hualien earthquake in Taiwan
<p>On 2 April 2024, a <span class="inline-formula"><i>M</i><sub>w</sub></span> 7.4 earthquake struck Taiwan's eastern coast, triggering numerous landslides and severely impacting infrastructure. To create a preliminary inventory of the earthqu...
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-07-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://nhess.copernicus.org/articles/25/2371/2025/nhess-25-2371-2025.pdf |
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| Summary: | <p>On 2 April 2024, a <span class="inline-formula"><i>M</i><sub>w</sub></span> 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 (3300 <span class="inline-formula">km<sup>2</sup></span>), we deployed automated landslide detection methods by combining Earth observation (EO) data with AI models. The models identified 7090 landslide events covering <span class="inline-formula">>75 km<sup>2</sup></span> within <span class="inline-formula">≈3 h</span> of the acquisition of the EO imagery. This research showcases AI's role in rapid landslide detection for disaster response. The landslide inventory generated can also be used to improve the understanding of earthquake–landslide interactions and thus improve seismic hazard mitigation.</p> |
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| ISSN: | 1561-8633 1684-9981 |