A giant two-stage landslide at Matai'an, Taiwan: insights from seismic source inversion and remote-sensing analysis
Year: 2026
Type: article
Abstract: The Matai'an landslide is the largest landslide event ever recorded in Taiwan, with an estimated volume of approximately 308 million m 3 . The failure resulted in the formation of a landslide dam, whose subsequent breach triggered a catastrophic flood, resulting in 19 fatalities, 5 missing persons, and 157 injuries. Multitemporal remote sensing analysis revealed obvious geomorphic precursor features prior to the landslide, with tensile cracking initiating and progressively developing following the 2024 Mw7.3 Hualien earthquake. Seismic source inversion analysis further indicated that the Matai'an landslide was composed of two distinct source events with different sliding directions, in which the second event predominantly involved westward motion. The two events occurred within 65 s. First, the slope collapsed, with an absolute maximum force magnitude (Fmax) of 1.995 × 10 12 N and a high sliding angle ( θ = 38.3°). Second, low-angle ( θ = 6.8°) sliding forces with an Fmax value of 0.908 × 10 12 N were resolved by seismic source inversion. This multisource failure mechanism led to stratified material deposition during landslide dam formation, a factor that critically influences the assessment of potential dam-breach mechanisms. By integrating multitemporal imagery with seismic waveform analysis, this study demonstrates that landslide-related geomorphic precursors can be detected prior to failure, while the landslide can be detected seismologically in near real time. Furthermore, the deployment of riverine seismic stations along downstream channels provides a viable approach for early warning of impending landslide-dam breach flooding.
Source: Landslides
Authors: Wei-An Chao, Che-Ming Yang
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,590
Awards: Geological Model Geomorphological Evolution, Hazard Analysis of Deep-Seated Landslide( II ), Artificial Intelligence of Environmental Seismology (Aioes): Monitoring of Earth Surface Processes with Ambient Noise and Image Data - Learning from Taiwan and Germany, and Applying to Vi Etnam, Application of Digital Technology Integration Techniques in Mountainous Road Disaster Prevention and Early Warning Systems( II ), River Sediment Observatory in the Mountainous Catchment: Long-Term High Spatiotemporal Monitoring with Distributed Acoustic Sensing (Das), Large-N Geophone Array, Hydrophone, Smart Rock, Ai-Grain-Size Scanner, and Photogrammetric Survey
OpenAlex ID: W7160203480