Integrating Multi-source Data for Landslide-dammed Lake Emergency Response: From Geomorphic Monitoring to Dynamic Exposure Assessment.

On April 3, 2024, an earthquake of Richter local magnitude (ML) 7.2 struck eastern Taiwan, centered near Shoufeng Township, Hualien County. The maximum intensity reached level 6+, recorded in the Heping area.The resulting geological instability was subsequently mobilised by the hydrometeorological impacts of Typhoon Wipha in July 2025. On July 25, a massive slope failure—estimated at approximately 290 million m³—occurred in the upper reaches of the Mataian River (TWD97/TM2 zone 121 coordinate system; EPSG:3826; X: 280138, Y: 2621774). This event formed a large-scale landslide-dammed lake with a dam height of 200 m and a potential storage capacity of 91 million m³. The lake was first identified by satellite monitoring on 26 July, prompting an immediate multi-agency emergency response.During the response, rapid engineering-geomorphological interpretation of the landslide source area and dam morphology was used to define priorities for subsequent monitoring and breach-scenario analysis. We present an integrated GIS-based decision-support framework designed to connect research outputs with time-critical disaster management. The workflow uses multi-temporal Sentinel-1 (SAR) and Sentinel-2 (optical) imagery to track dam–lake evolution and geomorphic change, and it cross-validates remote-sensing interpretation with real-time water-level observations from an in situ gauge installed by a National Cheng Kung University team. For downstream hazard assessment, the PRISM platform (The Indigenous Platform for Risk Information and Safety Management, PRISM) ingests independent hydraulic simulations provided by National Taiwan University and National Yang Ming Chiao Tung University to build plausible breach-inundation scenarios. By spatially intersecting simulated flood extents with address-level geocoded household data, we identify 1,837 threatened households. In addition, telecom signalling population statistics enable dynamic exposure estimates for 8,000 individuals within the risk zone, supporting evacuation prioritisation and providing a high-fidelity basis for evacuation decisions. This case study demonstrates how multi-source Earth-observation and population-scale data streams can be operationalised to manage post-earthquake cascading hazards from landslide dams, and highlights the indispensable role of multi-source data integration in mitigating complex, post-seismic cascading hazards.