Introduction Intelligently determining the co-seismic landslide hazard is crucial for post-seismic risk assessment and disaster reduction management. Methods This study proposes an integrated emergency mitigation management system for co-seismic landslide hazard assessment and the rapid output of thematic maps at a national-scale. By integrating five key aspects of geo-environmental data—topography, active tectonics, land use, ground vibration, and rainfall, as well as co-seismic landslide samples associated with the nine identified seismic events in China between 1920 and 2024, a Trans-unit grid with regular points sampling method is developed and combine it with a gradient boosting decision tree binary classification prediction model to forecast and visualize co-seismic landslide hazard with 500 m spatial resolution accuracy in China. Furthermore, an ArcPy-based emergency script program is created to facilitate post-seismic landslide hazard management applications, including epicenter localization, hazard thematic maps, and the rapid generation of statistical information. Results Our results indicate that the distribution of co-seismic landslide hazard is primarily influenced by seismic tectonics. Areas with medium to high hazard probability degree are predominantly located in large active rupture zones, uplifted mountain systems, and along basin margins. Results The research findings provide scientific methods and technical support for pre-seismic hazard early warning in communities, as well as post-seismic emergency management aimed at mitigating and reducing landslide risks.
Gao et al. (Wed,) studied this question.