Abstract: The upper reaches of the Jinsha River are characterized by active geological tectonics and intense topographic incision, resulting in an extremely high risk of landslides and induced chain disasters that seriously threaten regional safety. Traditional emergency models often face challenges such as scattered data, difficult fusion, lagging judgment, insufficient warning timeliness, and weak support when dealing with watershed-scale disasters. To address these issues, an early warning and emergency platform for watershed landslides based on multi-source information fusion was independently developed. This platform integrates “Space-Air-Ground” integrated monitoring data with geological and hydrological background information. It constructs a full-chain technical system covering data aggregation and governance, dynamic real-time monitoring, risk evolution assessment, intelligent prediction and early warning, and emergency response. Application verification on typical landslides in the upper Jinsha River indicates that the platform effectively achieves deep mining of multi-source heterogeneous data. It significantly enhances the early identification capability and warning timeliness for potential unstable areas, providing a scientific and intuitive decision-making basis for cross-departmental collaborative emergency response.