Satellite remote sensing is crucial for monitoring volcanic sulfur dioxide (SO<sub>2</sub>) globally. However, the rapid evolution of volcanic plumes necessitates high-frequency observations, which typical twice-daily overpasses of Low Earth Orbit (LEO) sensors fail to capture. To address this limitation, this study presents a synergistic Geostationary Earth Orbit (GEO) and LEO observation framework. Specifically, we show the first quantitative SO<sub>2</sub> retrieval from a GEO hyperspectral infrared sounder (FY-4B/GIIRS), using an optimal-estimation-based retrieval algorithm. Because current and upcoming GEO infrared sounders lack the strong <em>ν</em>3 absorption band, our algorithm uniquely leverages the weaker <em>ν</em>1 absorption band. Simulation experiments indicate that the detection limit (retrieval error > 100 %) is 3 DU for plumes at 10 km altitude. During the June 2024 Kanlaon eruption, GIIRS captured early, high-concentration plume dynamics, though tracking diluted plumes remained challenging. Crucially, it provided the earliest satellite detection by continuously monitoring the initial nighttime burst (posterior error of 53.7 ± 24.1 %), filling critical temporal gaps left by ultraviolet sensors. Combined with LEO (HIRAS, IASI, CrIS, TROPOMI and MLS) and GEO sensor (GEMS), the synergistic framework achieved high frequency quantification of SO<sub>2</sub> mass loading and transport pathways. We estimated a peak SO<sub>2</sub> mass loading of ∼40 kt and an e-folding time of 5.2 ± 0.5 days. Furthermore, multi-platform observations identified significant discrepancies in the CAMS global model regarding the plume's evolution and magnitude. This geostationary-driven synergistic framework delivers high-fidelity observational records, establishing a robust basis for monitoring moderate-scale volcanic events and evaluating atmospheric chemical transport models.