FIGURE 29 VISUALIZATION EXAMPLE FROM EVENTS VISUALIZATION IN EMERGENCIES, SHOWING FLOOD PERSISTENCE ACROSS CROPLAND IN TARABA STATE, NIGERIA, OCTOBER 2024

population, livelihood profile). Additionally, hydrological hazards. Flood Hubis and Flood Forecasting's models from Google, for example, predictions in ungauged watersheds, fostering Monitoring (PRISM).2 PRISM integrates layers Decision-makers need quick, reliable and of climate hazard impacts on food security, sector. Risk and impact analysis requires a historical weather data, satellite imagery, and real-time meteorological inputs, from sensors socioeconomic factors, which is often missing, leading to incomplete assessments, particularly and IoT devices, to forecast weather events and to provide early warning alerts. Post-disaster satellite and drone imagery, combined with information systems. Adoption is also limited In collaboration with Google Research, WFP has developed SKAI, an AI and satellite imagery when data comes late, after critical decisions been made, or when the data is not granular at disaster response.94 Fusing cutting-edge the decision-making level (administrative level,