The application of geospatial technologies and space-based systems has transformed disaster risk management by improving prediction, preparedness, response, and recovery mechanisms. Recent advancements in geoinformatics, remote sensing, Geographic Information Systems (GIS), Global Navigation Satellite Systems (GNSS), and satellite communication have enabled more accurate assessment of hazards and vulnerabilities. Emerging trends in these technologies are strengthening decision-making processes and reducing disaster-related losses. Artificial Intelligence (AI) and Machine Learning (ML) are among the latest trends in geoinformatics for disaster management. These technologies analyze large volumes of satellite imagery, climate data, and sensor information to identify patterns and predict disaster events. AI-based models can detect changes in land use, forecast floods, identify wildfire risks, and estimate the potential impact of extreme weather events. Machine learning algorithms improve the accuracy and speed of hazard mapping and early warning systems. The integration of