Abstract
As climate change and extreme weather events increase, natural disasters’ frequency and intensity continue to rise worldwide. Traditional disaster prediction and prevention methods face numerous challenges regarding accuracy and response speed. This paper explores the cutting-edge applications of big data and artificial intelligence (AI) technologies in natural disaster prediction and prevention, with a focus on analyzing the ability of big data to extract disaster patterns from multisource data and the innovative approaches AI employs—through machine learning and deep learning—to enhance prediction accuracy. Using case studies of earthquakes, floods, and landslides, the paper demonstrates the practical effectiveness of these technologies in real-time monitoring, early warning systems, and emergency response. Additionally, the paper discusses future technological trends and ethical challenges in disaster management, emphasizing the importance of interdisciplinary collaboration and technological integration. This paper aims to provide a comprehensive technical review of the disaster management field, revealing the potential of big data and AI in enhancing global disaster response capabilities and offering a reference for future research and applications.
