This book explores the integration of geospatial intelligence and artificial intelligence in disaster management, with a focus on unconventional mapping approaches. It examines how location-based data, satellite imagery, and deep learning converge to create real-time, predictive mapping tools that save lives. It provides a comprehensive understanding of how AI enhances every phase of disaster management - preparation, response, recovery, and resilience. The book focuses on deep learning techniques for image-based disaster mapping and predictive modeling, alongside current advances, research tools, and applications ranging from environmental observation to social sensing. Beyond the technology, it addresses critical challenges such as ethical considerations and future research directions, offering a balanced perspective on the opportunities and limitations of AI-driven disaster management. Designed for policymakers, researchers, and emergency responders, it provides groundbreaking strategies to predict, prevent, and respond to environmental disasters with unparalleled speed and accuracy.
