Spatial Intelligence for Hydrometeorological Hazards in a Changing Climate explores the intersection of advanced machine learning techniques and the intricate challenges posed by shifting hydrometeorological patterns. This comprehensive guide navigates readers through a diverse landscape of topics, ranging from data-driven models for early prediction of floods, landslides, soil erosion, heat waves, droughts, and novel approaches for assessing the impacts of extreme weather events on ecosystems and societies. Through real-world case studies and practical examples, the book demystifies complex algorithms and equips readers with the skills to harness the power of machine learning.

Whether you are a researcher, practitioner, or enthusiast, this book empowers you to leverage cutting-edge technology to address the urgent and evolving threats of a changing climate.

• Contains detailed case studies for mastering machine learning techniques in order to address specific climate hazard challenges
• Provides an interdisciplinary approach by blending spatial-based machine learning with hydrometeorological science to enhance hazard prediction accuracy
• Includes step-by-step instructions and code samples that facilitate the hands-on implementation of advanced machine learning algorithms