Drought and the condition of water scarcity lead to several socio-economic, social and environmental impacts. Whatever the approaches of drought management, policymakers and planners require novel methods to analyze data and model drought processes and its connection with water scarcity. In recent years, artificial intelligence-based and earth observation approaches have been progressively developed and applied in domain of water-related disasters. The target of this book is to present new advances and achievements in the fields of drought monitoring, analyzing, and modeling using artificial intelligence algorithms (e.g., machine learning, deep learning, etc.), statistical indices, and a diverse range of satellite remote sensing and geo-spatial data sets. Water Scarcity Management: Towards the Application of Artificial Intelligence and Earth Observation Data will help students gain knowledge on drought prediction using new free-access earth observation data and machine learning models. It will also guide scientists, researchers, and urban planners with the monitoring of water resources and key elements of hydrological cycle.

• Covers application of a range of diverse artificial intelligence algorithms for spatial modeling of drought susceptibility
• Includes real case studies from large geographical areas
• Offers earth observation satellite data for spatio-temporal analysis of drought and water scarcity
• Combines geo-environmental and topo-hydrological factors with drought and water scarcity issues