This comprehensive handbook covers Geospatial Artificial Intelligence (Geo AI), which is the integration of geospatial studies and AI machine (deep) learning and knowledge graph technologies. It explains key fundamental concepts, methods, models, and technologies of Geo AI, and discusses the recent advances, research tools, and applications that range from environmental observation and social sensing to natural disaster responses. As the first single volume on this fast-emerging domain, Handbook of Geospatial Artificial Intelligence is an excellent resource for educators, students, researchers, and practitioners utilizing Geo AI in fields such as information science, environment and natural resources, geosciences, and geography.Features Provides systematic introductions and discussions of Geo AI theory, methods, technologies, applications, and future perspectives Covers a wide range of Geo AI applications and case studies in practice Offers supplementary materials such as data, programming code, tools, and case studies Discusses the recent developments of Geo AI methods and tools Includes contributions written by top experts in cutting-edge Geo AI topics This book is intended for upper-level undergraduate and graduate students from different disciplines and those taking GIS courses in geography or computer sciences as well as software engineers, geospatial industry engineers, GIS professionals in non-governmental organizations, and federal/state agencies who use GIS and want to learn more about Geo AI advances and applications.
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