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Paperback. Zustand: New. 1st. This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), 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 GeoAI, 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 GeoAI in fields such as information science, environment and natural resources, geosciences, and geography.FeaturesProvides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectivesCovers a wide range of GeoAI applications and case studies in practiceOffers supplementary materials such as data, programming code, tools, and case studiesDiscusses the recent developments of GeoAI methods and toolsIncludes contributions written by top experts in cutting-edge GeoAI topicsThis 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 GeoAI advances and applications.

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Paperback. Zustand: New. 1st. This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), 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 GeoAI, 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 GeoAI in fields such as information science, environment and natural resources, geosciences, and geography.FeaturesProvides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectivesCovers a wide range of GeoAI applications and case studies in practiceOffers supplementary materials such as data, programming code, tools, and case studiesDiscusses the recent developments of GeoAI methods and toolsIncludes contributions written by top experts in cutting-edge GeoAI topicsThis 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 GeoAI advances and applications.

Taschenbuch. Zustand: Neu. Neuware - Geospatial Artificial Intelligence (GeoAI) is the integration of geospatial studies and AI using machine learning and deep learning technologies. This comprehensive handbook explains and discusses key fundamental concepts, methods, models, technologies of GeoAI, recent advances, research tools, and applications in different fields.

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Taschenbuch. Zustand: Neu. Handbook of Geospatial Artificial Intelligence | Song Gao (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2026 | CRC Press | EAN 9781032311678 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

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Paperback. Zustand: new. Paperback. This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), 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 GeoAI, 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 GeoAI in fields such as information science, environment and natural resources, geosciences, and geography.FeaturesProvides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectivesCovers a wide range of GeoAI applications and case studies in practiceOffers supplementary materials such as data, programming code, tools, and case studiesDiscusses the recent developments of GeoAI methods and toolsIncludes contributions written by top experts in cutting-edge GeoAI topicsThis 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 GeoAI advances and applications. Geospatial Artificial Intelligence (GeoAI) is the integration of geospatial studies and AI using machine learning and deep learning technologies. This comprehensive handbook explains and discusses key fundamental concepts, methods, models, technologies of GeoAI, recent advances, research tools, and applications in different fields. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Zustand: new. Paperback. This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), 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 GeoAI, 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 GeoAI in fields such as information science, environment and natural resources, geosciences, and geography.FeaturesProvides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectivesCovers a wide range of GeoAI applications and case studies in practiceOffers supplementary materials such as data, programming code, tools, and case studiesDiscusses the recent developments of GeoAI methods and toolsIncludes contributions written by top experts in cutting-edge GeoAI topicsThis 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 GeoAI advances and applications. Geospatial Artificial Intelligence (GeoAI) is the integration of geospatial studies and AI using machine learning and deep learning technologies. This comprehensive handbook explains and discusses key fundamental concepts, methods, models, technologies of GeoAI, recent advances, research tools, and applications in different fields. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Zustand: new. Paperback. This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), 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 GeoAI, 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 GeoAI in fields such as information science, environment and natural resources, geosciences, and geography.FeaturesProvides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectivesCovers a wide range of GeoAI applications and case studies in practiceOffers supplementary materials such as data, programming code, tools, and case studiesDiscusses the recent developments of GeoAI methods and toolsIncludes contributions written by top experts in cutting-edge GeoAI topicsThis 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 GeoAI advances and applications. Geospatial Artificial Intelligence (GeoAI) is the integration of geospatial studies and AI using machine learning and deep learning technologies. This comprehensive handbook explains and discusses key fundamental concepts, methods, models, technologies of GeoAI, recent advances, research tools, and applications in different fields. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Song Gao is an Assistant Professor and the Director of Geospatial Data Science Lab at the University of Wisconsin-Madison. He holds a Ph.D. degree in Geography from the University of California-Santa Barbara. His research interests are on Spatial .