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.
Features
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 GeoAI advances and applications.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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 Data Science and GeoAI approaches to Human Mobility and Social Sensing. He has authored and co-authored over 50 peer-reviewed articles in prominent journals and conference proceedings. He is the recipient of various research and teaching awards at the university, state, and international levels, including the Waldo Tobler Young Researcher Award in GIScience. He serves as the Associate Editor for Annals of GIS, and editorial board member for Scientific Reports, PLOS One, and Guest Editor for IJGIS, TGIS, and GeoInformatica. He has been a lead organizer for the AAG symposiums on GeoAI and Deep Learning and and for the ACM SIGSPATIAL GeoAI workshops.
Yingjie Hu is an Assistant Professor in the Department of Geography at the University at Buffalo, NY, and at the National Center for Geographic Information and Analysis (NCGIA). He holds a PhD from the Department of Geography at UC Santa Barbara. He is the author of over 50 peer-reviewed articles in top international journals and conferences. He and his work received awards at international, national, and university levels, including Waldo-Tobler Young Researcher Award, GIScience 2018 Best Full Paper Award, and others. His research was also covered by major media such as Reuters and VOA News.
Wenwen Li is a Full Professor in the School of Geographical Sciences and Urban Planning, Arizona State University, where she heads the CyberInfrastructure and Computation Intelligence Lab. Li's work has been applied to several scientific disciplines, including polar science, climatology, public health, hydrology and urban studies. Her research has been supported by various funding agencies, including the National Science Foundation (NSF), United States Geological Survey (USGS), and Open Geospatial Consortium. Li was the chair of the Association of American Geographers' cyber-infrastructure specialty group from 2013-2014; a member of the Spatial Decision Support Consortium at the University of the Redlands (2015-); and a graduate faculty member in the Computer Science program at ASU (2016-). Li is also the 2015 NSF CAREER award winner and 2021 NSF Mid-CAREER award winner.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 52121377-n
Quantité disponible : 10 disponible(s)
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Paperback. Etat : 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. N° de réf. du vendeur 9781032311678
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 52121377
Quantité disponible : 10 disponible(s)
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur GB-9781032311678
Quantité disponible : 3 disponible(s)
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur GB-9781032311678
Quantité disponible : 3 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 52121377-n
Quantité disponible : 10 disponible(s)
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9781032311678
Quantité disponible : Plus de 20 disponibles
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. N° de réf. du vendeur 408839458
Quantité disponible : 3 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 52121377
Quantité disponible : 4 disponible(s)
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Paperback / softback. Etat : New. New copy - Usually dispatched within 4 working days. N° de réf. du vendeur B9781032311678
Quantité disponible : 1 disponible(s)