相關主題
商品描述
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
- Provides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectives
- Covers a wide range of GeoAI applications and case studies in practice
- Offers supplementary materials such as data, programming code, tools, and case studies
- Discusses the recent developments of GeoAI methods and tools
- Includes contributions written by top experts in cutting-edge GeoAI 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 GeoAI advances and applications.
商品描述(中文翻譯)
這本全面的手冊涵蓋了地理空間人工智慧（GeoAI），即地理空間研究與人工智慧機器（深度）學習和知識圖譜技術的整合。它解釋了GeoAI的關鍵基本概念、方法、模型和技術，並討論了從環境觀測和社會感知到自然災害應對的最新進展、研究工具和應用。作為這個快速發展領域的首部單卷著作，《地理空間人工智慧手冊》是教育工作者、學生、研究人員和從事信息科學、環境和自然資源、地球科學和地理學等領域的實踐者利用GeoAI的優秀資源。
特點：
- 提供GeoAI理論、方法、技術、應用和未來展望的系統介紹和討論
- 涵蓋了各種實踐中的GeoAI應用和案例研究
- 提供了數據、編程代碼、工具和案例研究等補充資料
- 討論了GeoAI方法和工具的最新發展
- 包含了頂尖專家撰寫的尖端GeoAI主題的貢獻
本書適用於不同學科的高年級本科生和研究生，以及地理學或計算機科學課程的地理信息系統（GIS）學生，以及軟件工程師、地理空間行業工程師、非政府組織的GIS專業人員和聯邦/州政府機構，他們使用GIS並希望了解更多關於GeoAI的進展和應用。
作者簡介
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.
作者簡介(中文翻譯)
Song Gao是威斯康辛大學麥迪遜分校的助理教授和地理空間數據科學實驗室的主任。他擁有加利福尼亞大學聖塔芭芭拉分校的地理學博士學位。他的研究興趣包括空間數據科學和地理人流和社會感知的地理人工智能方法。他在知名期刊和會議論文中發表和合著了50多篇同行評審的文章。他曾獲得該大學、州和國際層面的多個研究和教學獎項，包括GIScience的Waldo Tobler青年研究者獎。他擔任《Annals of GIS》的副編輯，並擔任《Scientific Reports》、《PLOS One》的編委會成員，以及《IJGIS》、《TGIS》和《GeoInformatica》的客座編輯。他曾是AAG關於GeoAI和深度學習的研討會和ACM SIGSPATIAL GeoAI研討會的主要組織者。
Yingjie Hu是紐約州布法羅市大學地理學系和國家地理信息分析中心（NCGIA）的助理教授。他擁有加利福尼亞大學聖塔芭芭拉分校地理學系的博士學位。他是國際頂尖期刊和會議上50多篇同行評審文章的作者。他和他的工作在國際、國家和大學層面上獲得了多個獎項，包括Waldo-Tobler青年研究者獎、GIScience 2018最佳全文獎等。他的研究還受到路透社和美國之音等主要媒體的報導。
Wenwen Li是亞利桑那州立大學地理科學與城市規劃學院的正教授，她還是該校的CyberInfrastructure和Computation Intelligence實驗室的負責人。李的工作已應用於極地科學、氣候學、公共衛生、水文學和城市研究等多個科學領域。她的研究得到了包括國家科學基金會（NSF）、美國地質調查局（USGS）和開放地理空間聯盟在內的各種資助機構的支持。李曾擔任2013-2014年美國地理學家協會的網絡基礎設施專業組主席；2015年至今是紅地大學空間決策支持聯盟的成員；2016年至今是亞利桑那州立大學計算機科學項目的研究生教師。李還是2015年NSF CAREER獎和2021年NSF Mid-CAREER獎的獲獎者。
