Remote Sensing Big Data

Eugene Yu

ISBN 10: 3031339347 / ISBN 13: 9783031339349

Editore: Springer International Publishing, 2024

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - This monograph provides comprehensive coverage of the collection, management, and use of big data obtained from remote sensing. The book begins with an introduction to the basics of big data and remote sensing, laying the groundwork for the more specialized information to follow. The volume then goes on to address a wide variety of topics related to the use and management of remote sensing big data, including hot topics such as analysis through machine learning, cyberinfrastructure, and modeling. Examples on how to use the results of big data analysis of remotely sensed data for concrete decision-making are offered as well. The closing chapters discuss geospatial big data initiatives throughout the world and future challenges and opportunities for remote sensing big data applications.The audience for this book includes researchers at the intersection of geoscience and data science, senior undergraduate and graduate students, and anyone else interested in how large datasets obtained through remote sensing can be best utilized. The book presents a culmination of 30 years of research from renowned spatial scientists Drs. Liping Di and Eugene Yu.

Codice articolo 9783031339349

Dati bibliografici

• Titolo: Remote Sensing Big Data
• Editore: Springer International Publishing
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 3031339347
• ISBN 13: 9783031339349
• Rilegatura: Taschenbuch
• Condizione: Neu

Descrizione articolo

Riassunto

This monograph provides comprehensive coverage of the collection, management, and use of big data obtained from remote sensing. The book begins with an introduction to the basics of big data and remote sensing, laying the groundwork for the more specialized information to follow. The volume then goes on to address a wide variety of topics related to the use and management of remote sensing big data, including hot topics such as analysis through machine learning, cyberinfrastructure, and modeling. Examples on how to use the results of big data analysis of remotely sensed data for concrete decision-making are offered as well. The closing chapters discuss geospatial big data initiatives throughout the world and future challenges and opportunities for remote sensing big data applications. 

The audience for this book includes researchers at the intersection of geoscience and data science, senior undergraduate and graduate students, and anyone else interested in how large datasets obtained through remote sensing can be best utilized. The book presents a culmination of 30 years of research from renowned spatial scientists Drs. Liping Di and Eugene Yu.

Informazioni sull?autore

Dr. Liping Di serves as Professor and Director of the Center for Spatial Information Science and Systems at George Mason University in Virginia, USA. He is internationally known for his extraordinary contributions to the geospatial information science/geoinformatics, especially to the development of geospatial interoperability technology and the federal, national, and international geographic information and remote sensing standards. He was one of the core members for the development of the NASA EOSDIS data standards, and is a pioneer in the development of web-based, advanced, distributed geospatial systems and tools. Dr. Di has engaged in the geoinformatics and Earth system research for more than twenty-five years and has published over 500 publications.

Dr. Eugene Yu is a Research Professor and the Associate Director of the Center for Spatial Information Science and Systems, George Mason University, Fairfax, Virginia, USA. Dr. Yu received the B.Sc. degree in physical geography from the Peking University, Beijing, China, the M.Sc. in environmental remote sensing from the University of Aberdeen, Aberdeen, U.K., the M.S. in Information Systems and the M.S. in computer science from George Mason University, Fairfax, Virginia, USA, and the Ph.D. in geography with the focus on remote sensing and geographic information systems from the Indiana State University, Terre Haute, Indiana, USA. His research interests include geographic information systems, remote sensing, intelligent image understanding, Sensor Web, semantic Web, computational vision, agro-informatics, and robotics.