Overview
- Fills the gap between the rapid development of High Performance Computing (HPC) approaches and their geospatial applications
- Presents applications of HPC in geospatial domains, including ecology, land change science, urban studies, spatial epidemiology, earth science, environmental science, transportation studies, and social science
- Uses several real-world examples to demonstrate how HPC can be used to collect, manage, and process geospatial big data
Part of the book series: Geotechnologies and the Environment (GEOTECH, volume 23)
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Table of contents (15 chapters)
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Front Matter
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Theoretical Aspects of High Performance Computing
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Front Matter
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High Performance Computing for Geospatial Analytics
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Front Matter
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Domain Applications of High Performance Computing
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Front Matter
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Future of High Performance Computing for Geospatial Applications
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Front Matter
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Keywords
About this book
This volume fills a research gap between the rapid development of High Performance Computing (HPC) approaches and their geospatial applications. With a focus on geospatial applications, the book discusses in detail how researchers apply HPC to tackle their geospatial problems. Based on this focus, the book identifies the opportunities and challenges revolving around geospatial applications of HPC. Readers are introduced to the fundamentals of HPC, and will learn how HPC methods are applied in various specific areas of geospatial study.
The book begins by discussing theoretical aspects and methodological uses of HPC within a geospatial context, including parallel algorithms, geospatial data handling, spatial analysis and modeling, and cartography and geovisualization. Then, specific domain applications of HPC are addressed in the contexts of earth science, land use and land cover change, urban studies, transportation studies, and social science. The bookwill be of interest to scientists and engineers who are interested in applying cutting-edge HPC technologies in their respective fields, as well as students and faculty engaged in geography, environmental science, social science, and computer science.
Editors and Affiliations
About the editors
Dr. Shaowen Wang is a Professor and Head of the Department of Geography and Geographic Information Science; Richard and Margaret Romano Professorial Scholar; and an Affiliate Professor of the Department of Computer Science, Department of Urban and Regional Planning, and School of Information Sciences at the University of Illinois at Urbana-Champaign (UIUC). He has served as Founding Director of CyberGIS Center for Advanced Digital and Spatial Studies at UIUC since 2013. He served as Associate Director of the National Center for Supercomputing Applications (NCSA) for CyberGIS from 2010 to 2017, and Lead of NCSA’s Earth and Environment Theme from 2014 to 2017. He received a BS in computer engineering from Tianjin University, an MS in geography from Peking University, and an MS of computer science and a PhD in geography from the University of Iowa. His research interests include geographic information science and systems (GIS), advanced cyberinfrastructure and cyberGIS, complex environmental and geospatial problems, computational and data sciences, high-performance and distributed computing, and spatial analysis and modeling.
Bibliographic Information
Book Title: High Performance Computing for Geospatial Applications
Editors: Wenwu Tang, Shaowen Wang
Series Title: Geotechnologies and the Environment
DOI: https://doi.org/10.1007/978-3-030-47998-5
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-47997-8Published: 21 July 2020
Softcover ISBN: 978-3-030-48000-4Published: 22 July 2021
eBook ISBN: 978-3-030-47998-5Published: 20 July 2020
Series ISSN: 2365-0575
Series E-ISSN: 2365-0583
Edition Number: 1
Number of Pages: XIII, 296
Number of Illustrations: 24 b/w illustrations, 70 illustrations in colour
Topics: Remote Sensing/Photogrammetry, Big Data, Data-driven Science, Modeling and Theory Building, Simulation and Modeling, Environmental Science and Engineering, Landscape Ecology