High Performance Computing for Geospatial Applications

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.

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

Autorentext

Dr. Wenwu Tang is an Associate Professor and Executive Director of the Center for Applied GIScience at the Department of Geography and Earth Sciences at the University of North Carolina at Charlotte at U.S.A. He holds a Ph.D. degree from the University of Iowa and was a Post-doc and Research Scientist at the U.S. National Center for Supercomputing Applications and the University of Illinois at Urbana-Champaign. His research interests include cyberinfrastructure and high-performance geocomputation, agent-based modeling, and land change modeling. Dr. Tang has over 69 peer-reviewed publications, including 47 journal articles (e.g., International Journal of Geographical Information Science, Annals of the American Association of Geographers, Computers, Environment, and Urban Systems), 10 book chapters, and 12 conference proceedings. He has been actively applying high-performance computing technologies into geospatially related domains. Dr. Tang's research has been supported by federal and state funding agencies, including USDA Forest Services, US CDC, US Fish and Wildlife, NCDOT, NC Forest Service, and Electric Power Research Institute. Relevant courses that he has taught include CyberGIS and Big Data, Spatial Statistics, and Web GIS.

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.

Inhalt
Chapter 1-Introduction to high performance computing for geospatial applications. Chapter 2-Algorithms of high performance computing for geospatial applications. Chapter 3-Geospatial data handling with high performance computing. Chapter 4-Remote sensing with high performance computing. Chapter 5-Spatial analysis with high performance computing. Chapter 6-Spatial modeling with high performance computing. Chapter 7-Cartography and geovisualization with high performance computing. Chapter 8-Domain applications of high performance computing in ecology. Chapter 9-Domain applications of high performance computing in land use and land cover change. Chapter 10-Domain applications of high performance computing in urban studies. Chapter 11-Domain applications of high performance computing in spatial epidemiology. Chapter 12-Domain applications of high performance computing in earth science. Chapter 13-Domain applications of high performance computing in environmental engineering. Chapter14-Domain applications of high performance computing in transportation studies. Chapter 15-Domain applications of high performance computing in social science. Chapter 16-Vision and future of high performance computing for geospatial applications.