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Chaowei Yang
Researcher at George Mason University
Publications - 196
Citations - 5347
Chaowei Yang is an academic researcher from George Mason University. The author has contributed to research in topics: Geospatial analysis & Cloud computing. The author has an hindex of 35, co-authored 171 publications receiving 4412 citations. Previous affiliations of Chaowei Yang include Tsinghua University & National Science Foundation.
Papers
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Journal ArticleDOI
Big Data and cloud computing: innovation opportunities and challenges
TL;DR: This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications.
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Geospatial Cyberinfrastructure: Past, present and future
TL;DR: This paper reviews the research, development, education, and other efforts that have contributed to building GCI in terms of its history, objectives, architecture, supporting technologies, functions, application communities, and future research directions.
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Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?
Chaowei Yang,Michael F. Goodchild,Qunying Huang,Doug Nebert,Robert Raskin,Yan Xu,Myra Bambacus,Dan Fay +7 more
TL;DR: In this paper, the authors propose a cloud-based infrastructure for the geospatial sciences that can support discovery, access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries.
Patent
Geographic information system
TL;DR: Disclosed is a geographic information system which comprises a multithreading client and a multathreading server cluster that includes at least one user interface, at least two client coordinator, map data, and at least three server-side spatial managers.
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Performance‐improving techniques in web‐based GIS
TL;DR: Several major potential performance problems with WebGIS are identified and several possible techniques to improve the performance are discussed, which include the use of pyramids and hash indices on the server side to handle large images and clustering and multithreading techniques.