The geospatial sciences face grand information technology(IT)challenges in the twenty-first century:data intensity,computing intensity,concurrent access intensity and spatiotemporal intensity.These challenges require ...The geospatial sciences face grand information technology(IT)challenges in the twenty-first century:data intensity,computing intensity,concurrent access intensity and spatiotemporal intensity.These challenges require the readiness of a computing infrastructure that can:(1)better 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;(2)provide real-time IT resources to enable real-time applications,such as emergency response;(3)deal with access spikes;and(4)provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge.The emergence of cloud computing provides a potential solution with an elastic,on-demand computing platform to integrateobservation systems,parameter extracting algorithms,phenomena simulations,analytical visualization and decision support,and to provide social impact and user feedbackthe essential elements of the geospatial sciences.We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles,the kernel of the geospatial sciences,could be utilized to ensure the benefits of cloud computing.Four research examples are presented to analyze how to:(1)search,access and utilize geospatial data;(2)configure computing infrastructure to enable the computability of intensive simulation models;(3)disseminate and utilize research results for massive numbers of concurrent users;and(4)adopt spatiotemporal principles to support spatiotemporal intensive applications.The paper concludes with a discussion of opportunities and challenges for spatial cloud computing(SCC).展开更多
基金We thank Drs.Huadong Guo and Changlin Wang for inviting us to write this definition and field review paper.Research reported is partially supported by NASA(NNX07AD99G and SMD-09-1448),FGDC(G09AC00103)Environmental Informatics Framework of the Earth,Energy,and Environment Program at Microsoft Research Connection.We thank insightful comments from reviewers including Dr.Aijun Chen(NASA/GMU),Dr.Thomas Huang(NASA JPL),Dr.Cao Kang(Clark Univ.),Krishna Kumar(Microsoft),Dr.Wenwen Li(UCSB),Dr.Michael Peterson(University of Nebraska-Omaha),Dr.Xuan Shi(Geogia Tech),Dr.Tong Zhang(Wuhan University),Jinesh Varia(Amazon)and an anonymous reviewer.This paper is a result from the collaborations/discussions with colleagues from NASA,FGDC,USGS,EPA,GSA,Microsoft,ESIP,AAG CISG,CPGIS,UCGIS,GEO,and ISDE.
文摘The geospatial sciences face grand information technology(IT)challenges in the twenty-first century:data intensity,computing intensity,concurrent access intensity and spatiotemporal intensity.These challenges require the readiness of a computing infrastructure that can:(1)better 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;(2)provide real-time IT resources to enable real-time applications,such as emergency response;(3)deal with access spikes;and(4)provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge.The emergence of cloud computing provides a potential solution with an elastic,on-demand computing platform to integrateobservation systems,parameter extracting algorithms,phenomena simulations,analytical visualization and decision support,and to provide social impact and user feedbackthe essential elements of the geospatial sciences.We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles,the kernel of the geospatial sciences,could be utilized to ensure the benefits of cloud computing.Four research examples are presented to analyze how to:(1)search,access and utilize geospatial data;(2)configure computing infrastructure to enable the computability of intensive simulation models;(3)disseminate and utilize research results for massive numbers of concurrent users;and(4)adopt spatiotemporal principles to support spatiotemporal intensive applications.The paper concludes with a discussion of opportunities and challenges for spatial cloud computing(SCC).
