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Study on Grid-Based Special Remotely Sensed Data Processing Node in Grid GIS

  • Jianqin Wang
  • Yong Xue
  • Jianping Guo
  • Yincui Hu
  • Chaolin Wu
  • Lei Zheng
  • Ying Luo
  • Yi Xie
  • YunLing Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4331)

Abstract

Grid Geospatial Information Service (Grid GIS) system aims to study and develop grid-based uniform spatial information access and analysis system. Data resources of Grid GIS include not only original and traditional GIS data but remotely sensed data. Everyday, space missions involve the download, from space to ground, of huge amount of raw images that are stored in the ground stations geographically distributed. It is a practical pressing task to process these data resource in real time or almost real time and to effectively share spatial information among remote sensing community. Grid technology can provide access to a global distributed computing environment via authentication, authorization, negotiation and security tools. This paper discusses the key technologies of Grid-based special remotely sensed data processing node. First, the concept of Grid-based special remotely sensed data processing node is introduced. Following is the architecture and functions of this node. Based on this architecture, the tasks scheduling algorithm is presented. Finally we introduce the computing resource meta-module information registry and renewal mechanism of the Grid-based special remotely sensed data processing node for Grid GIS.

Keywords

Grid Environment Virtual Resource Grid Technology Globus Toolkit Task Scheduler 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jianqin Wang
    • 1
  • Yong Xue
    • 2
    • 3
  • Jianping Guo
    • 2
    • 4
  • Yincui Hu
    • 2
  • Chaolin Wu
    • 2
  • Lei Zheng
    • 2
    • 4
  • Ying Luo
    • 2
    • 4
  • Yi Xie
    • 1
  • YunLing Liu
    • 1
  1. 1.College of Information and Electric EngineeringChina Agricultural UniversityBeijingChina
  2. 2.State Key Laboratory of Remote Sensing ScienceJointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of SciencesBeijingChina
  3. 3.Department of ComputingLondon Metropolitan UniversityLondonUK
  4. 4.Graduate School of the Chinese Academy of SciencesBeijingChina

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