摘要
This paper proposed a virtual quadtree (VQT) based loose architecture of multi-level massive geospatial data for integrating massive geospatial data dispersed in the departments of different hierarchies in the same sector into a unified GIS (Geographic Information System) platform. By virtualizing the nodes of the quad-tree,the VQT separates the structure of data organization from data storage,and screens the difference between the data storage in local computer and in the re-mote computers in network environment. And by mounting,VQT easily integrates the data from the remote computers into the local VQT so as to implement seam-less integration of distributed multi-level massive geospatial data. Based on that mode,the paper built an application system with geospatial data over 1200 GB distributed in 12 servers deployed in 12 cities. The experiment showed that all data can be seamlessly rapidly traveled and performed zooming in and zooming out smoothly.
This paper proposed a virtual quadtree (VQT) based loose architecture of multi-level massive geospatial data for integrating massive geospatial data dispersed in the departments of different hierarchies in the same sector into a unified GIS (Geographic Information System) platform. By virtualizing the nodes of the quad-tree,the VQT separates the structure of data organization from data storage,and screens the difference between the data storage in local computer and in the re-mote computers in network environment. And by mounting,VQT easily integrates the data from the remote computers into the local VQT so as to implement seam-less integration of distributed multi-level massive geospatial data. Based on that mode,the paper built an application system with geospatial data over 1200 GB distributed in 12 servers deployed in 12 cities. The experiment showed that all data can be seamlessly rapidly traveled and performed zooming in and zooming out smoothly.
作者
YANG ChongJun,WU Sheng,REN YingChao,FU Li,ZHANG FuQing,WANG Gang,TAN Jian,LIU DongLin,MA ChaoJi & LIANG Li State Key Laboratory of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing 100101,China
基金
the National Natural Science Foundation of China (Grant No. 2006AA12Z208)
the CAS Innovation Program (Grant No. KZCX2-YW-304-02)
