郭明强的论文在IJGIS刊出.doc

郭明强的论文在 IJGIS 刊出 标题： A spatially adaptive decomposition approach for parallel vector data visualization of polylines and polygons 作者：Mingqiang Guo, Qingfeng Guan*, Zhong Xie, Liang Wu, Xiangang Luo and Ying Huang 来源出版物：International Journal of Geographical Information Science DOI：10.1080/13658816.2015.1032294 出版年：Apr 2015 摘要：With the wide adoption of big spatial data and the emergence of CyberGIS, the nontrivial computational intensity introduced by massive amount of data poses great challenges to the performance of vector map visualization. The parallel computing technologies provide promising solutions to such problems. Evenly decomposing the visualization task into multiple subtasks is one of the key issues in parallel visualization of vector data. This study focuses on the decomposition of polyline and polygon data for parallel visualization. Two key factors impacting the computational intensity were identified: the number of features and the number of vertices of each feature. The computational intensity transform functions (CITFs) were constructed based on the linear relationships between the factors and the computing time. The computational intensity grid (CIG) can then be constructed using the CITFs to represent the spatial distribution of computational intensity. A noninterlaced continuous space-filling curve is used to group the lattices of CIG into multiple sub-domains such that each sub- domain entails the same amount of computational intensity as others. The experiments demonstrated that the approach proposed in this paper was able to effectively estimate and spatially represent the computational intensity of visualizing polylines and polygons. Compared with the regular domain decomposition methods, the new approach generated much more balanced decomposition of computational intensity for parallel visualization and achieved near-linear speedups, especially when the data is greatly heterogeneously distributed in space. 文献类型：Article 语种：English 关键词：vector map; visualization; load-balance; decomposition; computational intensity 通讯作者地址：Guan, Qingfeng; Faculty of Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China Email: guanqf@cug.edu.cn ISSN：1362-3087