期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B4
页码：1449-1456
出版社：Copernicus Publications
摘要：Bulk-loading of spatial data is time-consuming and can not satisfy the desire of the applications dealing with massive spatial data. In the article, the TGS-based (Top-Down Greedy Split) parallel technique is made to accelerate the processing of spatial data bulk- loading, adopting the DCSO (Decompose- Conquer- Stitch - Output) strategy to build the R-tree in parallel. In order to manage and access the spatial data more efficiently, partition technology is applied to the physical storage of spatial data. This study accelerates the spatial data bulk loading efficient and makes the management and maintain of the spatial index easier and more flexible. The study also proves the R-tree constructed by parallel partitions performs better than serially strategy from the theoretical and experimental points of view as long as the decomposition of the study area is reasonable. Finally, an experiment is made to demonstrate the rationality of the proposed method and gains a perfect result
