中文摘要：

为了解决并行矢量空间分析在数据划分阶段的负载均衡问题，研究了矢量空间数据的划分，提出了一种基于空间聚类思想的矢量空间数据划分方法。该方法充分考虑矢量空间数据规模以及空间邻近性特征对并行空间分析算法效率的影响，首先采用空间填充曲线对二维空间数据进行编码，保证空间要素邻近性特征；然后用空间要素集合对空间要素流进行填充，从而确保各个子任务集中的要素数据规模相对均衡。以并行叠加分析中点面、线面、面面叠加操作为例，设计了对比实验。实验结果表明，该方法能够有效提高以线、面要素为操作对象的并行算法负载均衡度和提高并行算法整体运行效率。

英文摘要：

The partitioning of vector spatial data was studied, and a new data partitioning method based on spatial cluste- ring was proposed to deal with the load balancing problem in the data partitioning stage of parallel vector spatial analysis. This method fully considers the influence of the ciency of the algorithm for parallel vector spatial analysis. vector spatial data size and Firstly, it uses space filling spatial proximity on the effi- curves to encode the two-di- mensional spatial data to keep the characteristic of spatial proximity. Secondly, it fills the features to the spatial feature box to ensure the balance of the feature sizes in each slaver processing. The operations of point-to-surface, curve-to-surface and surface-to-surface overlay were used as the examples to design the contrast test. The experi- mental result proved that this proposed method improved the load balancing degree and the whole efficiency of the parallel algorithm on the curve and surface spatial data.