Vector polygon overlay is a complex type of a geo-spatial analysis algorithm used in geographical information system, which requires increasingly higher computational efficiency given the rapid growth of spatial data sets. Parallel computing has provided an effective approach to improve the computational efficiency and expand the processing scales of polygon overlay algorithms. Polygon overlay analysis algorithms that are based on traditional vector polygon clipping algorithms will experience significant efficiency decreases when handling overlap among polygons that have quantities of vertices. The discretization processing method-based rasterization-based polygon clipping algorithm (RaPC) algorithm exhibits higher efficiency for addressing clipping issues among such polygons. In this paper, we designed and implemented two types of parallel polygon overlay analysis algorithms to determine the differences in efficiency between the RaPC algorithm and the Vatti algorithm under the open multi-processing and message passing interface parallel computing environments. The results show that parallel polygon overlay analysis methods based on the RaPC algorithm present advantages for processing overlap among large data sets. The parallel algorithm based on the Vatti algorithm presents higher efficiency when handling overlap among small spatial data sets. The discretization process between two overlapped geometries of the RaPC algorithm provided a potential approach to solve the polygon overlay problem using a fine-grained parallelization method.

中文翻译：

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基于 OpenMP 和 MPI 的基于栅格化计算的并行矢量多边形叠加分析算法


矢量多边形叠加是地理信息系统中使用的一种复杂类型的地理空间分析算法，随着空间数据集的快速增长，它对计算效率的要求越来越高。并行计算为提高多边形叠加算法的计算效率和扩展处理规模提供了一种有效的方法。在处理具有大量折点的面之间的重叠时，基于传统矢量面裁剪算法的面叠加分析算法的效率将显著降低。基于离散化处理方法的基于光栅化的多边形裁剪算法 （RaPC） 算法在解决此类多边形之间的裁剪问题方面表现出更高的效率。在本文中，我们设计并实现了两种类型的并行多边形叠加分析算法，以确定在开放多处理和消息传递接口并行计算环境下 RaPC 算法和 Vatti 算法的效率差异。结果表明，基于 RaPC 算法的并行多边形叠加分析方法在处理大型数据集之间的重叠方面具有优势。基于 Vatti 算法的并行算法在处理小型空间数据集之间的重叠时具有更高的效率。RaPC 算法的两个重叠几何图形之间的离散化过程提供了一种使用细粒度并行化方法解决多边形叠加问题的潜在方法。