面向大规模DEM数据的并行填挖算法

A Parallel Cut-fill Algorithm for Large-scale DEM Data

传统填挖方算法在计算填挖方量时,对大规模DEM数据的处理能力和处理效率较低。针对上述问题,提出一种面向大规模DEM数据的并行填挖算法。首先实现了基于条带划分的并行算法,针对该算法负载不均衡和无效区域较多的问题,提出等面积划分方法。该方法通过对待填挖区域进行扫描并建立二元索引,实现了填挖区域的等面积划分,克服了上述问题。最后,在真实数据集上对上述两种算法进行了对比实验。实验结果表明,本文算法大幅提高了填挖分析效率,同时对海量DEM数据具有较强的处理能力。

The traditional cut-fill algorithm has poor processing ability and efficiency when calculating the cut-fill quantity of massive data.This paper proposes a parallel cut-fill algorithm for large-scale DEM data.Firstly,a parallel algorithm based on strip partitioning is implemented.For the problem of uneven load and invalid regions,an equal area partitioning method is proposed.The method overcomes the above problem by dividing the data to be analyzed into equal areas and establishing a dualistic index.Finally,experiments using real data sets verify the correctness and efficiency of the proposed algorithm.