• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2013, Vol. 35 ›› Issue (4): 18-23.

• 论文 • 上一篇    下一篇

地形分析中坡度坡向算法并行化方法研究

江岭,刘学军,汤国安,宋效东   

  1. (南京师范大学虚拟地理环境教育部重点实验室,江苏 南京 210023)
  • 出版日期:2013-04-25 发布日期:2013-04-27
  • 基金资助:

    国家高技术研究发展计划资助项目(2011AA120303);国家自然科学基金资助项目(40930531,41071244);江苏省普通高校研究生科研创新计划资助项目(CXZZ12_0391);南京师范大学研究生优秀学位论文培育计划资助项目(2011BS0007)

Parallel slope and aspect algorithm in terrain analysis     

JIANG Ling,LIU Xuejun,TANG Guoan,SONG Xiaodong   

  1. (Key Laboratory of Virtual Geographic Environment,Ministry of Education,Nanjing Normal University,Nanjing 210023,China)
  • Online:2013-04-25 Published:2013-04-27

摘要:

数字地形分析(DTA)是在DEM上进行地形属性计算和特征提取的数字信息处理技术,广泛应用于各行各业。在分析地形分析中坡度坡向串行算法特征的基础上,对坡度坡向算法的并行化进行了深入研究。从数据并行的角度,对算法的数据拆分、结果融合及I/O策略进行了分析,构建了坡度坡向算法并行化方法。实验结果表明,本文提出的并行化方法可以有效对坡度坡向串行算法进行并行化改造,大幅度提高了算法的执行效率,具有较好的并行性能。方法的提出和实现亦可为类似矩阵型数据算法的并行化提供参考。

关键词: 数字地形分析, 数字高程模型, 坡度坡向, 算法并行

Abstract:

Digital Terrain Analysis (DTA) is a digital information processing technology based on Digital Elevation Model (DEM) for the terrain attribute calculation and features extraction. Slope and aspect are the basic terrain parameters of DTA and widely used in different fields. However, it is always more difficult to get slope and aspect from DEM and normally needs more time to calculate slope and aspect due to large study area and huge data. Based on the analysis of serial algorithm features of slope and aspect in terrain analysis, the strategies of the data division, the data fusion and I/O of DTA algorithms are analyzed, and the parallel method was constructed from the aspect of data parallelism in the paper. The research indicates that the parallel method is efficient in performing the parallelization of sequential algorithms of slope and aspect, and the parallel method increases the execution efficiency of algorithms and achieves a good performance. The proposed parallel method can also be as a reference for the parallelization of the algorithms with the similar matrix type data.

Key words: DTA;DEM;slope &, aspect;algorithm parallelization