《计算机应用研究》|Application Research of Computers

基于MapReduce模型的侵蚀地形因子计算方法研究

Calculation of topographic factor on soil erosion based on MapReduce

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作者 王猛,张宏鸣
机构 西北农林科技大学 信息工程学院,陕西 杨凌 712100
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文章编号 1001-3695(2019)06-022-1700-05
DOI 10.19734/j.issn.1001-3695.2017.12.0806
摘要 针对传统侵蚀地形因子提取方法在处理海量数据时出现的瓶颈,提出一种基于MapReduce模型的侵蚀地形因子计算方法。该方法将并行计算模型MapReduce与改进的通用土壤流失方程(revised universal soil loss equation,RUSLE)相结合。利用最大坡降原理和B+树建立流向关系查找树来表现地形数据的相关性;利用MapReduce模型进行流路查找与栅格汇聚来替代传统正反向遍历算法,解决侵蚀地形因子计算过程中汇水和累计坡长的计算效率问题。实验结果表明,对于基于海量数字高程模型数据的地形因子提取,该方法能够在计算精度允许的范围内有效提高效率。
关键词 MapReduce模型; 大数据; Hadoop; 地形因子; 地理信息系统
基金项目 国家自然科学基金资助项目(41771315,41301283,41371274)
国家重点研发计划资助项目(2017YFC0403203)
欧盟地平线2020研究与创新计划项目(GA:635750)
本文URL http://www.arocmag.com/article/01-2019-06-022.html
英文标题 Calculation of topographic factor on soil erosion based on MapReduce
作者英文名 Wang Meng, Zhang Hongming
机构英文名 College of Information Engineering,Northwest A&F University,Yangling Shaanxi 712100,China
英文摘要 Aiming at the bottleneck of traditional extraction method of topographic factor on soil erosion in processing massive data, this paper proposed a method based on MapReduce. This method combined the parallel computing model MapReduce with the revised universal soil loss equation(RUSLE). The method established the flow relationship search tree by the principle of steep slope and the B+ tree, and represented the correlation of topographic data; The method used the MapReduce model to search flow path and converge grid instead of the traditional forward and backward traversal algorithm, and solved the efficiency of the flow accumulation and slope length calculation in topographic factor calculation. The experimental results show that for the extraction of topographic factor from massive digital elevation model, the method can effectively improve the extraction efficiency in the range of the allowable accuracy.
英文关键词 MapReduce model; big data; Hadoop; topographic factor; geographic information system
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收稿日期 2017/12/13
修回日期 2018/2/5
页码 1700-1704
中图分类号 TP399
文献标志码 A