| 引用本文: | 杨宜舟,吴立新,郭甲腾,等.地籍数据库点线拓扑一致性并行检查方法.[J].国防科技大学学报,2015,37(5):40-46.[点击复制] |
| YANG Yizhou,WU Lixin,GUO Jiateng,et al.Parallel checking method for point-line topological consistency in cadastral database[J].Journal of National University of Defense Technology,2015,37(5):40-46[点击复制] |
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| 地籍数据库点线拓扑一致性并行检查方法 |
| 杨宜舟1, 吴立新1,2, 郭甲腾1, 刘善军1 |
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(1.东北大学 测绘遥感与数字矿山研究所， 辽宁 沈阳 110819;2.
2.中国矿业大学 物联网（感知矿山）研究中心， 江苏 徐州 221008)
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| 摘要: |
| 针对拓扑检查算法复杂、计算量大，串行计算已远不能满足海量地籍数据高效拓扑检查需求的问题，在分析了点线拓扑关系的并行特点基础上，将界址点的数据划分方法与界址线的Q&R空间索引方法相结合，实现了界址点与界址线的并行拓扑计算。用某地区实际的界址点集与界址线集对点线拓扑并行检查进行实验。测试结果表明：并行检查算法的并行效率随着进程数的增加而有所衰减，但稳定在30%以上，加速比达到5以上，且相比于ArcGIS效率提升了30倍以上。并行检查方法以工具的方式集成应用于高性能地理计算平台中，应用效果良好。 |
| 关键词: 地籍数据库 拓扑关系 数据质量 并行计算 高性能地理计算平台 |
| DOI：10.11887/j.cn.201505007 |
| 投稿日期：2015-06-29 |
| 基金项目:国家863计划资助项目（2011AA120302）；国家自然科学基金资助项目（41001228）；中央高校基本科研业务费资助项目（N140104002）；辽宁省自然科学基金资助项目（2015020581） |
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| Parallel checking method for point-line topological consistency in cadastral database |
| YANG Yizhou1, WU Lixin1,2, GUO Jiateng1, LIU Shanjun1 |
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(1. Institute of Geo-informatics & Digital Mine, Northeastern University, Shenyang 110819, China;2.
2. IoT/Perception Mine Research Center, China University of Mining & Technology, Xuzhou 221008, China)
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| Abstract: |
| The current topology inspection methods which use serial computation method accompanied with the complicated algorithms and excessive calculation amount cannot satisfy the demands of the efficient topology inspection for massive cadastral data. On the basis of the characteristics of topology calculation between point and line, the parallel topological computing method aiming at boundary points and lines has been implemented by combining the decomposition method for boundary points data with the Q tree and R tree spatial index method for boundary lines data. The topology parallel tests using the datasets of boundary points and lines in one area was taken in this method. The results show that the parallel efficiency of the algorithm which decreased with the increased number of processes steady maintains at above 30%, and the parallel speedup ratio reaches up to 5. The computation efficiency is improved more than 30 times than that of ArcGIS. The method can be used as a tool in high performance geographic information system and achieves good application effect. |
| Keywords: cadastral database topological relations data quality parallel computing high performance geographic information system |
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