| 矢量数据变化对象的快速定位与最优组合匹配方法 |
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| 引用本文： | 罗国玮,张新长,齐立新,郭泰圣. 矢量数据变化对象的快速定位与最优组合匹配方法[J]. 测绘学报, 2014, 43(12): 1285-1292. DOI: 10.13485/j.cnki.11-2089.2014.0191 |
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| 作者姓名： | 罗国玮 张新长 齐立新 郭泰圣 |
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| 作者单位： | 1. 中山大学 地理科学与规划学院, 广东 广州 510275;2. 广西师范学院, 广西 南宁 530001;3. 广东省城市化与地理环境空间模拟重点实验室, 广东 广州 510275;4. 广东省国土资源测绘院, 广东 广州 510500 |
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| 基金项目： | 国家自然科学基金重点项目(41431178)；国家863计划(2013AA122302)；高等学校博士点专项基金 |
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| 摘 要： | 要素变化信息对地物生命周期的记录、时空数据库的构建、GIS数据库的更新有重要意义.针对大数据量的变化信息发现,本文采用基于格网划分的方法,通过对空间特征与属性特征汇总信息的对比,只对发生变化的格网进行检测,缩小了检测范围与空间查询区域.为解决要素变化前后的匹配问题,提出一种最优组合匹配法,通过对组合对象空间特征及语义特征的综合比较,从候选要素中选取最佳匹配对象.试验证明,该方法能够高效准确地实现大数据量的矢量数据变化信息的探测,并能很好地解决非一对一的要素匹配问题.
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| 关 键 词： | 变化信息 格网划分 语义树 最优组合匹配 |
| 收稿时间： | 2014-01-17 |
| 修稿时间： | 2014-06-22 |
The Fast Positioning and Optimal Combination Matching Method of Change V ector Obj ect |
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| LUO Guowei,ZHANG Xingchang,QI Lixin,GUO Taisheng. The Fast Positioning and Optimal Combination Matching Method of Change V ector Obj ect[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(12): 1285-1292. DOI: 10.13485/j.cnki.11-2089.2014.0191 |
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| Authors: | LUO Guowei ZHANG Xingchang QI Lixin GUO Taisheng |
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| Affiliation: | 1. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China;2. Guangxi Teachers Education University, Nanning 530001, China;3. Guangdong Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510275, China;4. Institute of Surverying and Mapping of Land and Resources Department of Guangdong Province, Guangzhou 510500, China |
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| Abstract: | The change-only information is important to the recording of object life cycle, the establishment of spatial-temporal database and the updating of GIS database. To solve the problem of low efficiency of traditional method in change detection when the data volume is large, we proposed a highly efficient method of change detection based on the grid-partitioning of data and the comparison of synthesis of spatial and attribute information. This method only detects the changed grid to reduce the detection region. In order to solve the matching problem of old features and new features, we propose a method named optimal combination-matching method. The method selects the optimally matched features through the comparison of the characteristic of spatial information and semantic information. The method's high efficiency and accuracy in change detection of large volume of spatial data and matching of changed features is validated by experiment. |
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| Keywords: | change-only information grid-partitioning semantic tree optimal combination-matching |
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