基于方向关系矩阵的空间方向相似性定量计算方法

doi:10.11947/j.AGCS.2015.20140198

测绘学报 ›› 2015, Vol. 44 ›› Issue (7): 813-821.doi: 10.11947/j.AGCS.2015.20140198

基于方向关系矩阵的空间方向相似性定量计算方法

陈占龙^1,2, 周林¹, 龚希¹, 吴亮¹

1. 中国地质大学(武汉)信息工程学院, 湖北武汉 430074;
2. 地理信息工程国家重点实验室, 陕西西安 710054

收稿日期:2014-04-23 修回日期:2015-03-19 发布日期:2015-07-28
通讯作者: 吴亮,E-mail:wuliang133@189.cn E-mail:wuliang133@189.cn
作者简介:陈占龙(1980-),男,副教授,博士,主要研究方向为空间分析算法、空间推理、地理信息系统软件开发与应用。
基金资助:
国家自然科学基金(41401443);国家科技支撑计划(2011BAH06B04);地理信息工程国家重点实验室开放基金(SKLGIE2013-Z-4-1);测绘遥感信息工程国家重点实验室资助项目(13I02);中央高校基本科研业务费专项(CUGL130260)

A Quantitative Calculation Method of Spatial Direction Similarity Based on Direction Relation Matrix

CHEN Zhanlong^1,2, ZHOU Lin¹, GONG Xi¹, WU Liang¹

1. Department of Information Engineering, China University of Geosciences, Wuhan 430074, China;
2. State Key Laboratory of Geography Information Engineering, Xi'an 710054, China

Received:2014-04-23 Revised:2015-03-19 Published:2015-07-28
Supported by:
The National Natural Science Foundation of China (No. 41401443);The National Key Technology Research and Development Program of the Ministry of Science and Technology of China (No. 2011BAH06B04);Open Research Fund of State Key Laboratory of Geography Information Engineering(No.SKLGIE2013-Z-4-1);Open Research Fund of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (No. 13I02);Research Funds for the Central Universities Basic Special Projects (No.CUGL130260)

摘要/Abstract

摘要：

介绍了一种多尺度空间对象的方向关系表达模型以及基于该模型的方向相似度度量方法。该方向关系模型对方向关系矩阵模型进行了改进,根据空间对象的形状定量描述空间对象之间的方向关系;借鉴平衡传输问题的解决方法计算方向矩阵间最小转换代价,即方向矩阵间的距离,从而量化方向对间的差异,最终获得任意尺度空间对象的方向相似度并对其进行比较。对不同尺度空间对象的方向相似性的试验表明,该方法简单可行且不失精度,结果符合人类认知。

关键词: 多尺度, 空间对象, 方向相似度, 方向关系矩阵, 邻域图

Abstract:

This article introduces a new model for direction relations between spatial objects at multiple scales and a corresponding similarity assessment method. The model is an improvement of direction relation matrix, which quantitatively models direction relations on object scale, and by means of the solution of the Transportation Problem to solve the minimum conversion cost between direction matrices, namely distance between a pair of matrices, thus quantified the difference between a pair of directions, finally obtain the similarity values between arbitrary pairs of spatial objects and compare the results. Experiments on calculating similarity between objects at different scales show that the presented method is efficient, accurate, and capable of obtaining results consistent with human cognition.

Key words: multi-scales, spatial objects, direction similarity, direction relation matrix, neighborhood graph

中图分类号:

P208

陈占龙, 周林, 龚希, 吴亮. 基于方向关系矩阵的空间方向相似性定量计算方法[J]. 测绘学报, 2015, 44(7): 813-821.

CHEN Zhanlong, ZHOU Lin, GONG Xi, WU Liang. A Quantitative Calculation Method of Spatial Direction Similarity Based on Direction Relation Matrix[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(7): 813-821.

参考文献

[1] HOLT A, BENWELL G L. Using Spatial Similarity for Exploratory Spatial Data Analysis: Some Directions[C]//Proceedings of the 2nd International Conference on GeoComputation. Otago, New Zealand: SIRC, 1997.
[2] YAN Haowen, CHU Yandong. On the Fundamental Issues of Spatial Similarity Relations in Multi-scale Maps[J]. Geography and Geo-Information Science, 2009, 25(4): 42-48. (闫浩文, 褚衍东. 多尺度地图空间相似关系基本问题研究[J]. 地理与地理信息科学, 2009, 25(4): 42-48.)
[3] HAAR R. Computational Models of Spatial Relations[R]. Technical Report: TR-478, MSC-72-03610, Computer Science. College Park,MD: University of Maryland,1976.
[4] ALLEN J F. Maintaining Knowledge about Temporal Intervals[J]. Communications of the ACM, 1983, 26(11): 832-843.
[5] GUESGEN H W. Spatial Reasoning Based on Allen's Temporal Logic[R]. Technical Report: TR-89-049. Berkley, CA:International Computer Science Institute, 1989.
[6] BALBIANI P, CONDOTTA J F, DEL CERRO L F. A New Tractable Subclass of the Rectangle Algebra[C]// Proceedings of the 16th International Joint Conference on Artifical Intelligence. San Francisco: Morgan Kaufmann Publishers Inc., 1999: 442-447.
[7] BALBIANI P, CONDOTTA J F, DEL CERRO L F. A Model for Reasoning about Bidimensional Temporal Relations[C]// Proceedings of Principles of Knowledge Representation and Reasoning (KR). Trento: [s.n.], 1998: 124-130.
[8] CHANG S K, SHI Q Y, YAN C W. Iconic Indexing by 2-D Strings[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1987, 9(3): 413-428.
[9] PAPADIAS D, SELLIS T, THEODORIDIS Y, et al. Topological Relations in the World of Minimum Bounding Rectangles: A Study with R-trees[C]//Proceedings of the 1995 ACM SIGMOD International Conference on Management of Data. New York: ACM, 1995: 92-103.
[10] GOYAL R K. Similarity Assessment for Cardinal Directions between Extended Spatial Objects[D]. Maine: The University of Maine, 2000.
[11] GOYAL R K, EGENHOFER M J. Similarity of Cardinal Directions[M]// JENSEN C S, SCHNEIDER M, SEEGER B, et al. Advances in Spatial and Temporal Databases, Lecture Notes in Computer Science Volume 2121. Berlin, Heidelberg: Springer, 2001: 36-55.
[12] SKIADOPOULOS S, KOUBARAKIS M. Composing Cardinal Direction Relations[J]. Artificial Intelligence, 2004, 152(2): 143-171.
[13] DING Hong. A Study on Spatial Similarity Theory and Calculation Model[D]. Wuhan: Wuhan University, 2004. (丁虹. 空间相似性理论与计算模型的研究[D]. 武汉: 武汉大学, 2004.)
[14] GUO Qingsheng, DING Hong. Similarity for Spatial Directions between Areal Objects in Raster Data[J]. Geomatics and Information Science of Wuhan University, 2004, 29(5): 447-450. (郭庆胜, 丁虹. 基于栅格数据的面状目标空间方向相似性研究[J]. 武汉大学学报:信息科学版, 2004, 29(5): 447-450.)
[15] AN Xiaoya. Research on Theory, Methods and Applications of Geometry Similarity Measurement for Spatial Data[D]. Zhengzhou: Information Engineering University, 2011. (安晓亚. 空间数据几何相似性度量理论方法与应用研究[D]. 郑州: 信息工程大学, 2011.)
[16] GUO Li, CUI Tiejun, ZHENG Haiying, et al. Arithmetic for Area Vector Spatial Data Matching on Spatial Direction Similarity[J]. Journal of Geomatics Science and Technology, 2008, 25(5): 380-382. (郭黎, 崔铁军, 郑海鹰, 等. 基于空间方向相似性的面状矢量空间数据匹配算法[J]. 测绘科学技术学报, 2008, 25(5): 380-382.)
[17] YAN Haowen, GUO Renzhong. Research on Formal Description Model of Directional Relationships[J]. Acta Geodaetica et Cartographica Sinica, 2003, 32(1): 42-46. (闫浩文, 郭仁忠. 空间方向关系形式化描述模型研究[J]. 测绘学报, 2003, 32(1): 42-46.)
[18] DU Shihong, WANG Qiao, YANG Yipeng. A Qualitative Description Model of Detailed Direction Relations[J]. Journal of Image and Graphics, 2004, 9(12): 1496-1503. (杜世宏, 王桥, 杨一鹏. 一种定性细节方向关系的表达模型[J]. 中国图象图形学报, 2004, 9(12): 1496-1503.)
[19] DU Shihong, WANG Qiao, YANG Yipeng, et al. Fuzzy Description of Spatial Direction Relations[J]. Journal of Computer-aided Design & Computer Graphics, 2005, 17(8): 1744-1751. (杜世宏, 王桥, 杨一鹏, 等. 空间方向关系模糊描述[J]. 计算机辅助设计与图形学报, 2005, 17(8): 1744-1751.)
[20] DU Shihong, WANG Qiao, WEI Bin, et al. Spatial Orientational Relations Rough Reasoning[J]. Acta Geodaetica et Cartographica Sinica, 2003, 32(4): 334-338. (杜世宏, 王桥, 魏斌, 等. 空间方向关系粗糙推理[J]. 测绘学报, 2003, 32(4): 334-338.)
[21] CAO Han, CHEN Jun, DU Daosheng. Qualitative Extention Description for Cardinal Directions of Spatial Objects[J]. Acta Geodaetica et Cartographica Sinica, 2001, 30(2): 162-167. (曹菡, 陈军, 杜道生. 空间目标方向关系的定性扩展描述[J]. 测绘学报, 2001, 30(2): 162-167.)
[22] HE Jianhua, LIU Yaolin. An Integrated Model for Topology & Direction Relation Reasoning[J]. Acta Geodaetica et Cartographica Sinica, 2004, 33(2): 156-162. (何建华, 刘耀林. GIS中拓扑和方向关系推理模型[J]. 测绘学报, 2004, 33(2): 156-162.)
[23] WU Jing, CHENG Penggen, CHEN Fei, et al. Qualitative Reasoning for Direction Relation of Spatial Objects[J]. Acta Geodaetica et Cartographica Sinica, 2006, 35(2): 160-165. (吴静, 程朋根, 陈斐, 等. 空间目标的方向关系定性推理[J]. 测绘学报, 2006, 35(2): 160-165.)
[24] STRAYER J K. Linear Programming and Its Applications[M]. New York: Springer-Verlag.

基于方向关系矩阵的空间方向相似性定量计算方法

A Quantitative Calculation Method of Spatial Direction Similarity Based on Direction Relation Matrix

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	张新长, 何显锦, 孙颖, 黄健锋, 张志强. 多尺度空间数据联动更新技术研究现状及展望[J]. 测绘学报, 2022, 51(7): 1520-1535.
[2]	艾廷华, 张翔. 地理信息科学中尺度概念的诠释与表达[J]. 测绘学报, 2022, 51(7): 1640-1652.
[3]	梁哲恒, 黎宵, 邓鹏, 盛森, 姜福泉. 融合多尺度特征注意力的遥感影像变化检测方法[J]. 测绘学报, 2022, 51(5): 668-676.
[4]	孙伟伟, 常明会, 孟祥超, 杨刚, 任凯. 空谱协同多尺度顶点成分分析的高光谱影像端元提取[J]. 测绘学报, 2022, 51(4): 587-598.
[5]	洪亮, 冯亚飞, 彭双云, 楚森森. 面向对象的多尺度加权联合稀疏表示的高空间分辨率遥感影像分类[J]. 测绘学报, 2022, 51(2): 224-237.
[6]	邓敏, 谌恺祺, 石岩, 陈袁芳, 郭艺文. 多尺度空间同位模式挖掘的点过程分解方法[J]. 测绘学报, 2022, 51(2): 258-268.
[7]	高晓蓉, 闫浩文, 禄小敏. 多尺度地图空间居民地语义相似度计算方法[J]. 测绘学报, 2022, 51(1): 95-103.
[8]	张玉鑫, 颜青松, 邓非. 高分辨率遥感影像建筑物提取多路径RSU网络法[J]. 测绘学报, 2022, 51(1): 135-144.
[9]	叶健, 胡鑫, 徐鸿蒙, 陈曦, 吕琦. 多尺度GTWR城市住宅价格建模与分析[J]. 测绘学报, 2021, 50(9): 1266-1274.
[10]	李静, 刘海砚, 郭文月, 陈欣. 基于深度学习的人群活动流量时空预测模型[J]. 测绘学报, 2021, 50(4): 522-531.
[11]	龚希, 谢忠, 周林, 何占军. 空间方向相似性二元组模型度量方法[J]. 测绘学报, 2021, 50(12): 1705-1716.
[12]	续东, 柳景斌, 花向红, 陶武勇. 道路空间特征与测量距离相结合的LiDAR道路边界点提取算法[J]. 测绘学报, 2021, 50(11): 1534-1545.
[13]	刘鹏程, 肖天元, 肖佳, 艾廷华. 曲线多尺度表达的Head-Tail信息量分割法[J]. 测绘学报, 2020, 49(7): 921-933.
[14]	赵传, 郭海涛, 卢俊, 余东行, 张保明. 基于深度残差网络的机载LiDAR点云分类[J]. 测绘学报, 2020, 49(2): 202-213.
[15]	赵泉华, 谢凯浪, 王光辉, 李玉. 全卷积网络和条件随机场相结合的全极化SAR土地覆盖分类[J]. 测绘学报, 2020, 49(1): 65-78.