Journal of Geo-information Science >
Geometry Similarity Assessment Model of Spatial Polygon Groups
Received date: 2013-03-26
Revised date: 2013-05-27
Online published: 2013-09-29
As a kind of spatial relationship, spatial similarity relationship is still in its initial research stage. Research works of similarity assessment of spatial group objects will improve spatial relationship's theory, deepen spatial cognition and raise the level of spatial data intelligent and automated handling. Focus on the spatial polygon groups, this paper proposed a novel computational model of geometry similarity measurement between spatial polygon groups. The conceptual neighborhood network of topological relationship was utilized to define topological relationship similarity between polygon groups. A suitable "dimensionality reduction" approach was utilized to process different polygon objects into line group. Then, the directional mean was utilized to define direction relationship between line groups, namely direction similarity of polygon groups. Finally, the circular variance was utilized to define distance relationship between line groups, namely distance similarity of polygon groups. Combined with the length, average length, area, average area, density and compactness of polygon groups, the final step established a computational model of similarity to comprehensively measure the geometry similarity of polygon groups. The computation model considered both geometry features and spatial relationship features of polygon groups, and a proper weights distribution was taking into account at the same time. Two experiments were taken out to verify the model. The experimental results showed that the computed similarity is consistent with ground object features and intuitive cognition of human beings.
LIU Chao, YAN Gao-Wen . Geometry Similarity Assessment Model of Spatial Polygon Groups[J]. Journal of Geo-information Science, 2013 , 15(5) : 635 -642 . DOI: 10.3724/SP.J.1047.2013.00635
[1] Li B N, Fonseca F T. TDD——A comprehensive model for qualitative spatial similarity assessment[J]. Spatial Cognition and Computation, 2006,6(1):31-62.
[2] Frontiera P, Larson R, Radke J. A comparison of geometric approaches to assessing spatial similarity for GIR[J]. International Journal of Geographical Information Science, 2008,22(3):337-360.
[3] Goodchild M F, Egenhofer M J, Fegeas R. Interoperating GISs. Report of a Specialist Meeting [EB/OL]. http://www. ncgia.ucsb.edu/conf/interop97/interop_toc.html.
[4] 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):42-44
[5] 郭仁忠.空间分析[M].北京:高等教育出版社,2001,240- 244.
[6] Arkin E M, Chew L P, Huttenlocher D P, et al. An efficiently computer metric for comparing polygonal shapes[J]. IEEE Transactions On Pattern Analysis And Machine Intelligence, 1991,3(13):209-215.
[7] Wang J Z, Li J. Wiederhold G. Simplicity: Semantics-sensitive integrated matching for picture libraries[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001,9(23):947-963.
[8] Rubner Y, Tomasi C, Guibas L J. The earth mover's distance as a metric for image retrieval[J]. International Journal of Computer Vision, 2000,40(2):99-121.
[9] 安晓亚,孙群,尉伯虎.利用相似性度量的不同比例尺地图数据网状要素匹配算法[J],武汉大学学报信息科学版2012,37(2):224-228.
[10] Bruns H T, Egenhofer M. Similarity of spatial scenes. //Kraak M J & Molenaar M (Eds.). Seventh International Symposium on Spatial Data Handling[C]. Delft, The Netherlands: Taylor & Francis, 1996:173-184.
[11] Zhao Z Q, Roger R S, Song D J. Measuring congruence of spatial objects[J]. International Journal of Geographical Information Science, 2011, 25(1):13-130.
[12] 唐炉亮,李清泉,杨必胜.空间数据网络多分辨率传输的几何图形相似性度量[J].测绘学报, 2009, 38(4): 336- 340.
[13] 刘鹏程,罗静,艾廷华,等.基于线要素综合的形状相似性评价模型[J],武汉大学学报·信息科学版,2012,37(1): 114-117.
[14] 郭庆胜,黄远林,郑春燕,等.空间推理与渐进式地图综合[M].武汉:武汉大学出版社,2007,73-76.
[15] Holt A. Spatial similarity and GIS: The grouping of spatial kinds[C]. Presented at SIRC 99 - The 11th Annual Colloquium of the Spatial Information Research Centre University of Otago, Dunedin, New Zealand,1999.
[16] 刘涛,杜清运,毛海辰.空间线群目标相似度计算模型研究[J].武汉大学学报信息科学版,2012,37(8): 992-995.
[17] 刘涛,杜清运,闫浩文.空间点群目标相似度计算模型研究[J].武汉大学学报·信息科学版,2011, 36(10) : 1149- 1153.
[18] Egenhofer M, Mark D. Naive Geography[C]. Spatial Information Theory: A Theoretical Basis for GIS, International Conference COSIT'95, Semmering, Austria, September 21-23,1995:1-15.
[19] Wong D W S, Lee J 著,张学良译. ArcView GIS 与Arc- GIS 地理信息统计分析[M].北京:中国财政经济出版社,2008,271-278.
[20] Janowicz K, Raubal M, Kuhn W. The semantics of similarity in geographic information retrieval[J]. Journal of Spatial Information Science, 2011(2):29-57.
/
| 〈 |
|
〉 |