Multi-Scale Areal Feature Matching Approach Based On Root Mean Square Error And Neighbouring Relation

Abstract

Abstract:

Map object matching as an indispensable process in spatial data integration and updating has important researching significance. Root Mean Square Error (RMSE) as a numerical indicator that measures map accuracy and quality , its range is as one of the important standards in mapping and cartography generalization, and commonly used to balance the quality of spatial data, The data of different scale or sources are varying in size and threshold of the RMSE. Polygons occupy a much proportion in a map, this paper introduces the RMSE in the process of areal feature matching, combined with the clustering algorithm of adjacent Polygon to match areal feature. It can effectively solve the problems for dertermining the threshold and many-to-many relationship in the multi-scale spatial areal feature matching, the experimental results show that this method is stability and reliability.

Key words: Multi-scale, Areal Feature, Root Mean Square Error, Neighbouring Relation, Data Matching

CLC Number:

References

[1] WENTZ E A. Shape analysis in GIS [A]. Proc of ACSM/ASPRS [C]. [s.l.]:Seattle, Washington. 1997: 204-213.
[2] YUAN S, TAO D C. Development of Conflation Components [M]. Proceedings of Geoinformatics 99 Conference[C], Ann Arbor:[s.n.], 1999, 1-12.
[3] BEERI C, KANZA Y, SAFRA E, et al. Object fusion in geographic information systems [M]. Proceedings of the Thirtieth international conference on Very large data bases - Volume 30[C]. Toronto, Canada; VLDB Endowment. 2004: 816-827.
[4] MASUYAMA A. Methods for detecting apparent differences between spatial tessellations at different time points [J]. International Journal of Geographical Information Science, 2006, 20(6): 633-648.
[5] MIN D, ZHILIN L, XIAOYONG C. Extended Hausdorff distance for spatial objects in GIS [J]. International Journal of Geographical Information Science, 2007, 21(4): 459-475.
[6] HUH Y, YU K, HEO J. Detecting conjugate-point pairs for map alignment between two polygon datasets [J]. Computers, Environment and Urban Systems, 2011, 35(3): 250-262.
[7] COBB M A, CHUNG M J, FOLEY III H, et al. A Rule-based Approach for the Conflation of Attributed Vector Data [J]. GeoInformatica, 1998, 2(1): 7-35.
[8] AL-BAKRI M, FAIRBAIRN D. Assessing similarity matching for possible integration of feature classifications of geospatial data from official and informal sources [J]. International Journal of Geographical Information Science, 2012, 26(8): 1437-1456.
[9] ZHANG Qiaoping, LI Deren, GONG Jianya. Areal Feature Matching among Urban Geographic Databases[ J]. Journal of Remote Sensing, 2004, 8(2): 107-112.( 张桥平, 李德仁, 龚健雅. 城市地图数据库面实体匹配技术[J]. 遥感学报. 2004(02): 107-112)
[10] TONG Xiaohua, DENG Susu, SHI Wenzhong . A Probabilistic Theory-based Matching Method[J]. Acta Geodaetica et Cartographica Sinaca, 2007, 36(2): 210-217. (童小华, 邓愫愫, 史文中. 基于概率的地图实体匹配方法[J]. 测绘学报. 2007(02): 210-217. )
[11] HAO Yanling, TANG Wenjing, ZHAO Yuxin, LI Ning 。Areal Feature Matching Algorithm Based on Spatial Similarity[J]. Acta Geodaetica et Cartographica Sinaca, 2008, 37(4): 501-506.（郝燕玲, 唐文静, 赵玉新, et al. 基于空间相似性的面实体匹配算法研究[J]. 测绘学报. 2008(04): 501-506.）
[12] YE Yaqin , WAN Bo, Chen Bo. The Fuzzy Match Algorithm between Area Object Considering Associated Area Similarities[J]. EarthScience(Journal of China University of Geosciences),2010,35(4) :385-390.（叶亚琴, 万波, 陈波. 基于成分关联区域相似度的面实体模糊匹配算法[J]. 地球科学(中国地质大学学报). 2010(03): 385-390.）
[13] LIU Hongshen, QIN Feng . Method of Determining the Function of Description of Shape in Shape Matching[J]. Huazhong Univ of Sci &Tech(Nature Science Edition), 2005, 33(4): 13-16.( 刘宏申, 秦锋. 确定轮廓形状匹配中形状描述函数的方法[J]. 华中科技大学学报(自然科学版). 2005(04): 13-16.)
[14] Shao Shiwei. Researehes and Applications on Polygon Entity Matching for Multi-Scale Vector Data based on Geometric Features[D], Wuhan university ,2011(邵世维. 基于几何特征的多尺度矢量面状实体匹配方法研究与应用[D]. 武汉大学, 2011.)
[15] SAFRA E, KANZA Y, SAGIV Y, et al. Location‐based algorithms for finding sets of corresponding objects over several geo-spatial data sets [J]. International Journal of Geographical Information Science, 2010, 24(1): 69-106.
[16] SAFRA E, KANZA Y, SAGIV Y, et al. Ad hoc matching of vectorial road networks [J]. International Journal of Geographical Information Science, 2012, 1-40.
[17] XIONG D, SPERLING J. Semiautomated matching for network database integration [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2004, 59(1–2): 35-46.
[18] GOMBOSˇI M, ZˇALIK B, KRIVOGRAD S. Comparing two sets of polygons [J]. International Journal of Geographical Information Science, 2003, 17(5): 431-443.
[19] A-M O. A Multi-Criteria Fusion Approach for Geographical Data Matching[J]. International Symposium in Spatial Data Quality, 2007.
[20] CHEN C-C, KNOBLOCK C A, SHAHABI C, et al. Automatically and accurately conflating orthoimagery and street maps [M]. Proceedings of the 12th annual ACM international workshop on Geographic information systems[C]. Washington DC, USA; ACM. 2004: 47-56.