A Building Polygonal Object Alignment Approach for Spatial Data Integration

ZHU Xinyan; LIU Lingjia

doi:10.13203/j.whugis20180184

Volume 43 Issue 12

Dec. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(12): 2269-2277. > DOI: 10.13203/j.whugis20180184

ZHU Xinyan, LIU Lingjia. A Building Polygonal Object Alignment Approach for Spatial Data Integration[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2269-2277. DOI: 10.13203/j.whugis20180184

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A Building Polygonal Object Alignment Approach for Spatial Data Integration

ZHU Xinyan^{1, 2, 3,},
LIU Lingjia^1, ,

1.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2.
Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China
3.
Key Laboratory of Aerospace Information Security and Trusted Computing of Ministry of Education, Wuhan University, Wuhan 430079, China

Funds:

The National Key Research and Development Program of China 2016YFB0502204

the National Natural Science Foundation of China 41661083

Special Research Funding of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing

Open Fund of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing 2016 Key Project

Aerospace Science and Technology Innovation Foundation of China

More Information

Author Bio:
ZHU Xinyan, PhD, professor, specializes in spatial database, spatial information service. E-mail: xinyanzhu@whu.edu.cn
Corresponding author:
LIU Lingjia, PhD candidate. E-mail: liulingjia_office@163.com
Received Date: August 13, 2018
Published Date: December 04, 2018

Graphical Abstract

Abstract

Abstract

This paper proposes a building polygon alignment approach for spatial data integration which can be used to improve the spatial data position accuracy. Firstly, this paper uses the minimum bounding rectangle combinatorial optimization algorithm to identify corresponding objects between the integrated data. Then, a pairwise constraint spectrum matching algorithm based on geometric simila-rity is proposed to detect conjugate-point pairs of 1:1, 1:N, and M:N correspondence. The conjugate-point pairs from 1:N, and M:N correspondence inevitably have weak or error corresponding point pair, thus this paper proposes a least-squares algorithm based on the IGG1 weight to align the corresponding objects. The proposed method is applied to align base map data with higher positional accuracy and Google map data with lower positional accuracy. The results show that the proposed method can not only detect conjugate-point pairs of 1:N, and M:N correspondence with complex contours, but also can achieve the accurate alignment between them, and minimize their difference of positional information.
- building polygon,
- spatial data integration,
- map alignment,
- object matching,
- contour-point pair

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References (32)

References

[1]	Xavier E M, Arizalopez F J, Urenacamara M A. A Survey of Measures and Methods for Matching Geospatial Vector Datasets[J]. ACM Computing Surveys, 2016, 49:1-34 http://dl.acm.org/ft_gateway.cfm?id=2963147&ftid=1780068&dwn=1&CFID=675543088&CFTOKEN=63263631
[2]	Wiemann S. Formalization and Web-Based Implementation of Spatial Data Fusion[J]. Computers & Geosciences, 2017, 99:107-115 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=f52128928081883028f6a1df0258c742
[3]	Wiemann S, Bernard L.Spatial Data Fusion in Spatial Data Infrastructures Using Linked Data[J]. International Journal of Geographical Information Science, 2016, 30:613-636 doi: 10.1080/13658816.2015.1084420
[4]	Yuan S, Tao C. Development of Conflation Components[C]. Geoinformatics'99 Conference, Ann Arbor, USA, 1999
[5]	Longley P A, Goodchild M, Maguire D J, et al. Geographic Information Systems and Science[M]. New Jersey: John Wiley & Sons Inc, 2001
[6]	Tong X, Liang D, Jin Y, et al. A Linear Road Object Matching Method for Conflation Based on Optimization and Logistic Regression[J]. International Journal of Geographical Information Science, 2014, 28(4): 824-846 doi: 10.1080/13658816.2013.876501
[7]	Ruiz-Lendínez J, Ureña-Cámara M, Ariza-López F. A Polygon and Point-Based Approach to Matching Geospatial Features[J]. International Journal of Geo-Information, 2017, 6(12):399 doi: 10.3390/ijgi6120399
[8]	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: 250-262 doi: 10.1016/j.compenvurbsys.2010.08.001
[9]	Saalfeld A. Conflation: Automated Map Compilation[J]. International Journal of Geographical Information Systems, 1988, 2:217-218 doi: 10.1080/02693798808927897
[10]	Jensen J, Saalfeld A, Broome F, et al. Spatial Data Acquisition and Integration[J]. Geomorphology, 2011, 41(2-3):171-181 http://d.old.wanfangdata.com.cn/Periodical/dlxxsj201602017
[11]	Hecht R, Kunze C, Hahmann S. Measuring Completeness of Building Footprints in OpenStreetMap over Space and Time[J]. ISPRS International Journal of Geo-Information, 2013, 2(4):1 066-1 091 doi: 10.3390/ijgi2041066
[12]	Fan H, Zipf A, Fu Q, et al. Quality Assessment for Building Footprints Data on OpenStreetMap[J]. International Journal of Geographical Information Science, 2014, 28: 700-719 doi: 10.1080/13658816.2013.867495
[13]	Devogele T. A New Merging Process for Data Integration Based on the Discrete Frechét Distance[C]. Joint International Symposium on Geospatial Theory, Processing and Applications, Ottawa, Canada, 2002 doi: 10.1007/978-3-642-56094-1_13
[14]	安晓亚, 孙群, 肖强, 等.一种形状多级描述方法及在多尺度空间数据几何相似性度量中的应用[J].测绘学报, 2011, 40(4):495-501, 508 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK201101695862 An Xiaoya, Sun Qun, Xiao Qiang, et al.A Shape Multilevel Description Method and Application in Measuring Geometry Similarity of Multi-scale Spatial Data[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(4):495-501, 508 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK201101695862
[15]	Kim J O, Yu K, Heo J, et al. A New Method for Matching Objects in Two Different Geospatial Datasets Based on the Geographic Context[J]. Compu-ters & Geosciences, 2010, 36: 1 115-1 122 http://www.sciencedirect.com/science/article/pii/S0098300410001731
[16]	Li L, Goodchild M F. An Optimization Model for Liner Feature Matching in Geographical Data Conflation[J]. International Journal of Image and Data Fusion, 2011, 2:309-328 doi: 10.1080/19479832.2011.577458
[17]	Gösseln G, Sester M.Change Detection and Integration of Topographic Updates from ATKIS and Geoscientific Data Sets[C]. International Conference on Next Generation Geospatial Information, Boston, USA, 2003
[18]	Butenuth M, Von Gosseln G, Tiedge M, et al.Integration of Heterogeneous Geospatial Data in a Federated Database[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2007, 62: 328-346 doi: 10.1016/j.isprsjprs.2007.04.003
[19]	郝燕玲, 唐文静, 赵玉新.基于多评价因素的面状要素合并变换算法[J].计算机辅助设计与图形学学报, 2009, 21(2):237-242 http://d.old.wanfangdata.com.cn/Periodical/jsjfzsjytxxxb200902017 Hao Yanling, Tang Wenjing, Zhao Yuxin. Areal Elements Adjusting Algorithm Based on Multi-eva-luation Factors[J]. Journal of Computer Aided Design & Computer Graphics, 2009, 21(2):237-242 http://d.old.wanfangdata.com.cn/Periodical/jsjfzsjytxxxb200902017
[20]	Kaygin S, Bulut M M.Shape Recognition Using Attributed String Matching with Polygon Vertices as the Primitives[J]. Pattern Recognition Letters, 2002, 23(1-3): 287-294 doi: 10.1016/S0167-8655(01)00111-8
[21]	Huh Y, Yang S, Ga C, et al. Line Segment Confidence Region-Based String Matching Method for Map Conflation[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 78(4): 69-84 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=c50ee9984b99589dd79058238b7b9e92
[22]	Arkin E M, Chew L P, Huttenlocher D P, et al. An Efficiently Computable Metric for Comparing Polygonal Shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, 13(3): 209-216 doi: 10.1109/34.75509
[23]	Chui H, Rangarajan A.A New Point Matching Algorithm for Non-rigid Registration[J]. Computer Vision and Image Understanding, 2003, 89 (2-3):114-141 doi: 10.1016/S1077-3142(03)00009-2
[24]	刘凌佳, 朱道也, 朱欣焰, 等.基于MBR组合优化算法的多尺度面实体匹配方法[J].测绘学报, 2018, 47(5):652-662 http://d.old.wanfangdata.com.cn/Periodical/chxb201805012 Liu Lingjia, Zhu Daoye, Zhu Xinyan, et al. A Multi-scale Polygonal Object Matching Method Based on MBR Combinatorial Optimization Algorithm[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(5):652-662 http://d.old.wanfangdata.com.cn/Periodical/chxb201805012
[25]	Leordeanu M, Hebert M. A Spectral Technique for Correspondence Problems Using Pairwise Constraints[C]. The 10th IEEE International Confe-rence on Computer Vision, Beijing, China, 2005
[26]	罗国玮, 张新长, 齐立新, 等.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):1 285-1 292 http://d.old.wanfangdata.com.cn/Conference/8869641 Luo Guowei, Zhang Xinchang, Qi Lixin, et al. The Fast Positioning and Optimal Combination Method of Chang Vector Object[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(12):1 285-1 292 http://d.old.wanfangdata.com.cn/Conference/8869641
[27]	Wang Y, Chen D, Zhao Z, et al. A Back-Propagation Neural Network-Based Approach for Multi-represented Feature Matching in Update Propagation[J]. Transactions in GIS, 2015, 19(6):964-993 doi: 10.1111/tgis.12138
[28]	Rutzinger M, Rottensteiner F, Pfeifer N. A Comparison of Evaluation Techniques for Building Extraction from Airborne Laser Scanning[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2009, 2:11-20 doi: 10.1109/JSTARS.2009.2012488
[29]	Huh Y, Kim J, Lee J, et al. Identification of Multi-scale Corresponding Object-Set Pairs Between Two Polygon Datasets with Hierarchical Co-clustering[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014, 88(2):60-68 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=9f564aa5eb3ccdbfbbbeef9b950c54b0
[30]	许俊奎, 武芳, 朱健东, 等.相邻比例尺居民地匹配[J].武汉大学学报·信息科学版, 2014, 39(3):340-345 http://d.old.wanfangdata.com.cn/Periodical/whchkjdxxb200806014 Xu Junkui, Wu Fang, Zhu Jiandong, et al. A Multi-to-Multi Matching Algorithm Between Neighborhood Scale Settlement Data[J]. Geomatics and Information Science of Wuhan University, 2014, 39(3):340-345 http://d.old.wanfangdata.com.cn/Periodical/whchkjdxxb200806014
[31]	张贤达.矩阵分析与应用[M].北京:清华大学出版社, 2004 Zhang Xianda. Matrix Analysis and Applications[M]. Beijing: Tsinghua University Press, 2004
[32]	杨元喜.等价权原理——参数平差模型的抗差最小二乘解[J].测绘通报, 1994(6):33-35, 29 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199400002059 Yang Yuanxi. The Equivalent Weight Principle-Robust Least Squares Solution Estimation of Parameters Adjustment Model[J]. Bulletin of Surveying and Mapping, 1994(6):33-35, 29 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199400002059

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