基于栅格数据的模糊方向关系的研究
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摘要
方向关系是空间数据库中重要的空间关系之一，在图像数据库、多媒体系统和地理信息系统等领域都有着重要应用。而由于现实世界中人类在思维和认知上的模糊性，必然导致方向关系具有模糊性的特点。目前对于模糊性方向关系的研究相对较少，大多采用定性的方法进行精确描述。在这种情况下，本文对模糊性方向关系进行了深入的研究和探索。
首先，从方向区域具有模糊性的角度出发，将矢量数据栅格化方法引入方向关系描述中，提出了一种基于栅格数据的模糊方向关系描述模型。该模型首先将矢量数据栅格化，然后依次对每个栅格数据进行方向隶属度处理，通过分析目标对象中各栅格数据的方向隶属程度，实现了目标对象的模糊性方向关系描述。利用地理信息数据进行测试，实验结果验证了该方法的有效性和可行性。
其次，针对方向关系研究过程中容易忽略含有重要信息的离群数据的问题，提出了一种离群数据检索算法。通过对每一个栅格数据分配一个动态的权值，并在算法迭代中不断更新权值来发现离群数据。利用公式推导证明了该算法具有收敛性。将模糊方向关系描述模型与离群数据检索算法相结合，提出了一种离群模糊方向关系描述算法，并利用地理信息数据对算法进行测试，仿真结果表明，该算法在优化精度方面上有所提高。
最后，设计并实现地理信息方向关系分析系统设计与实现，系统主要实现了数据的栅格化、数据的预处理、离散数据的检测、方向关系描述、结果的可视化等功能。系统对地理信息数据进行实验，最终得到的分析结果所反映的规律符合实际地理情况。
Direction relation, which is one of the important spatial relations in spatialdatabase, is used widely in many domains, including GIS, multimedia system andimage database. But the direction relation is fuzzy because of the fuzziness ofgeographical objects themselves, the imprecision of geographical informationprocessing and the vagueness of mankind cognition about spatial direction relations,uncertainty is inherent property of direction relations. At present, the research ondirection relation is mainly based on qualitative method, while there is relatively littleresearch on fuzziness. Based on these, the description on fuzzy direction relationsbased on raster data are studied and explored.
First of all, the fuzzy direction relation model based on raster data is extended,the fuzzy direction relation model based on raster data is proposed by analyzing theproperty of raster data. At the same time, based on this model, the membership ofdirection relations based on raster data is calculated, the calculation result canrepresent as the target objects that pertain to each direction, and this kind ofcalculation result matches people’s cognitive habits precisely.
Secondly, as direction relation research process is easy to overlook the problemof discrete data, one kind of discrete data retrieval algorithm is produced.Discrete data retrieval algorithm assign a dynamic weight value for each discrete dataand continuously update the value of the raster data in the iteration algorithm to findthe discrete data. The algorithm is proved convergent by using a formula derivation.Using the geographical information data test discrete data retrieval algorithm,experiment results show that this algorithm is improved in optimizing the precision.
Finally, an experiment is performed to the description model based on the spatialdirection relations. From basic membership function and basic membership functionsof the choice of parameters and fuzzy objects, the present thesis makes a deep study tothe function of this model. Experimental results show that the model can reflect thefuzzy characteristics of direction relations in real world and is fit for the habit of the human mind’s cognition.
首先，从方向区域具有模糊性的角度出发，将矢量数据栅格化方法引入方向关系描述中，提出了一种基于栅格数据的模糊方向关系描述模型。该模型首先将矢量数据栅格化，然后依次对每个栅格数据进行方向隶属度处理，通过分析目标对象中各栅格数据的方向隶属程度，实现了目标对象的模糊性方向关系描述。利用地理信息数据进行测试，实验结果验证了该方法的有效性和可行性。
其次，针对方向关系研究过程中容易忽略含有重要信息的离群数据的问题，提出了一种离群数据检索算法。通过对每一个栅格数据分配一个动态的权值，并在算法迭代中不断更新权值来发现离群数据。利用公式推导证明了该算法具有收敛性。将模糊方向关系描述模型与离群数据检索算法相结合，提出了一种离群模糊方向关系描述算法，并利用地理信息数据对算法进行测试，仿真结果表明，该算法在优化精度方面上有所提高。
最后，设计并实现地理信息方向关系分析系统设计与实现，系统主要实现了数据的栅格化、数据的预处理、离散数据的检测、方向关系描述、结果的可视化等功能。系统对地理信息数据进行实验，最终得到的分析结果所反映的规律符合实际地理情况。
Direction relation, which is one of the important spatial relations in spatialdatabase, is used widely in many domains, including GIS, multimedia system andimage database. But the direction relation is fuzzy because of the fuzziness ofgeographical objects themselves, the imprecision of geographical informationprocessing and the vagueness of mankind cognition about spatial direction relations,uncertainty is inherent property of direction relations. At present, the research ondirection relation is mainly based on qualitative method, while there is relatively littleresearch on fuzziness. Based on these, the description on fuzzy direction relationsbased on raster data are studied and explored.
First of all, the fuzzy direction relation model based on raster data is extended,the fuzzy direction relation model based on raster data is proposed by analyzing theproperty of raster data. At the same time, based on this model, the membership ofdirection relations based on raster data is calculated, the calculation result canrepresent as the target objects that pertain to each direction, and this kind ofcalculation result matches people’s cognitive habits precisely.
Secondly, as direction relation research process is easy to overlook the problemof discrete data, one kind of discrete data retrieval algorithm is produced.Discrete data retrieval algorithm assign a dynamic weight value for each discrete dataand continuously update the value of the raster data in the iteration algorithm to findthe discrete data. The algorithm is proved convergent by using a formula derivation.Using the geographical information data test discrete data retrieval algorithm,experiment results show that this algorithm is improved in optimizing the precision.
Finally, an experiment is performed to the description model based on the spatialdirection relations. From basic membership function and basic membership functionsof the choice of parameters and fuzzy objects, the present thesis makes a deep study tothe function of this model. Experimental results show that the model can reflect thefuzzy characteristics of direction relations in real world and is fit for the habit of the human mind’s cognition.
引文
[1]谢昆青.空间数据库[M].北京:机械工业出版社, 2004: 1-141.
[2] R.H.Güting. An Introduction to Spatial Database Systems[J]. Information Science, 2005,3(4): 357-399.
[3]郭文格,汤志华,李庆耀.浅析GIS空间数据库[J].北京测绘, 2011, 13(2): 217-224.
[4] Deng Min, Liu Wenbao Li Junjie, et al. Computational Model of Spatial Direction Relationsin Vector GIS[J]. Journal Of Remote Sensing, 2006, 10(6): 821-828.
[5]肖乐斌,田永青,朱仲英. GIS前瞻性技术的若干应用研究[J].微型电脑应用, 2002,18(1): 9-17.
[6]谢宏全,崔旭升.数字地球概论课程改革的实践探索[J].测绘通报, 2009, 17(5):593-604.
[7]彭宇,雷苗,郭嘉.基于先验知识的移动通信话务量预测[J].电子学报, 2011, 39(1):72-85.
[8] C.Sun, D.Agrawal, A.E. Abbadi. Selectivity Estimation for Spatial Joins with GeometricSelections[C]//In the 8th International Conference on Extending Database Technology,Prague, 2002: 609-626.
[9] Abler R F. The National Science Foundation National Center for Geographic Informationand Analysis[J]. International Journal of Geographical Information Systems, 2008, 1(4):303-326.
[10]纪婉玉.地理空间数据库及其数据模型研究[D].武汉:中国地质大学博士学位论文,2010: 142-234.
[11]冯欣欣,李明昱,刘乾. ArcGIS空间数据库的创建及应用[J].西部探矿工程, 2011, 23(9):74-81.
[12]陈炳富,李成钢,徐峰.嵌入式GIS海量栅格数据快速处理技术与实现[J].测绘,2011 36(6): 1284-1289.
[13] Goyal, Kriegel H.P, Schneider R, et al. The R+-tree: An Efficient and RobustAccess Methodfor Points and Rectangles[C]//ACM SIGMOD, Atlantic City, 2001: 322-331.
[14]肖予钦,张巨,景宁.基于R树的方向关系查询处理[J].软件学报, 2004, 15(1): 148-167.
[15] Wang Jing, Jiang Gangwu, Guo Rui. Qualitative Detailed Description for Spatial directionRelations[J]. Remote Sensing and Spatial Information Sciences, 2008, 32(2): 237-240.
[16]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): 241-254.
[17]郝忠孝,吴海燕.基于Vague集的不确定方向查询[J].哈尔滨理工大学学报, 2010 15(4):964-975.
[18]何云斌,边健.空间推理中方向关系模型的研究[J].计算机与数字工程, 2010 38(4):749-754.
[19]刘永山,成雪琴.基于坐标映射模型的方向关系一致性检验[J].计算机工程,2011 37(16): 1017-1024.
[20] Egenhofer M, Franzosa R. V Point-Set Topological Spatial Relations[J]. International Journalof Geographical Information Systems, 2001, 5(2): 161-174.
[21]郝忠孝,王玉东,何云斌.空间数据库平面线段近邻查询问题研究[J].计算机研究与发展, 2008, 45(9): 584-590.
[22] Guo P, Jia S Y, Li D.The expression and reasoning of spatial direction relations based onlattice arrays[C]//2007 International Conference on Intelligent Systems and KnowledgeEngineering (ISKE 2007), Chengdu, China, 2007: 2415-2426.
[23] Esterline.A.C, G.Dozier. Fuzzy spatial reasoning[C]//Proceedings of the International FuzzySystems Association World Congress, IFSA’97, 2007: 162-167.
[24]申世群,刘大有,王生生.基于草图的空间数据检索研究[J].电子学报, 2010 38(8):571-580.
[25]李松,郝忠孝.空间关系推理的研究方法[J].计算机工程与应用, 2009, 45(19): 17-21.
[26] D.Papadias, M.Egenhofer, J.Sharma. Hierarchical Reasoning about DirectionRelations[C]//Proceedings of the 4th ACM International Workshop on Advances inGeographic Information Systems, Rockville, 2004: 105-112.
[27]付迎春,袁修孝,聂启祥.扩展的锥形方向关系查询处理方法[J].计算机工程, 2008,34(15): 1187-1194.
[28] MacQueen J. Some methods for classification and analysis of multivariateobservations[J].Proceedings of the Fifth Berkeley Symposium on Mathematical. 1997, 7(1): 281-297.
[29]杜世宏,王桥,杨一鹏.空间方向关系模糊描述[J].计算机辅助设计与图形学学报,2005 17(8): 685-697.
[30] MacQueen J. Some methods for classification and analysis of multivariateobservations[J].Proceedings of the Fifth Berkeley Symposium on Mathematical. 2002, 3(1): 281-297.
[31] Lin P L, Tan W H. An Efficient Method for the Retrieval of Objects by Topological Relationsin Spatial Database Systems[J]. Information Processing and Management. 2008, 9(4):543-559.
[32]闫浩文,郭仁忠.空间方向关系基础性问题研究[J].测绘学报, 2002, 31(4): 295-304.
[33] Haar R.Computational models of spatial relations[J]. Computer Science, 1976, 18(2):487-496.
[34] D.Peuquet, C.Zhan. An Algorithm to Determine the Directional Relationship BetweenArbitrarily-shaped Polygons in the plane[J]. Pattern Recognition, 1987, 20(1):65-74.
[35]张德胜,冯登国,陈驰.一种面向空间数据库矢量数据的授权模型与实现方法[J].计算机研究与发展, 2011, 48(8): 873-883.
[36]闫浩文,郭仁忠.基于Voronoi图的空间方向关系形式化描述模型[J].武汉大学学报,2003, 28(4): 846-853.
[37]董轶群,刘大有,王芳.一种基于MBR的不确定区域间方向关系建模方法[J].电子学报,2011, 39(2): 157-167.
[38] Papadias D, Theodoridis Y, Sellis T. The retrieval of direction relations using r-trees[C]// the5th International Conference on Database and Expert Systems Applications, Greece NewYork, Springer-Verlag, 1994: 173-182.
[39] P.W.Huang, Y.R.Jean. Using 2D C+-String as Spatial Knowledge Representation for ImageDatabase Systems[J]. Pattern Recogintion, 1998, 30(10): 1249-1257.
[40] Goyal R K. Similarity assessment for cardinal directions between extended spatial objects[D].Ph.D. Thesis of Maine University, 2000.
[41] Glasgow, D.Papadias. Computational Imagery[J]. Cognitive Science, 2002, 16(3): 109-114.
[42] Cicerone, P.D.Felice. Cardinal relations between regions with a broad boundary[C]//Proceedings of the 8th ACM International Symposium on Advances in GeographicInformation Systems, Washington. 1999: 15-20.
[43] Santos MY, Amaral LA. Geo-spatial data mining in the analysis of a demographic database[J].Soft Computing, 2002, 9(5): 374-384.
[44]杨存建,王琴,任平.基于空间数据库的地类知识的发现[J].遥感技术与应用, 2010,25(5): 482-490.
[45]邓瑞芝,祝胜林.空间数据库的访问控制技术[J].计算机与现代化, 2010, 13(1):434-339.
[46] Mukerjee A, Joe G. A qualitative model for space[C]//Proceedings 8th National Conferenceon Artificial Intelligence, Boston, 1990: 721-727.
[47] Glasgow, D.Papadias. Computational Imagery[J]. Cognitive Science, 1998, 16(3): 109-114.
[48]张德胜,冯登国.一种地理空间数据库矢量数据授权与实现[J].计算机研究与发展,2010, 47(5): 1014-1021.
[49]卢廷军,黄明.海量栅格数据空间索引与存储的研究[J].测绘通报, 2010 10(3): 87-99.
[50]苏程,周祖煜,倪广翼.基于像元有向边的栅格数据扫描线矢量化方法[J].计算机辅助设计与图形学学报, 2011 23(7): 674-683.
[51] Keller A. Fuzzy clustering with outliers[D]. In Proc of the NAFIPS00, 2000:143-147.
[2] R.H.Güting. An Introduction to Spatial Database Systems[J]. Information Science, 2005,3(4): 357-399.
[3]郭文格,汤志华,李庆耀.浅析GIS空间数据库[J].北京测绘, 2011, 13(2): 217-224.
[4] Deng Min, Liu Wenbao Li Junjie, et al. Computational Model of Spatial Direction Relationsin Vector GIS[J]. Journal Of Remote Sensing, 2006, 10(6): 821-828.
[5]肖乐斌,田永青,朱仲英. GIS前瞻性技术的若干应用研究[J].微型电脑应用, 2002,18(1): 9-17.
[6]谢宏全,崔旭升.数字地球概论课程改革的实践探索[J].测绘通报, 2009, 17(5):593-604.
[7]彭宇,雷苗,郭嘉.基于先验知识的移动通信话务量预测[J].电子学报, 2011, 39(1):72-85.
[8] C.Sun, D.Agrawal, A.E. Abbadi. Selectivity Estimation for Spatial Joins with GeometricSelections[C]//In the 8th International Conference on Extending Database Technology,Prague, 2002: 609-626.
[9] Abler R F. The National Science Foundation National Center for Geographic Informationand Analysis[J]. International Journal of Geographical Information Systems, 2008, 1(4):303-326.
[10]纪婉玉.地理空间数据库及其数据模型研究[D].武汉:中国地质大学博士学位论文,2010: 142-234.
[11]冯欣欣,李明昱,刘乾. ArcGIS空间数据库的创建及应用[J].西部探矿工程, 2011, 23(9):74-81.
[12]陈炳富,李成钢,徐峰.嵌入式GIS海量栅格数据快速处理技术与实现[J].测绘,2011 36(6): 1284-1289.
[13] Goyal, Kriegel H.P, Schneider R, et al. The R+-tree: An Efficient and RobustAccess Methodfor Points and Rectangles[C]//ACM SIGMOD, Atlantic City, 2001: 322-331.
[14]肖予钦,张巨,景宁.基于R树的方向关系查询处理[J].软件学报, 2004, 15(1): 148-167.
[15] Wang Jing, Jiang Gangwu, Guo Rui. Qualitative Detailed Description for Spatial directionRelations[J]. Remote Sensing and Spatial Information Sciences, 2008, 32(2): 237-240.
[16]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): 241-254.
[17]郝忠孝,吴海燕.基于Vague集的不确定方向查询[J].哈尔滨理工大学学报, 2010 15(4):964-975.
[18]何云斌,边健.空间推理中方向关系模型的研究[J].计算机与数字工程, 2010 38(4):749-754.
[19]刘永山,成雪琴.基于坐标映射模型的方向关系一致性检验[J].计算机工程,2011 37(16): 1017-1024.
[20] Egenhofer M, Franzosa R. V Point-Set Topological Spatial Relations[J]. International Journalof Geographical Information Systems, 2001, 5(2): 161-174.
[21]郝忠孝,王玉东,何云斌.空间数据库平面线段近邻查询问题研究[J].计算机研究与发展, 2008, 45(9): 584-590.
[22] Guo P, Jia S Y, Li D.The expression and reasoning of spatial direction relations based onlattice arrays[C]//2007 International Conference on Intelligent Systems and KnowledgeEngineering (ISKE 2007), Chengdu, China, 2007: 2415-2426.
[23] Esterline.A.C, G.Dozier. Fuzzy spatial reasoning[C]//Proceedings of the International FuzzySystems Association World Congress, IFSA’97, 2007: 162-167.
[24]申世群,刘大有,王生生.基于草图的空间数据检索研究[J].电子学报, 2010 38(8):571-580.
[25]李松,郝忠孝.空间关系推理的研究方法[J].计算机工程与应用, 2009, 45(19): 17-21.
[26] D.Papadias, M.Egenhofer, J.Sharma. Hierarchical Reasoning about DirectionRelations[C]//Proceedings of the 4th ACM International Workshop on Advances inGeographic Information Systems, Rockville, 2004: 105-112.
[27]付迎春,袁修孝,聂启祥.扩展的锥形方向关系查询处理方法[J].计算机工程, 2008,34(15): 1187-1194.
[28] MacQueen J. Some methods for classification and analysis of multivariateobservations[J].Proceedings of the Fifth Berkeley Symposium on Mathematical. 1997, 7(1): 281-297.
[29]杜世宏,王桥,杨一鹏.空间方向关系模糊描述[J].计算机辅助设计与图形学学报,2005 17(8): 685-697.
[30] MacQueen J. Some methods for classification and analysis of multivariateobservations[J].Proceedings of the Fifth Berkeley Symposium on Mathematical. 2002, 3(1): 281-297.
[31] Lin P L, Tan W H. An Efficient Method for the Retrieval of Objects by Topological Relationsin Spatial Database Systems[J]. Information Processing and Management. 2008, 9(4):543-559.
[32]闫浩文,郭仁忠.空间方向关系基础性问题研究[J].测绘学报, 2002, 31(4): 295-304.
[33] Haar R.Computational models of spatial relations[J]. Computer Science, 1976, 18(2):487-496.
[34] D.Peuquet, C.Zhan. An Algorithm to Determine the Directional Relationship BetweenArbitrarily-shaped Polygons in the plane[J]. Pattern Recognition, 1987, 20(1):65-74.
[35]张德胜,冯登国,陈驰.一种面向空间数据库矢量数据的授权模型与实现方法[J].计算机研究与发展, 2011, 48(8): 873-883.
[36]闫浩文,郭仁忠.基于Voronoi图的空间方向关系形式化描述模型[J].武汉大学学报,2003, 28(4): 846-853.
[37]董轶群,刘大有,王芳.一种基于MBR的不确定区域间方向关系建模方法[J].电子学报,2011, 39(2): 157-167.
[38] Papadias D, Theodoridis Y, Sellis T. The retrieval of direction relations using r-trees[C]// the5th International Conference on Database and Expert Systems Applications, Greece NewYork, Springer-Verlag, 1994: 173-182.
[39] P.W.Huang, Y.R.Jean. Using 2D C+-String as Spatial Knowledge Representation for ImageDatabase Systems[J]. Pattern Recogintion, 1998, 30(10): 1249-1257.
[40] Goyal R K. Similarity assessment for cardinal directions between extended spatial objects[D].Ph.D. Thesis of Maine University, 2000.
[41] Glasgow, D.Papadias. Computational Imagery[J]. Cognitive Science, 2002, 16(3): 109-114.
[42] Cicerone, P.D.Felice. Cardinal relations between regions with a broad boundary[C]//Proceedings of the 8th ACM International Symposium on Advances in GeographicInformation Systems, Washington. 1999: 15-20.
[43] Santos MY, Amaral LA. Geo-spatial data mining in the analysis of a demographic database[J].Soft Computing, 2002, 9(5): 374-384.
[44]杨存建,王琴,任平.基于空间数据库的地类知识的发现[J].遥感技术与应用, 2010,25(5): 482-490.
[45]邓瑞芝,祝胜林.空间数据库的访问控制技术[J].计算机与现代化, 2010, 13(1):434-339.
[46] Mukerjee A, Joe G. A qualitative model for space[C]//Proceedings 8th National Conferenceon Artificial Intelligence, Boston, 1990: 721-727.
[47] Glasgow, D.Papadias. Computational Imagery[J]. Cognitive Science, 1998, 16(3): 109-114.
[48]张德胜,冯登国.一种地理空间数据库矢量数据授权与实现[J].计算机研究与发展,2010, 47(5): 1014-1021.
[49]卢廷军,黄明.海量栅格数据空间索引与存储的研究[J].测绘通报, 2010 10(3): 87-99.
[50]苏程,周祖煜,倪广翼.基于像元有向边的栅格数据扫描线矢量化方法[J].计算机辅助设计与图形学学报, 2011 23(7): 674-683.
[51] Keller A. Fuzzy clustering with outliers[D]. In Proc of the NAFIPS00, 2000:143-147.