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
|
摘要
随着地理信息系统(下文简称GIS)技术的不断发展和广泛应用,多源、多尺度、多时相空间数据的快速更新和集成应用也成为一种必然趋势,对GIS空间数据库更新与可持续发展的研究与探讨已经成为迫在眉睫的任务,矢量空间数据的匹配技术也已成为迫切需要解决的关键问题。由于同一地区的矢量空间数据往往被多个部门重复采集或同一部门不同时间采集,这些数据在几何位置、几何形状、拓扑结构、几何精度、属性详细程度、编码方案、语义表达以及实体空间关系等方面不尽相同,使得数据的合并与共享非常困难。为了得到精度较高、属性信息更丰富、地图范围更大的高质量的空间数据,就需要对不同的地图数据库之间进行实体匹配,建立实体之间的连接,并在此基础上进行矢量空间数据融合处理,解决数据之间的几何、拓扑和语义的不一致性问题。
本文对面实体的几何特征描述方法进行了深入的研究,并探讨了面实体在多尺度下的特征变化及其匹配方法,研究了实体匹配技术在数据库更新中的应用,给出了合理可行的多尺度实体匹配方法和基于要素级数据更新方案。
首先,本文针对面状矢量数据的几何特征及矢量要素类型的不同,设计了四种几何描述方法,分别为重心射线法、凸包法、正切空间法和离散几何矩法。重心射线法和凸包法可以对面实体进行粗匹配,具有算法简单,速度快的特点。为了精确地描述面实体几何特征,同时最大限度保持实体的原有信息,本文提出了基于正切空间的特征描述方法,将面实体通过正切空间的方式进行描述,通过形状相似度距离对匹配实体进行几何相似度计算,实验证明,利用正切空间的思想描述面实体,描述方法简单,存储计算量小,其描述函数对目标具有形状不变性,对复杂面实体具有匹配准确的特点。本文还提出了一种适用于矢量图形的形状不变几何矩描述方法,将传统的基于图像像素点的离散不变矩改进为由面实体轮廓构建的三角形矩累加,解决了不等间距离散矢量数据的带来的问题,提高了匹配的准确率。
其次,考虑对跨尺度的一对一实体匹配,通过Douglas-Peucker算法对面实体建立层次模型和然后再用角度演算算法对形状分段后的图形进行简化,将简化后实体再进行实体匹配,提高了匹配的正确率。针对多尺度匹配中的一对多匹配,提出了一种基于外扩和内收缓冲区聚类方法的匹配模型,通过缓冲区合并算法提取多个面实体的外轮廓特征,再与源匹配实体进行几何匹配。
此外,还研究了基于面与面之间的基本空间拓扑关系模型,并通过建立三级混合索引的方式对空间索引进行优化,通过固定格网索引对候选匹配集进行快速准确查找,避免了叠加分析等计算操作,并最大限度的缩小了匹配集的范围。
最后,设计了一整套基于实体匹配的要素级数据库更新处理流程,通过基于权重及规则的相似性计算模型,解决了多种要素类同时进行匹配等复杂情况下的面实体匹配问题；通过实体匹配后的相似度结果来判断实体是否需要更新,并将已更新实体放入历史数据库中,方便要素的历史管理。并通过地理对象的建立,来解决多尺度下的联动更新问题。
With the development and wide application Geographic Information System (hereinafter referred to as GIS) technology, integration and instant (quickly) updating of multi-source, multi-scale, multi-temporal spatial data, has become an inevitable trend quickly update and integration of applications. Thus quickly updating and sustainable development of GIS spatial database has become an urgent task, and the vector spatial data matching technology is the key issue to be addressed. Since Vector Spatial Data of the same region are usually repeatedly collected by a number of departments or the same departments but at different times, the data varies in the geometry position, geometry shape, topology structure, geometric accuracy, and level of attribute detail, coding schemes, semantic expression and the relationship between entity spaces. This makes the consolidation and sharing of the data become very difficult. In order to obtain spatial data of higher accuracy, richer attribute information and wider coverage of mapping with high quality, the procedure of entity matching is very necessary between different map databases to establish the relationship between entities. And on this basis, fusion of vector spatial data can be handled to solve geometric, topological, semantic inconsistencies between the data.
This thesis makes thorough research on methods of entities matching, and explores changes of the surface entities features in a multi-scale and its matching methods. In Addition, this thesis illustrates applications of entities matching in the database updating. This thesis also proposes reasonable and feasible methods of multi-scale entities matching and schemes of element-level data updating.
Firstly, according to differences of geometric features of surface vector data and type of vector elements, three geometric matching methods are designed, that is, orientation coding method, tangent space method and the discrete geometric moments. Orientation coding method applies for matching of simple and regular surface entities at small and medium scale (such as 1:50000 buildings, streets, etc.), with a high processing speed. In order to identify the geometric characteristics(features) of surface entities, while to maintain more information about the original attribute of the entities as possible, tangent space method(matching method on the tangent space) is proposed. This method expresses (projects) shapes of surface entities in the tangent space, and calculates geometric similarity with adaptive similarity of shapes. Experimental results show that describing surface entities in tangent plane, feature extraction method is simple with little memory, and the coding has the characteristics of shape invariance. Additionally, this methods obtains accurate matching when applied to complex surface entities at small and medium scales. When there is variance in scales (When there is a certain span of time scales), this thesis introduces improved shape invariant geometric moments to the process of matching. By adjusting the traditional discrete HU moment invariants based on image pixels to moments constructed by triangles witch are established by outline of surface entities, matching accuracy has been improved.
Secondly, considering the span of a certain scale of one to one entity matching, hierarchical model of surface entities can be built with the Douglas-Peucker algorithm and angle calculation algorithm of entities, first extract the corresponding physical characteristics, and then a physical match and improve the matching accuracy. For one to many matches in multi-scale matching, this thesis puts forward a matching model based on clustering through expanding and contracting the buffer zone. This method extracts features of mathematical morphology operators and tangent space extract multiple surfaces merging algorithm outline entities attributes, and on this basis, geometric matching with the source matching entities will be performed.
In addition, this thesis also researches on the basic topological relationship between surface entities, and in order to address the problem of unable to distinguish entities in geometric matching, a match method based on topological relationship of the overall environment is proposed. Topological matching happens according to the hierarchical relationship between the matching entities with the environment around. In the case of semantic multi-scale matching in multi-scale matching, semantic similarity is calculated through the establishment of semantic encoding and hierarchical properties of ontology structure and similarity of attributes, such as numeric and text strings can be calculated through the semantic relationship between entities.
Finally, this thesis designs the whole processes of updating elemental database based on entity matching, and with index-based grid searching method, efficiency of searching candidate matching set during surface entities matching and efficiency of spatial analysis have been greatly improved. By adopting similarity calculation model based on weights and rule-based, surface entities matching problems in the complex situations with diverse elements are solved. Additionally, the similarity gained during the entities matching can be used to decide whether to update the database or not, and updated entities are settled down in historical database which facilitate elements management.
本文对面实体的几何特征描述方法进行了深入的研究,并探讨了面实体在多尺度下的特征变化及其匹配方法,研究了实体匹配技术在数据库更新中的应用,给出了合理可行的多尺度实体匹配方法和基于要素级数据更新方案。
首先,本文针对面状矢量数据的几何特征及矢量要素类型的不同,设计了四种几何描述方法,分别为重心射线法、凸包法、正切空间法和离散几何矩法。重心射线法和凸包法可以对面实体进行粗匹配,具有算法简单,速度快的特点。为了精确地描述面实体几何特征,同时最大限度保持实体的原有信息,本文提出了基于正切空间的特征描述方法,将面实体通过正切空间的方式进行描述,通过形状相似度距离对匹配实体进行几何相似度计算,实验证明,利用正切空间的思想描述面实体,描述方法简单,存储计算量小,其描述函数对目标具有形状不变性,对复杂面实体具有匹配准确的特点。本文还提出了一种适用于矢量图形的形状不变几何矩描述方法,将传统的基于图像像素点的离散不变矩改进为由面实体轮廓构建的三角形矩累加,解决了不等间距离散矢量数据的带来的问题,提高了匹配的准确率。
其次,考虑对跨尺度的一对一实体匹配,通过Douglas-Peucker算法对面实体建立层次模型和然后再用角度演算算法对形状分段后的图形进行简化,将简化后实体再进行实体匹配,提高了匹配的正确率。针对多尺度匹配中的一对多匹配,提出了一种基于外扩和内收缓冲区聚类方法的匹配模型,通过缓冲区合并算法提取多个面实体的外轮廓特征,再与源匹配实体进行几何匹配。
此外,还研究了基于面与面之间的基本空间拓扑关系模型,并通过建立三级混合索引的方式对空间索引进行优化,通过固定格网索引对候选匹配集进行快速准确查找,避免了叠加分析等计算操作,并最大限度的缩小了匹配集的范围。
最后,设计了一整套基于实体匹配的要素级数据库更新处理流程,通过基于权重及规则的相似性计算模型,解决了多种要素类同时进行匹配等复杂情况下的面实体匹配问题；通过实体匹配后的相似度结果来判断实体是否需要更新,并将已更新实体放入历史数据库中,方便要素的历史管理。并通过地理对象的建立,来解决多尺度下的联动更新问题。
With the development and wide application Geographic Information System (hereinafter referred to as GIS) technology, integration and instant (quickly) updating of multi-source, multi-scale, multi-temporal spatial data, has become an inevitable trend quickly update and integration of applications. Thus quickly updating and sustainable development of GIS spatial database has become an urgent task, and the vector spatial data matching technology is the key issue to be addressed. Since Vector Spatial Data of the same region are usually repeatedly collected by a number of departments or the same departments but at different times, the data varies in the geometry position, geometry shape, topology structure, geometric accuracy, and level of attribute detail, coding schemes, semantic expression and the relationship between entity spaces. This makes the consolidation and sharing of the data become very difficult. In order to obtain spatial data of higher accuracy, richer attribute information and wider coverage of mapping with high quality, the procedure of entity matching is very necessary between different map databases to establish the relationship between entities. And on this basis, fusion of vector spatial data can be handled to solve geometric, topological, semantic inconsistencies between the data.
This thesis makes thorough research on methods of entities matching, and explores changes of the surface entities features in a multi-scale and its matching methods. In Addition, this thesis illustrates applications of entities matching in the database updating. This thesis also proposes reasonable and feasible methods of multi-scale entities matching and schemes of element-level data updating.
Firstly, according to differences of geometric features of surface vector data and type of vector elements, three geometric matching methods are designed, that is, orientation coding method, tangent space method and the discrete geometric moments. Orientation coding method applies for matching of simple and regular surface entities at small and medium scale (such as 1:50000 buildings, streets, etc.), with a high processing speed. In order to identify the geometric characteristics(features) of surface entities, while to maintain more information about the original attribute of the entities as possible, tangent space method(matching method on the tangent space) is proposed. This method expresses (projects) shapes of surface entities in the tangent space, and calculates geometric similarity with adaptive similarity of shapes. Experimental results show that describing surface entities in tangent plane, feature extraction method is simple with little memory, and the coding has the characteristics of shape invariance. Additionally, this methods obtains accurate matching when applied to complex surface entities at small and medium scales. When there is variance in scales (When there is a certain span of time scales), this thesis introduces improved shape invariant geometric moments to the process of matching. By adjusting the traditional discrete HU moment invariants based on image pixels to moments constructed by triangles witch are established by outline of surface entities, matching accuracy has been improved.
Secondly, considering the span of a certain scale of one to one entity matching, hierarchical model of surface entities can be built with the Douglas-Peucker algorithm and angle calculation algorithm of entities, first extract the corresponding physical characteristics, and then a physical match and improve the matching accuracy. For one to many matches in multi-scale matching, this thesis puts forward a matching model based on clustering through expanding and contracting the buffer zone. This method extracts features of mathematical morphology operators and tangent space extract multiple surfaces merging algorithm outline entities attributes, and on this basis, geometric matching with the source matching entities will be performed.
In addition, this thesis also researches on the basic topological relationship between surface entities, and in order to address the problem of unable to distinguish entities in geometric matching, a match method based on topological relationship of the overall environment is proposed. Topological matching happens according to the hierarchical relationship between the matching entities with the environment around. In the case of semantic multi-scale matching in multi-scale matching, semantic similarity is calculated through the establishment of semantic encoding and hierarchical properties of ontology structure and similarity of attributes, such as numeric and text strings can be calculated through the semantic relationship between entities.
Finally, this thesis designs the whole processes of updating elemental database based on entity matching, and with index-based grid searching method, efficiency of searching candidate matching set during surface entities matching and efficiency of spatial analysis have been greatly improved. By adopting similarity calculation model based on weights and rule-based, surface entities matching problems in the complex situations with diverse elements are solved. Additionally, the similarity gained during the entities matching can be used to decide whether to update the database or not, and updated entities are settled down in historical database which facilitate elements management.
引文
[1]艾廷华,毋河海.相邻多边形共享边界的一致化改正[J].武汉测绘科技大学学报,2000,Vo1.25.No.5：426—431
[2]艾廷华,帅赟,李精忠.基于形状相似性识别的空间查询[J].测绘学报,2009,Vol.38,No.4：356—362
[3]边馥苓.地理信息系统原理和方法[M].北京：测绘出版社,1996
[4]陈军,胡云岗,赵仁亮,等.道路数据缩编更新的自动综合方法研究[J].武汉大学学报(信息科学版),2007,32(11)：1022-1027
[5]陈建春Visual C++开发GIS系统[M],第二版.北京：电子工业出版社,2004：549-564.
[6]陈玉敏,龚健雅,史文中.多尺度道路网的距离匹配算法研究[J].测绘学报,2007,Vol.36,No.1：84-90
[7]崔铁军,郭黎.多源地理空间矢量数据集成与融合方法探讨[J].测绘科学技术学报,2007,Vol.24,No.1：1-4
[8]杜世宏,王桥,秦其明.空间关系模糊描述与组合推理[M].北京：科学出版社,2007
[9]范大昭,张永生,雷蓉,郭海涛.GIS数据自动更新技术的研究[J].测绘科学,2005,6,Vo1.30.No.3：15-18
[10]付仲良,吴建华.多比例尺空间数据库更新技术研究.武汉大学学报.信息科学版.2007,12,Vo1.32,No.12：1115—1118
[11]付仲良,邵世维.复杂面状矢量要素快速形状匹配方法.[J].测绘通报,2011,Vol.3：26-28
[12]付仲良,邵世维,童春芽.基于正切空间的多尺度面实体形状匹配[J]计算机工程.2010,17,Vol.36,No.17：216-218
[13]龚健雅.GIS中面向对象时空数据模型[J].测绘学报,1997,11,Vol.26,No.4：289—298
[14]龚健雅.地理信息系统基础.北京：科学出版社,2001
[15]郭黎,崔铁军,吴正升.多源数字地图融合技术问题的研究[J].海洋测绘,2000,(2)：22—25
[16]郭庆胜,杜晓初,刘浩.空间拓扑关系定量描述与抽象方法研究[J].测绘学报,2005,34(2)：123-128
[17]郭庆胜,杜晓初,闫卫阳.地理空间推理.北京：科学出版社,2006
[18]郭仁忠.空间分析[M].武汉：武汉测绘科技大学出版社,1997
[19]郭仁忠,闫浩文.空间方向关系基础性问题研究[J].测绘学报,2001,31(4)201—207
[20]郝燕玲,唐文静,赵玉新,李宁.基于空间相似性的面实体匹配算法研究[J].测绘学报,2008,37(4)501-506
[21]胡久乡,何松,锋瑜.空间数据库网格索引机制的最优划分[J].计算机学报,2002,25,Vo1.11：1227-1230
[22]晋耀红.基于语境框架的文本相似度计算[J].计算机工程与应用,2004,(16)：36—39
[23]金博,史彦军,滕弘飞.基于语义理解的文本相似度算法[J].大连理工大学学报,2005,Vol.45.No.2：291—297
[24]金文华,何涛,刘晓全等.基于有序简单多边形的平面点集凸包快速求取算法[J].计算机学报,1998,21(6)：533—539.
[25]孔祥玲,欧斌.地形图缩编技术的探讨[J].科技资讯,2007,No.12：2—2
[26]李芳玉,潘懋,朱雷.三维缓冲体生成栅格算法研究[J].计算机辅助设计与图形学学报,2005,17(9)：1928-1932.
[27]李科,杜琳.基于膨胀算法的缓冲区分析的设计与实现[J].测绘学院学报,2005,22(3)：229—231.
[28]罗晓燕,袁燕岩,蔡恒刚,黄德咏.大比例尺地形图数据库数据更新一体化技术综述[J].北京测绘,2004,(2)：20—23
[29]罗德安,廖丽琼.基于粗分格网的空问对象范围索引[J].西南交通大学学报.2003,38(3)：271-275
[30]刘东琴,苏山舞.多空间数据库位置匹配方法及其应用[J].测绘科学,2005,Vol.30,No.2：78—81
[31]刘大杰,史文中等.空间误差处理的理论和方法[M].上海：上海科学技术文献出版社,1998
[32]刘宏中.一种基于像素标识的笔画细化新方法[J].华中科技大学学报(自然科学版),2002,30(3)：80—82.
[33]刘宏中,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),2005,33(4)：13—16.
[34]刘万增,赵仁亮.水系要素更新中空间冲突的自动检测研究.中国地理信息系统协会第八届年会论文集,2004年11月,北京：145—152
[35]刘万增,陈军.循环经济GIS数据库空间冲突的确认方法研究[J].地球信息科学,2007,Vol.9.No.1：78-83
[36]刘万增,陈军,赵仁亮.基于平面扫描算法的空间冲突检测方法.2004年两岸四地地理信息系统发展研讨论文集,2004年12月,香港
[37]刘湘南,黄方,王平等.GIS空间分析原理与方法.北京：科学出版社,2005
[38]刘勇,李成名.城市基础空间数据库更新方法研究[J].测绘科学,2006,7,Vol.31,No.4：103—106
[39]刘志勇.城市地图数据库合并中的面实体匹配方法研究[D].南京：河海大学,2006,6
[40]罗德安,廖丽琼.基于粗分格网的空间对象范围索引[J].西南交通大学学报.2003,38(3)：271—275.
[41]李三玉.GIS图形数据更新解决方案[J].现代计算机,2005(10)：109—111
[42]李德仁,龚健雅,张桥平.论地图数据库合并技术[J].测绘科学,2004,Vol.29,No.1：1-4
[43]李德仁,关泽群.空间信息系统的集成与实现[M].武汉：武汉测绘科技大学出版社,2000
[44]李波.城市基础地理信息系统矢量数据更新研究[D].南京师范大学,2006
[45]毛定山,崔先国,李行,吴哲辉.简单多边形集凸包的快速算法.工程图学学报,2007,28(6).
[46]孟妮娜,周校东.固定格网划分的空间索引的实现技术[J].北京测绘.2003,1：7—11
[47]潘谦红,王炬,史忠植.基于属性论的文本相似度计算[J].计算机学报,1999,Vol.22,No.6：651—655
[48]潘瑜春,钟耳顺,赵春江.GIS空间数据库的更新技术[J].地球信息科学,2004,6(1)：36—39
[49]邱建华,唐学兵,黄华国.一种基于四叉树和R*树的索引结构—Q R*树[J].计算机应用.2003,23(8)：124-126,152
[50]任艳,易宝林,陈佳丽.基于规则的空间一致性维护[J].计算机工程,2007,Vol.33,No.19：93—95
[51]舒红,陈军,杜道生,周勇前.面向对象的时空数据模型[J].武汉测绘科技大学学报,1997,9,Vol.22,No.3：229-232
[52]帅赞,艾廷华,帅海燕,倪琳.基于形状模板匹配的多边形查询[J].武汉大学学报(信息科学版),2008,Vo1.33,No.12：1267—1270
[53]宋关福,钟耳顺,刘纪远,肖乐斌.多源空间数据无缝集成研究[J].地理科学进展,2000,6,Vol.19,No.2：110—115
[54]苏山舞,于荣花,沈涛,刘东琴,王荣彬.全国1：1000000数据库建设与更新[J].地理信息世界,2003,4,Vol.1,No.2：21-25
[55]商瑶玲,王东华,李莉.论全国1：250000数据库的建立与更新[J]地理信息世界,2003,4,Vol.1,No.2：16-20
[56]史杏荣,孙贞寿,曹爱军.基于固定网格划分和面向类对象的四分树空间索引机制制[J]小型微型计算机系统.1998,19(10)：24—31
[57]谭建荣,岳小莉,陆国栋.图形相似的基本原理、方法及其在结构模式识别中的应用[J].计算机学报,2002,9,Vol.25,No.9：959—967
[58]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,Vol.36,No.2：210-217
[59]王斌,舒华忠,施朝健,罗立民.一种基于轮廓线的形状描述与匹配方法.电子与信息学报,2008,30(4)：949-952.
[60]武芳.关系处理中要素重叠的自动判别[J].测绘学院学报,1997,3,Vol.14,No.1：43-46
[61]邬伦,刘瑜,张晶等.地理信息系统一原理、方法和应用.北京：科学出版社,2001
[62]王琴,李建辉.GIS空间多源数据集成模式探讨[J].黄河水利职业技术学院学报,2007,1,Vol.19,No.1：46-47
[63]王辉连,武芳,张琳琳,邓红艳.数学形态学和模式识别在建筑物多边形化简中的应用.测绘学报,2005,34(3)：269-276.
[64]汪嘉业,刘鼎元.对平面简单多边形求凸包的线性时间算法[J].计算机学报,1989,(1)：38-43.
[65]王晓峰,黄德双等叶片图像特征提取与识别技术的研究[J].中国科学院合肥智能机械研究所,2006.vol.42,No.3：190-193
[66]王育红,陈军.基于实例的GIS数据库模式匹配方法[J].武汉大学学报(信息科学版),2008年1月,Vol.33,No.1：46-50
[67]毋河海.关于GIS缓冲区的建立问题[J].武汉测绘科技大学学报,1997,22(4)：358-365.
[68]吴飞,蔡胜渊,郭同强,庄越挺.三角形约束下的图像特征点匹配方法.测绘学报[J].2010,22(3)：503-510
[69]吴立新,史文中3DGIS与3DGMS中的空间构模技术[J].地理与地理信息科学,2003,19(1)：209-215
[70]肖伟器,冯玉才.空间对象数据库的网格索引机制[J].计算机学报,1994,17(10)：736-742
[71]于桂芹,郭淑贤,赵立军.国家1：50000地形数据库更新工程项目的研究[J].测绘与空间地理信息,2007,4,Vol.30,No.2：125-127
[72]张桥平,李德仁,龚健雅.地图合并技术[J].测绘通报,2001,No.9：6-8
[73]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,Vol.8,No.2：107-112
[74]张桥平.地图数据库实体匹配与合并技术研究[D].武汉：武汉大学,2002
[75]张宏,温永宁,刘爱利等.地理信息系统算法基础.北京：科学出版社,2006
[76]赵仁亮,刘万增.利用空间关系检测数据更新中空间冲突.青年科学家论坛第九十二次活动论文集,2004年8月,北京
[77]张保钢,袁燕岩.城市大比例尺地形图数据库中地物变化的自动发现[J].武汉大学学报.信息科学版,2005,7,Vol.30,No.7：640-642
[78]曾衍伟.矢量GIS数据位置精度评价[J].测绘信息与工程,2002,27(3),20-22
[79]朱妮,艾廷华.基于条带扫描思想的线目标缓冲区快速构建[J].测绘学报,2006,35(2)：171-176.
[80]A.Guttman. R-trees:a dynamic index structure for spatial searching[C]. In Proceedings of the ACM SIGMOD Conference on Management of Data,1984:47-57
[81]Aldefeld B.On automatic recognition of 3D structure from 2D representations.Computer-Aided Design,1983,15(2):59-64
[82]Ana-Maria Olteanu,Sebastien Mustiere,Anne Ruas.Matching imperfect spatial data.7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences.694-704
[83]Arnaud B.From the Schema Matching to the Integration of Updating Information into User Geographic Database [C].The 12th International Conference on Geoinformatics,Geospatial Information Research:Bridging the Pacific and Atlantic,University of Gvle,Sweden,2004
[84]Badard T.On the automatic retrieval of updates in geographic databases based on geographic data matching tools[C].Proceedings ofl9th International Cartographic Con ference,11th General Assembly of ICA.Ottawa.1999:47-56
[85]BEERI C,KANZA Y,SAFRA E,SAGIV Y.Object Fusion in Geographic Information Systems [A].Proceedings of the 30th VLDB Conference [C].Toronto,2004:816-827
[86]Beckmann N., Kriegel H.P., Schneider R., Seeger B..The R*-tree:An efficient and robust access method for points and rectangles[C]. In Proceedings of SIGMOD, Atlantic City, New Jersey,1990:322-331
[87]Bishr Y.,Overcoming the semantic and other barriers to GIS interoperability,International Journal of Geographic Information Science,Vol.12,No.4,1998,299-314
[88]Braun Arnaud.From the Schema Matching to the Integration of Updating Information into User Geographic Database[C].Proceedingofl2th International Conference on Geoinfor-matics,Geospatial Information Research: Bridging the Pacific and Atlantic. Swede:University of G vle,7-9,June 2004
[89]Canters F.Evaluating the uncertainty of area estimates derived from fuzzy land-cover classification.Photogrammetric Engineering and Remote Sensing,1997,(63):403-414
[90]Case K,Gao J.Feature technology.An overview.International Journal for Computer Integrated Manufacturing,1993,6(12):2-12
[91]Cecile Lemarie,Laurent Raynal.Geographic Data Matching:First Investigations For A Generic Tool[C].GIS/LIS'96 Annual Conference and Exposition Proceedings,Denver,Colorado,US A,1996,405-420
[92]Chua C E H,Chiang R H L,Lim E P.InstanceBased Attribute Identification in Database Integration[J].VLDB Journal,2003,12 (3):228-243
[93]Claramunt C,Theriault M.Managing Time in GIS:An Events-Oriented Approach[C].The Interna-tional Workshop on Temporal Databases,Zurich,1995
[94]COBB M,CHUNG M,FOL EY H.A Rule2based Approach for the Conflation of Attributed Vector Data [J].Geo Informatica,1998,2 (1):7-35
[95]Cohn A G,Hazarik A S.Q ualitative spatial rep resentation and reasoning:an overview [J].Fundamenta Info rmaticae,2001,46(1-2):1-29
[96]COHN A QGOTTS N M.The'Egg-Yolk'Representation of Regions with Indeterminate Boundaries[A].In:Burrough P A and Frank A U(ed),Proceedings of GIS DATA-Specialist Meeting on Spatial Objects with Undetermined Boundaries[C].London:Taylor & Francis.1996:171-187.
[97]Cooper Antony.The Concepts of Incremental Updating and Versioning[C].Proceedings of the21st International Cartographic Conference (ICC).August 2003,:855-857
[98]David A.Gadish.Inconsistency Detection and Adjustment of Spatial Data Using Rule Discovery [D].University Of Guelph,In Canada,2001
[99]David Gadish.Spatial Data Consistency in Production and On-line Query Environments.PDF
[100]Dekang Lin.An information-theoretic definition of similarity.In Proceedings of the 15th International Conference on Machine Learning.San Francisco,CA,1998:296-304
[101]Dungan J L,Perry J N,Dale M R T,et al.A Balanced View of Scale in Spatial Statistical Analysis[J].Ecography,2002,25:625-640
[102]EGENHOFER M,FRANZOSA R.Point-Set Topological Spatial Relations[J].International Journal of Geographical Information Systems,1991,5(2):161-174.
[103]EGENHOFER M,HERRING J.Categoring Binary Topological Relationships between Regions,Lines,and Points in Geographic Databases[R J.Oronoi:Technical report,Department of Surveying Engineering,University of Maine,Oronoi,ME,1991.
[104]E Persoon,K S Fu.Shape discrimination using Fourier descriptors.IEEE Trans on PAMI,1986,8:388-397
[105]Elizabeth A. Wentz.A Shape Definition for Geographic Applications Based on Edge,Elongation,and Perforation [J].Geographical Analysis,2000,Vol.32,No.1:95-112
[106]Elizabeth A.Wentz.Shape Analysis in GIS[C].ACSM/ASPRS,1997,Seattle, Washington. Vol.5.(Auto-Carto 13):204-213
[107]Fisher P F. Visualizing uncertainty in soil maps by animation.Cartographica,1994,(30):20-27
[108]Frank AU.Qualitative topological relations and indeterminate boundaries[A].In:Burrough PA,Frank AU (Eds).Geographic Objects with Indeterminate Boundaries[C].London:Taylor & Francis,1996,153-154
[109]Freeman H.Computer processing of line-drawing images.Computing Surveys,1974,6 (1):57-97
[110]FU Zhongliang,WU Jianhua.Entity Matching in Vector Data.ISPRS2008.2008,7:1467-1472
[111]Graham R L.An efficient algorihm for determining the convex hull of a finite point set[J].InformationProcessing Letters,1972,(1):132-133.
[112]Gadish,David,Baser,Otman,Chiu,David.Detection and Adjustment of Inconsistencies In a Multi-Layered Spatial Representation,Proc.13th Annual Conference on Geographic Information Systems,GIS'99,Vancouver,pp.24-27
[113]Grimson,Huttenlocher. On the sensitivity of the Hough transform for object recognition [J]. Pattern Analysis and Machine Intelligence,1990,12(3):255-274
[114]Harris C,Stephens M.A combined corner and edge detector[C] Proceedings of the Alvey Vision Conference,Manchester,1988:147-151
[115]Hu Ming-Kuei. Visual pattern recognition by moment invariants.IRE TransInformation Theory.1962:179-187.
[116]Huttenlocher D P,Klanderman G A,Rucklidge W J.Comparing I mages Using the Hausdorff Distance.IEEE Transactions on Pattern Analysis andMachine Intelligence,1993,15 (9):850-863.
[117]H Kauppien,T Sepanen.An experiment comparison of autoregressive and Fourier-based descriptors in 2D shape classification.IEEE Trans on PAMI,1995,2:201-207.
[118]H.Kadri-Dahmani "Updating Data in GIS:Towards a More Generic Approach "in Proceedings of the 20th International Cartographic Conference,Beijing,China,August 6-10,2001,vol 3,pp.1463-1471
[119]Jianyu (Jack) Zhou.A Three-step General Map Matching Method in the GIS Environment-Travel-Transportation Study Perspective,Department of Geography,University of California Santa Barbar,2004
[120]Kang Hae-Kyong,Li Ki-Joune.Assessing topological consistency for collapse operation in generalization of spatial databases[C].ER 2005 Workshops CAOIS,BP-UML,CoMoGIS,eCOMO,and QoIS-Perspectives in Conceptual Modeling,2005,10:249-258
[121]Laurent Spery A Framework for Update Process in GIS,http://www.geocomputation.org/1998/30/gc 30.htm
[122]Lee D T.On finding the convex hull of a simple polygon[J].Int.J.Computing Info.,1983,12(2):87-98.
[123]Li Wen-Syan,and Clifton Chris.SEMINT:A tool for identifying attribute correspondences in heterogeneous databases using neural net-works[J].Data&Knowledge Engineering,2000,33 (1):49-84
[124]Li Z L,Xu Z,ChenM Y,et al.Robust Surface Matching for Automated Detection of Local Deformations Using LeastMedian of Squares Estimator.Photogrammetric Engineering & Remote Sensing.2001,67 (11):1283-1292.
[125]LI Zhi-lin,ZHAO Ren-liang,CHEN Jun.An Algebra Model for Spatial Relations[A].Proceedings of the 3RD ISPRS Workshop on Dynamic and Multi-dimensional GIS[C],Bangkok:[s.n.],2001,170-177.
[126]Lee-Wen Tyan,Venkat D.Automatic identification of non-intersecting machining features from 2D CAD input.ComputerAided Design,1998,30(5):357-366
[127]Masuyama A. Methods for Detecting Apparent Differences between Spatial Tessellations at Different Time Points [J]. International Journal of Geographical Informati on Science,2006, 20(6):633-648
[128]MacEachren,A.M.(1985).Compactness of Geographic Shape:Comparison and Evaluationof Measures.Geografiska Annaler 67B,53-67
[129]Maceachren A M. Visualizing uncertain information.Cartographic Perspectives,1992,(13):10-19
[130]Mcgranaghan M.A cartographic view of saptial data quality.Cartographica,1993,(30):8-19
[131]M.Egenhofer,J.Herring.A Mathematical Framework for the Definition of Topological Relations[C].4th International Symposium on Spatial Data Handling,pp 803-813,Zurich,Switzerland,July 1990
[132]M.J.Egenhofer.Reasoning about binary topological relations.In:Proceedings of the 2nd Symposium on Large Spatial Databases.Lecture Notes in Computer Science,Springer-Verlag,1991,143-160
[133]M.J.Egenhofer,R.D.Franzosa.Point-set topological spatial relations [J].International Journal for Geographical Information Systems,1991,5 (2):161-174
[134]M.J.Egenhofer,J.R.Herring.Categorizing Binary Topological Relations between Regions,Lines,and Points in Geographic Databases[R].NCGIA Technical Report,1994,1-23
[135]M.J.Egenhofer.Evaluating Inconsistencies Among Multiple Representations,Sixth International Symposium on Spatial Data Handling,Edinburgh,Scotland,pp.901-920,September 1994
[136]M.J.Egenhofer,R.D.Franzosa.On the Equivalence of Topological Relations [J]. International Journal of Geographical Information Systems,1995, Vol.9,No.2,133-152
[137]O'Neill.A hierarchical concept of ecosystems[M].Monographs in Population Biology,1986,23-24
[138]Park Jinsoo,Schema Integration Methodology and Toolkit for Heterogeneous and Distributed Geographic Databases,Journal of the Korea Industrial Information Systems Society,2001,Vol6,No.3,51-64
[139]Rahm E,Bernstein P A.A survey of approaches to automatic schema matching.VLDB Journal,2001,10 (4):334-350
[140]SAALFELD A.Automated Map Conflation [D].Washington D C:University of Mary land,1993
[141]SAALFELD A.Conflation: Automated Map Compilation[J].International Journal of Geographical Information Systems,1988,2 (3):217-228
[142]SamalA,Seth S C,Cueto K.A Feature-based Approach to Conflation of Geospatial Sources.International Journal of Geographical Information Science,2004,18 (5):459-489
[143]Sellis T.K, Roussopoulos N., Faloutsos C. The R+-tree:A dynamic index for multi-dimensional objects[C]. In Proceedings of the 13th VLDB, Brighton, England,1987,507-518
[144]Servigne,S.,T.Ubeda,et al.A Methodology for Spatial Consistency Improvement of Geographic Databases.Geoinformatica,2000,4(1),pp.7-34
[145]Spery Laurent,A Framework for Update Process in GIS[C].Proceedings of the 3rd International Conference on GeoComputation,University of Bristol,United Kingdom,1998,9:17-19
[146]Shen D G,Davatzikos C.Hammer:Hierarchical Attribute Matching Mechanism for Elastic Registrati on.IEEE Transactions on Medical I maging,2002,21:1421-1439.
[147]Stephan Winter.Uncertain topological relations between imprecise regions [J].International Journal of Geographical Information Science,2000,14(5):411-430
[148]Theodoridis Y., Setlis T.K. A model for the prediction of R-tree performance[C].In Proceedings of PODS, Montreal,Canada,1996:161-171
[149]Ubeda,T.and Egenhofer,M.J.,1997.Topological Error Correcting in GIS.In:M.Scholl and A.Voisard (eds),Advances in Spatial Databases SSD'97,LNCS 1262,Springer,pp.283-297
[150]Veltkamp,R.C.(2001).Shape Matching:Similarity Measures and Algorithms.The 3rd International Conference on Shape Modeling and Applications,May 2001,Genoa,Italy,pp.188-99
[151]VOLKER WALTER and DIETER FRITSCH.Matching spatial data sets a statistical approach [J].Geographical information science,1999,Vol.13,No.5:445-473.
[152]WalterW,Fritsch D.Matching SpatialData Sets:A Statistical Approach.International Journal of Geographical Information Science,1999,13 (5):445-473.
[153]Weiguo Fan,etal.Discovering and reconciling value conflicts for numerical data integration.Information Systems,2001,26 (8):635-656
[154]Wu Jianhua,Fu Zhongliang.Research on Methods of Inconsistency Automatic Detection and Adjustment of Spatial Vector Data.International Conference on Information Technology & Environmental System Sciences 2008,May 15-17,2008,Jiaozuo,China:87-92
[155]Yerahmiel Doytsher,Sagi Filin,Eti Ezra.Transformation of Datasets in a Linear-based Map Conflation Framework [J].Surveying and Land Information Systems,2001, Vol.61,No.3,pp.159-169
[156]Y.R.Wong.Scene matching with invariant moments.Computer Graphics and Image Processing.1978,8(1):16-24.
[157]Yuan Shuxin,Tao Chuang.Development of Conflation Components[C].Geoinformatics'99,Interna-tional conference on Geoinformatics and Socioinfor-matics. Ann Arbor,Michigan,USA,1999:1-13
[158]Zhan F B.App roximate analysis of topo logical relations between geographic regions w ith indeterm inate boundaries [J].Soft Computing,1998,2 (2):28-34
[159]ZHANG Qiaoping,LI Deren,GONG Jianya.Shape Similarity Measures of Linear Entities[J].Geo-spatial Information Science.2002,Vol 5,No.2,62-67
[160]Zhang M, Shi W, Meng L. A Generic Matching Algorithm for Line Networks of Different Resolutions. Proceedings of the 8th ICA Workgroup on Generalization and Multiple Representations, A Coruna,2005,7
[161]Zuoquan Zhao,Roger R.Stough.Measuring Similarity among Various Shapes Based on Geometric Matching [J].Geographical Analysis,2005,(37):410-422
[2]艾廷华,帅赟,李精忠.基于形状相似性识别的空间查询[J].测绘学报,2009,Vol.38,No.4：356—362
[3]边馥苓.地理信息系统原理和方法[M].北京：测绘出版社,1996
[4]陈军,胡云岗,赵仁亮,等.道路数据缩编更新的自动综合方法研究[J].武汉大学学报(信息科学版),2007,32(11)：1022-1027
[5]陈建春Visual C++开发GIS系统[M],第二版.北京：电子工业出版社,2004：549-564.
[6]陈玉敏,龚健雅,史文中.多尺度道路网的距离匹配算法研究[J].测绘学报,2007,Vol.36,No.1：84-90
[7]崔铁军,郭黎.多源地理空间矢量数据集成与融合方法探讨[J].测绘科学技术学报,2007,Vol.24,No.1：1-4
[8]杜世宏,王桥,秦其明.空间关系模糊描述与组合推理[M].北京：科学出版社,2007
[9]范大昭,张永生,雷蓉,郭海涛.GIS数据自动更新技术的研究[J].测绘科学,2005,6,Vo1.30.No.3：15-18
[10]付仲良,吴建华.多比例尺空间数据库更新技术研究.武汉大学学报.信息科学版.2007,12,Vo1.32,No.12：1115—1118
[11]付仲良,邵世维.复杂面状矢量要素快速形状匹配方法.[J].测绘通报,2011,Vol.3：26-28
[12]付仲良,邵世维,童春芽.基于正切空间的多尺度面实体形状匹配[J]计算机工程.2010,17,Vol.36,No.17：216-218
[13]龚健雅.GIS中面向对象时空数据模型[J].测绘学报,1997,11,Vol.26,No.4：289—298
[14]龚健雅.地理信息系统基础.北京：科学出版社,2001
[15]郭黎,崔铁军,吴正升.多源数字地图融合技术问题的研究[J].海洋测绘,2000,(2)：22—25
[16]郭庆胜,杜晓初,刘浩.空间拓扑关系定量描述与抽象方法研究[J].测绘学报,2005,34(2)：123-128
[17]郭庆胜,杜晓初,闫卫阳.地理空间推理.北京：科学出版社,2006
[18]郭仁忠.空间分析[M].武汉：武汉测绘科技大学出版社,1997
[19]郭仁忠,闫浩文.空间方向关系基础性问题研究[J].测绘学报,2001,31(4)201—207
[20]郝燕玲,唐文静,赵玉新,李宁.基于空间相似性的面实体匹配算法研究[J].测绘学报,2008,37(4)501-506
[21]胡久乡,何松,锋瑜.空间数据库网格索引机制的最优划分[J].计算机学报,2002,25,Vo1.11：1227-1230
[22]晋耀红.基于语境框架的文本相似度计算[J].计算机工程与应用,2004,(16)：36—39
[23]金博,史彦军,滕弘飞.基于语义理解的文本相似度算法[J].大连理工大学学报,2005,Vol.45.No.2：291—297
[24]金文华,何涛,刘晓全等.基于有序简单多边形的平面点集凸包快速求取算法[J].计算机学报,1998,21(6)：533—539.
[25]孔祥玲,欧斌.地形图缩编技术的探讨[J].科技资讯,2007,No.12：2—2
[26]李芳玉,潘懋,朱雷.三维缓冲体生成栅格算法研究[J].计算机辅助设计与图形学学报,2005,17(9)：1928-1932.
[27]李科,杜琳.基于膨胀算法的缓冲区分析的设计与实现[J].测绘学院学报,2005,22(3)：229—231.
[28]罗晓燕,袁燕岩,蔡恒刚,黄德咏.大比例尺地形图数据库数据更新一体化技术综述[J].北京测绘,2004,(2)：20—23
[29]罗德安,廖丽琼.基于粗分格网的空问对象范围索引[J].西南交通大学学报.2003,38(3)：271-275
[30]刘东琴,苏山舞.多空间数据库位置匹配方法及其应用[J].测绘科学,2005,Vol.30,No.2：78—81
[31]刘大杰,史文中等.空间误差处理的理论和方法[M].上海：上海科学技术文献出版社,1998
[32]刘宏中.一种基于像素标识的笔画细化新方法[J].华中科技大学学报(自然科学版),2002,30(3)：80—82.
[33]刘宏中,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),2005,33(4)：13—16.
[34]刘万增,赵仁亮.水系要素更新中空间冲突的自动检测研究.中国地理信息系统协会第八届年会论文集,2004年11月,北京：145—152
[35]刘万增,陈军.循环经济GIS数据库空间冲突的确认方法研究[J].地球信息科学,2007,Vol.9.No.1：78-83
[36]刘万增,陈军,赵仁亮.基于平面扫描算法的空间冲突检测方法.2004年两岸四地地理信息系统发展研讨论文集,2004年12月,香港
[37]刘湘南,黄方,王平等.GIS空间分析原理与方法.北京：科学出版社,2005
[38]刘勇,李成名.城市基础空间数据库更新方法研究[J].测绘科学,2006,7,Vol.31,No.4：103—106
[39]刘志勇.城市地图数据库合并中的面实体匹配方法研究[D].南京：河海大学,2006,6
[40]罗德安,廖丽琼.基于粗分格网的空间对象范围索引[J].西南交通大学学报.2003,38(3)：271—275.
[41]李三玉.GIS图形数据更新解决方案[J].现代计算机,2005(10)：109—111
[42]李德仁,龚健雅,张桥平.论地图数据库合并技术[J].测绘科学,2004,Vol.29,No.1：1-4
[43]李德仁,关泽群.空间信息系统的集成与实现[M].武汉：武汉测绘科技大学出版社,2000
[44]李波.城市基础地理信息系统矢量数据更新研究[D].南京师范大学,2006
[45]毛定山,崔先国,李行,吴哲辉.简单多边形集凸包的快速算法.工程图学学报,2007,28(6).
[46]孟妮娜,周校东.固定格网划分的空间索引的实现技术[J].北京测绘.2003,1：7—11
[47]潘谦红,王炬,史忠植.基于属性论的文本相似度计算[J].计算机学报,1999,Vol.22,No.6：651—655
[48]潘瑜春,钟耳顺,赵春江.GIS空间数据库的更新技术[J].地球信息科学,2004,6(1)：36—39
[49]邱建华,唐学兵,黄华国.一种基于四叉树和R*树的索引结构—Q R*树[J].计算机应用.2003,23(8)：124-126,152
[50]任艳,易宝林,陈佳丽.基于规则的空间一致性维护[J].计算机工程,2007,Vol.33,No.19：93—95
[51]舒红,陈军,杜道生,周勇前.面向对象的时空数据模型[J].武汉测绘科技大学学报,1997,9,Vol.22,No.3：229-232
[52]帅赞,艾廷华,帅海燕,倪琳.基于形状模板匹配的多边形查询[J].武汉大学学报(信息科学版),2008,Vo1.33,No.12：1267—1270
[53]宋关福,钟耳顺,刘纪远,肖乐斌.多源空间数据无缝集成研究[J].地理科学进展,2000,6,Vol.19,No.2：110—115
[54]苏山舞,于荣花,沈涛,刘东琴,王荣彬.全国1：1000000数据库建设与更新[J].地理信息世界,2003,4,Vol.1,No.2：21-25
[55]商瑶玲,王东华,李莉.论全国1：250000数据库的建立与更新[J]地理信息世界,2003,4,Vol.1,No.2：16-20
[56]史杏荣,孙贞寿,曹爱军.基于固定网格划分和面向类对象的四分树空间索引机制制[J]小型微型计算机系统.1998,19(10)：24—31
[57]谭建荣,岳小莉,陆国栋.图形相似的基本原理、方法及其在结构模式识别中的应用[J].计算机学报,2002,9,Vol.25,No.9：959—967
[58]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,Vol.36,No.2：210-217
[59]王斌,舒华忠,施朝健,罗立民.一种基于轮廓线的形状描述与匹配方法.电子与信息学报,2008,30(4)：949-952.
[60]武芳.关系处理中要素重叠的自动判别[J].测绘学院学报,1997,3,Vol.14,No.1：43-46
[61]邬伦,刘瑜,张晶等.地理信息系统一原理、方法和应用.北京：科学出版社,2001
[62]王琴,李建辉.GIS空间多源数据集成模式探讨[J].黄河水利职业技术学院学报,2007,1,Vol.19,No.1：46-47
[63]王辉连,武芳,张琳琳,邓红艳.数学形态学和模式识别在建筑物多边形化简中的应用.测绘学报,2005,34(3)：269-276.
[64]汪嘉业,刘鼎元.对平面简单多边形求凸包的线性时间算法[J].计算机学报,1989,(1)：38-43.
[65]王晓峰,黄德双等叶片图像特征提取与识别技术的研究[J].中国科学院合肥智能机械研究所,2006.vol.42,No.3：190-193
[66]王育红,陈军.基于实例的GIS数据库模式匹配方法[J].武汉大学学报(信息科学版),2008年1月,Vol.33,No.1：46-50
[67]毋河海.关于GIS缓冲区的建立问题[J].武汉测绘科技大学学报,1997,22(4)：358-365.
[68]吴飞,蔡胜渊,郭同强,庄越挺.三角形约束下的图像特征点匹配方法.测绘学报[J].2010,22(3)：503-510
[69]吴立新,史文中3DGIS与3DGMS中的空间构模技术[J].地理与地理信息科学,2003,19(1)：209-215
[70]肖伟器,冯玉才.空间对象数据库的网格索引机制[J].计算机学报,1994,17(10)：736-742
[71]于桂芹,郭淑贤,赵立军.国家1：50000地形数据库更新工程项目的研究[J].测绘与空间地理信息,2007,4,Vol.30,No.2：125-127
[72]张桥平,李德仁,龚健雅.地图合并技术[J].测绘通报,2001,No.9：6-8
[73]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,Vol.8,No.2：107-112
[74]张桥平.地图数据库实体匹配与合并技术研究[D].武汉：武汉大学,2002
[75]张宏,温永宁,刘爱利等.地理信息系统算法基础.北京：科学出版社,2006
[76]赵仁亮,刘万增.利用空间关系检测数据更新中空间冲突.青年科学家论坛第九十二次活动论文集,2004年8月,北京
[77]张保钢,袁燕岩.城市大比例尺地形图数据库中地物变化的自动发现[J].武汉大学学报.信息科学版,2005,7,Vol.30,No.7：640-642
[78]曾衍伟.矢量GIS数据位置精度评价[J].测绘信息与工程,2002,27(3),20-22
[79]朱妮,艾廷华.基于条带扫描思想的线目标缓冲区快速构建[J].测绘学报,2006,35(2)：171-176.
[80]A.Guttman. R-trees:a dynamic index structure for spatial searching[C]. In Proceedings of the ACM SIGMOD Conference on Management of Data,1984:47-57
[81]Aldefeld B.On automatic recognition of 3D structure from 2D representations.Computer-Aided Design,1983,15(2):59-64
[82]Ana-Maria Olteanu,Sebastien Mustiere,Anne Ruas.Matching imperfect spatial data.7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences.694-704
[83]Arnaud B.From the Schema Matching to the Integration of Updating Information into User Geographic Database [C].The 12th International Conference on Geoinformatics,Geospatial Information Research:Bridging the Pacific and Atlantic,University of Gvle,Sweden,2004
[84]Badard T.On the automatic retrieval of updates in geographic databases based on geographic data matching tools[C].Proceedings ofl9th International Cartographic Con ference,11th General Assembly of ICA.Ottawa.1999:47-56
[85]BEERI C,KANZA Y,SAFRA E,SAGIV Y.Object Fusion in Geographic Information Systems [A].Proceedings of the 30th VLDB Conference [C].Toronto,2004:816-827
[86]Beckmann N., Kriegel H.P., Schneider R., Seeger B..The R*-tree:An efficient and robust access method for points and rectangles[C]. In Proceedings of SIGMOD, Atlantic City, New Jersey,1990:322-331
[87]Bishr Y.,Overcoming the semantic and other barriers to GIS interoperability,International Journal of Geographic Information Science,Vol.12,No.4,1998,299-314
[88]Braun Arnaud.From the Schema Matching to the Integration of Updating Information into User Geographic Database[C].Proceedingofl2th International Conference on Geoinfor-matics,Geospatial Information Research: Bridging the Pacific and Atlantic. Swede:University of G vle,7-9,June 2004
[89]Canters F.Evaluating the uncertainty of area estimates derived from fuzzy land-cover classification.Photogrammetric Engineering and Remote Sensing,1997,(63):403-414
[90]Case K,Gao J.Feature technology.An overview.International Journal for Computer Integrated Manufacturing,1993,6(12):2-12
[91]Cecile Lemarie,Laurent Raynal.Geographic Data Matching:First Investigations For A Generic Tool[C].GIS/LIS'96 Annual Conference and Exposition Proceedings,Denver,Colorado,US A,1996,405-420
[92]Chua C E H,Chiang R H L,Lim E P.InstanceBased Attribute Identification in Database Integration[J].VLDB Journal,2003,12 (3):228-243
[93]Claramunt C,Theriault M.Managing Time in GIS:An Events-Oriented Approach[C].The Interna-tional Workshop on Temporal Databases,Zurich,1995
[94]COBB M,CHUNG M,FOL EY H.A Rule2based Approach for the Conflation of Attributed Vector Data [J].Geo Informatica,1998,2 (1):7-35
[95]Cohn A G,Hazarik A S.Q ualitative spatial rep resentation and reasoning:an overview [J].Fundamenta Info rmaticae,2001,46(1-2):1-29
[96]COHN A QGOTTS N M.The'Egg-Yolk'Representation of Regions with Indeterminate Boundaries[A].In:Burrough P A and Frank A U(ed),Proceedings of GIS DATA-Specialist Meeting on Spatial Objects with Undetermined Boundaries[C].London:Taylor & Francis.1996:171-187.
[97]Cooper Antony.The Concepts of Incremental Updating and Versioning[C].Proceedings of the21st International Cartographic Conference (ICC).August 2003,:855-857
[98]David A.Gadish.Inconsistency Detection and Adjustment of Spatial Data Using Rule Discovery [D].University Of Guelph,In Canada,2001
[99]David Gadish.Spatial Data Consistency in Production and On-line Query Environments.PDF
[100]Dekang Lin.An information-theoretic definition of similarity.In Proceedings of the 15th International Conference on Machine Learning.San Francisco,CA,1998:296-304
[101]Dungan J L,Perry J N,Dale M R T,et al.A Balanced View of Scale in Spatial Statistical Analysis[J].Ecography,2002,25:625-640
[102]EGENHOFER M,FRANZOSA R.Point-Set Topological Spatial Relations[J].International Journal of Geographical Information Systems,1991,5(2):161-174.
[103]EGENHOFER M,HERRING J.Categoring Binary Topological Relationships between Regions,Lines,and Points in Geographic Databases[R J.Oronoi:Technical report,Department of Surveying Engineering,University of Maine,Oronoi,ME,1991.
[104]E Persoon,K S Fu.Shape discrimination using Fourier descriptors.IEEE Trans on PAMI,1986,8:388-397
[105]Elizabeth A. Wentz.A Shape Definition for Geographic Applications Based on Edge,Elongation,and Perforation [J].Geographical Analysis,2000,Vol.32,No.1:95-112
[106]Elizabeth A.Wentz.Shape Analysis in GIS[C].ACSM/ASPRS,1997,Seattle, Washington. Vol.5.(Auto-Carto 13):204-213
[107]Fisher P F. Visualizing uncertainty in soil maps by animation.Cartographica,1994,(30):20-27
[108]Frank AU.Qualitative topological relations and indeterminate boundaries[A].In:Burrough PA,Frank AU (Eds).Geographic Objects with Indeterminate Boundaries[C].London:Taylor & Francis,1996,153-154
[109]Freeman H.Computer processing of line-drawing images.Computing Surveys,1974,6 (1):57-97
[110]FU Zhongliang,WU Jianhua.Entity Matching in Vector Data.ISPRS2008.2008,7:1467-1472
[111]Graham R L.An efficient algorihm for determining the convex hull of a finite point set[J].InformationProcessing Letters,1972,(1):132-133.
[112]Gadish,David,Baser,Otman,Chiu,David.Detection and Adjustment of Inconsistencies In a Multi-Layered Spatial Representation,Proc.13th Annual Conference on Geographic Information Systems,GIS'99,Vancouver,pp.24-27
[113]Grimson,Huttenlocher. On the sensitivity of the Hough transform for object recognition [J]. Pattern Analysis and Machine Intelligence,1990,12(3):255-274
[114]Harris C,Stephens M.A combined corner and edge detector[C] Proceedings of the Alvey Vision Conference,Manchester,1988:147-151
[115]Hu Ming-Kuei. Visual pattern recognition by moment invariants.IRE TransInformation Theory.1962:179-187.
[116]Huttenlocher D P,Klanderman G A,Rucklidge W J.Comparing I mages Using the Hausdorff Distance.IEEE Transactions on Pattern Analysis andMachine Intelligence,1993,15 (9):850-863.
[117]H Kauppien,T Sepanen.An experiment comparison of autoregressive and Fourier-based descriptors in 2D shape classification.IEEE Trans on PAMI,1995,2:201-207.
[118]H.Kadri-Dahmani "Updating Data in GIS:Towards a More Generic Approach "in Proceedings of the 20th International Cartographic Conference,Beijing,China,August 6-10,2001,vol 3,pp.1463-1471
[119]Jianyu (Jack) Zhou.A Three-step General Map Matching Method in the GIS Environment-Travel-Transportation Study Perspective,Department of Geography,University of California Santa Barbar,2004
[120]Kang Hae-Kyong,Li Ki-Joune.Assessing topological consistency for collapse operation in generalization of spatial databases[C].ER 2005 Workshops CAOIS,BP-UML,CoMoGIS,eCOMO,and QoIS-Perspectives in Conceptual Modeling,2005,10:249-258
[121]Laurent Spery A Framework for Update Process in GIS,http://www.geocomputation.org/1998/30/gc 30.htm
[122]Lee D T.On finding the convex hull of a simple polygon[J].Int.J.Computing Info.,1983,12(2):87-98.
[123]Li Wen-Syan,and Clifton Chris.SEMINT:A tool for identifying attribute correspondences in heterogeneous databases using neural net-works[J].Data&Knowledge Engineering,2000,33 (1):49-84
[124]Li Z L,Xu Z,ChenM Y,et al.Robust Surface Matching for Automated Detection of Local Deformations Using LeastMedian of Squares Estimator.Photogrammetric Engineering & Remote Sensing.2001,67 (11):1283-1292.
[125]LI Zhi-lin,ZHAO Ren-liang,CHEN Jun.An Algebra Model for Spatial Relations[A].Proceedings of the 3RD ISPRS Workshop on Dynamic and Multi-dimensional GIS[C],Bangkok:[s.n.],2001,170-177.
[126]Lee-Wen Tyan,Venkat D.Automatic identification of non-intersecting machining features from 2D CAD input.ComputerAided Design,1998,30(5):357-366
[127]Masuyama A. Methods for Detecting Apparent Differences between Spatial Tessellations at Different Time Points [J]. International Journal of Geographical Informati on Science,2006, 20(6):633-648
[128]MacEachren,A.M.(1985).Compactness of Geographic Shape:Comparison and Evaluationof Measures.Geografiska Annaler 67B,53-67
[129]Maceachren A M. Visualizing uncertain information.Cartographic Perspectives,1992,(13):10-19
[130]Mcgranaghan M.A cartographic view of saptial data quality.Cartographica,1993,(30):8-19
[131]M.Egenhofer,J.Herring.A Mathematical Framework for the Definition of Topological Relations[C].4th International Symposium on Spatial Data Handling,pp 803-813,Zurich,Switzerland,July 1990
[132]M.J.Egenhofer.Reasoning about binary topological relations.In:Proceedings of the 2nd Symposium on Large Spatial Databases.Lecture Notes in Computer Science,Springer-Verlag,1991,143-160
[133]M.J.Egenhofer,R.D.Franzosa.Point-set topological spatial relations [J].International Journal for Geographical Information Systems,1991,5 (2):161-174
[134]M.J.Egenhofer,J.R.Herring.Categorizing Binary Topological Relations between Regions,Lines,and Points in Geographic Databases[R].NCGIA Technical Report,1994,1-23
[135]M.J.Egenhofer.Evaluating Inconsistencies Among Multiple Representations,Sixth International Symposium on Spatial Data Handling,Edinburgh,Scotland,pp.901-920,September 1994
[136]M.J.Egenhofer,R.D.Franzosa.On the Equivalence of Topological Relations [J]. International Journal of Geographical Information Systems,1995, Vol.9,No.2,133-152
[137]O'Neill.A hierarchical concept of ecosystems[M].Monographs in Population Biology,1986,23-24
[138]Park Jinsoo,Schema Integration Methodology and Toolkit for Heterogeneous and Distributed Geographic Databases,Journal of the Korea Industrial Information Systems Society,2001,Vol6,No.3,51-64
[139]Rahm E,Bernstein P A.A survey of approaches to automatic schema matching.VLDB Journal,2001,10 (4):334-350
[140]SAALFELD A.Automated Map Conflation [D].Washington D C:University of Mary land,1993
[141]SAALFELD A.Conflation: Automated Map Compilation[J].International Journal of Geographical Information Systems,1988,2 (3):217-228
[142]SamalA,Seth S C,Cueto K.A Feature-based Approach to Conflation of Geospatial Sources.International Journal of Geographical Information Science,2004,18 (5):459-489
[143]Sellis T.K, Roussopoulos N., Faloutsos C. The R+-tree:A dynamic index for multi-dimensional objects[C]. In Proceedings of the 13th VLDB, Brighton, England,1987,507-518
[144]Servigne,S.,T.Ubeda,et al.A Methodology for Spatial Consistency Improvement of Geographic Databases.Geoinformatica,2000,4(1),pp.7-34
[145]Spery Laurent,A Framework for Update Process in GIS[C].Proceedings of the 3rd International Conference on GeoComputation,University of Bristol,United Kingdom,1998,9:17-19
[146]Shen D G,Davatzikos C.Hammer:Hierarchical Attribute Matching Mechanism for Elastic Registrati on.IEEE Transactions on Medical I maging,2002,21:1421-1439.
[147]Stephan Winter.Uncertain topological relations between imprecise regions [J].International Journal of Geographical Information Science,2000,14(5):411-430
[148]Theodoridis Y., Setlis T.K. A model for the prediction of R-tree performance[C].In Proceedings of PODS, Montreal,Canada,1996:161-171
[149]Ubeda,T.and Egenhofer,M.J.,1997.Topological Error Correcting in GIS.In:M.Scholl and A.Voisard (eds),Advances in Spatial Databases SSD'97,LNCS 1262,Springer,pp.283-297
[150]Veltkamp,R.C.(2001).Shape Matching:Similarity Measures and Algorithms.The 3rd International Conference on Shape Modeling and Applications,May 2001,Genoa,Italy,pp.188-99
[151]VOLKER WALTER and DIETER FRITSCH.Matching spatial data sets a statistical approach [J].Geographical information science,1999,Vol.13,No.5:445-473.
[152]WalterW,Fritsch D.Matching SpatialData Sets:A Statistical Approach.International Journal of Geographical Information Science,1999,13 (5):445-473.
[153]Weiguo Fan,etal.Discovering and reconciling value conflicts for numerical data integration.Information Systems,2001,26 (8):635-656
[154]Wu Jianhua,Fu Zhongliang.Research on Methods of Inconsistency Automatic Detection and Adjustment of Spatial Vector Data.International Conference on Information Technology & Environmental System Sciences 2008,May 15-17,2008,Jiaozuo,China:87-92
[155]Yerahmiel Doytsher,Sagi Filin,Eti Ezra.Transformation of Datasets in a Linear-based Map Conflation Framework [J].Surveying and Land Information Systems,2001, Vol.61,No.3,pp.159-169
[156]Y.R.Wong.Scene matching with invariant moments.Computer Graphics and Image Processing.1978,8(1):16-24.
[157]Yuan Shuxin,Tao Chuang.Development of Conflation Components[C].Geoinformatics'99,Interna-tional conference on Geoinformatics and Socioinfor-matics. Ann Arbor,Michigan,USA,1999:1-13
[158]Zhan F B.App roximate analysis of topo logical relations between geographic regions w ith indeterm inate boundaries [J].Soft Computing,1998,2 (2):28-34
[159]ZHANG Qiaoping,LI Deren,GONG Jianya.Shape Similarity Measures of Linear Entities[J].Geo-spatial Information Science.2002,Vol 5,No.2,62-67
[160]Zhang M, Shi W, Meng L. A Generic Matching Algorithm for Line Networks of Different Resolutions. Proceedings of the 8th ICA Workgroup on Generalization and Multiple Representations, A Coruna,2005,7
[161]Zuoquan Zhao,Roger R.Stough.Measuring Similarity among Various Shapes Based on Geometric Matching [J].Geographical Analysis,2005,(37):410-422