空间数据质量控制与评价技术体系研究
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摘要
随着信息技术的发展,地理信息系统(GIS)的应用日益广泛。在我国GIS发展初期,李德仁院士(1991)指出:如何建立GIS的质量模型、用什么尺度来度量GIS中的精确数据和非确定数据、定量数据与定性数据等是GIS发展必须解决的问题。GIS数据不确定性以及由此产生的GIS数据质量控制技术成了国内外GIS研究的热点问题之一。
近年来,空间数据位置不确定性成为研究热点,并已取得一些成果:点位不确定性采用一系列误差区间来度量,线位不确定性采用误差带来度量,采用构成面元边界线段的不确定性描述面元不确定性。以往研究的重点集中在建立位置不确定性模型及度量指标、遥感分类数据的不确定性等方面,对于如何在数据获取过程中进行质量控制以确保成果数据符合质量要求探讨较少,是值得深入研究的课题。
本文首先分析空间数据质量问题,归纳可能出现的质量问题,并以地形图扫描数字化为例,分析空间数据的误差来源;然后,建立统一的空间数据成果质量模型;接着,从GIS数据采集过程着手,研究如何在数据获取过程进行质量控制从而确保成果数据质量,以及研究空间数据质量指标的检验与评价方法,尤其是采用程序进行检验的方法:最后,开发相应的软件,实现空间数据质量控制与评价,从而建立完整的空间数据质量控制与评价技术体系。本文的主要研究成果包括:
1.分析了空间数据质量
分析了空间数据质量问题,并将其分为误差和错误两大类。针对GIS数据获取方式多、工序复杂,以地形图扫描数字化为例,分析空间数据误差来源,探讨各作业工序可能引入的误差、误差表现形式及其对成果数据质量的影响;通过误差分布检验,分析了地形图扫描数字化数据误差分布,为地形图扫描数字化数据质量控制提供依据。
2.建立了统一的空间数据质量模型
在提出的各种空间数据质量元素基础上,针对GIS数据格式、数据类型多种多样,目前尚无统一的数据质量模型,通过归纳、指标细分等方法,提出采用“精度”、“一致性”、“完整性与正确性”作为描述空间数据质量的一级质量元素,并详细列出了各个一级质量元素相应的二级质量元素、各个二级质量元素相应的三级质量元素,建立基于GIS数据内容的、统一的空间数据质量模型,作为GIS数据质量控制、质量评价的依据。然后,以统一的空间数据质量模型为基础,建立了数字线划图(DLG)、数字正射影像(DOM)、数字高程模型(DEM)的质量评价模型,作为产品质量检验与评价的标准。
3.提出了空间数据质量控制方法
提出了空间数据质量总体控制方法,并以地形图扫描数字化为例,探讨了如何从选择数据源、地图扫描、扫描图像几何纠正、图纸定向、屏幕数字化、数据编辑、成果数据位置精度限差规定、位置精度检测时检测点个数的确定等方面进行工序质量控制,确保获得高质量的DLG成果数据、应用相关软件生成高质量的DEM成果数据。
4.提出了空间数据质量检验与评价方法
首先,根据GIS数据质量模型,研究了需要检验的质量指标,探讨了不同质量指标的检查方法;进一步区分出可以采用程序检查的质量指标;最后,研究质量检查、质量评价的实现方法。主要成果包括:
With the development of the information technique, the use of Geographical Information System(GIS) becomes broader and broader. At the GIS development beginning stage in China, Prof. Deren Li (1991 ) pointed that the following problems must be solved: how to build quality model of GIS, which index is used to measure accurate data and uncertainty data, quantitative data and qualitative data in GIS.GIS data uncertainty and GIS data quality control technique becomes a research issue.Recent years, positional accuracy of the spatial data is a research issue, and some research result is gained. Point uncertainty is measured by error intervals, line positional uncertainty is measured by error belt, area positional uncertainty is described by uncertainty of lines which form the boundary of the area. The former research emphases on the foundation of positional uncertainty and measurement index, remote sensing classification data uncertainty etc. Fewer discussion is made on how to control data quality in the process of data collection to insure data production quality to meet the quality requirements, which deserves deep research.At first, spatial data quality problem is analyzed and possible quality problem is summed up. Map scanning digitization is used an example to discuss the error source of spatial data. After that, an uniform spatial data quality model is built. Then starting from the GIS data collection process, how to control data quality in the process of data collection to insure data product quality is researched. Next, spatial data quality control and evaluation method is discussed, and the program check arithmetic is emphasized. Finally, the correspond soft of the spatial data quality control and evaluation is developed to control and evaluate spatial data quality. So a complete spatial data quality control and evaluation technique system is founded. The main research result is shown as the following:l.Spatila data quality is analyzed.Spatial data quality problem is analyzed, and is divided into error and mistake. Aiming at GIS data can be collected by much methods and working procedure is complicated, map scanning digitization is used as an example to analyze the error source of spatial data. The error source of map scanning digitization is detailedly analyzed. Possibly imported error, error representation form and its impact on the accuracy of data product is probed. Error distribution of map scanning digitization is analyzed by the way of error distribution test to give the basis of map scanning digitization data quality control.2.An uniform spatial data quality model is founded.Aiming at much GIS data format and data type, and there is not an uniform spatial data quality model, on the basis of GIS data content, quality elements Accuracy, Consistency and Completeness & correctness are suggested to measure spatial data quality by the way of induction and subdivision. And data quality elements and their quality subelements is given in detail. As a result, an uniform spatial data quality model is advanced, which is used as the basis of GIS data quality control and evaluation. Using this data quality model, data quality evaluation models of DLG,DOM and DEM are founded, which are used as a standard of product quality testing and evaluation.3.Spatial data quality control method is advanced.Using map scanning digitization as an example, general spatial data quality control method is advanced. To insure the data product to meet quality requirements, the following method were discussed as process quality control: select data source, map scan, geometrical rectify, map orientation, screen digitization, data edit, positional accuracy limitation defining of data product, testing point number of positional accuracy test, etc. By this way, DLG data with high quality can be gotten, and DEM data with high quality can also be gotten using correlative DEM making software.
4.Spatial data quality control and evaluation method is suggested.At first, data quality test index is researched according to GIS data quality model. And test method of the different quality index is discussed. Next, quality index which can be tested by program is distinguished. Finally, quality test and quality evaluation method is researched. The main research results is introduced here.? Using template match technique to check attribute data and metadata.? Using special topological relation test to check the topological consistency.? As for data cartography rule, element relative relation among different data layer, edgematch of different data file, etc., rule base is founded to check data consistency of different data by the way of rule defining by user.? Using mathematical method to check positional accuracy.? Vision model of man eye is established using experiences, the statistics value of the testing image is computed. They are compared to check image quality.? To check completeness and correctness automatically using the specific demands of the specification and technique design.? To represent error information in different ways, especially by means of graphic to become convenient for error affirming and editing.? To evaluate data quality automatically with the comparison of quality standard database and data quality testing result database.5.Spatial data quality control and evaluation software is developed.New spatial data quality test and evaluation idea is advanced. The complicated spatial data quality characteristics is abstracted as rule and model, which is used as the theoretic basis to check and evaluate the different data quality by means of program.Based on above research results, two universal software is developed, which is named as Vector Data Quality Control and Evaluation System(DLG-Checker) and Image Data Quality Check and Evaluation system(DOM-Checker) respectively. They have the following merits:? The graphic and image operation environment are developed by advanced language and database, which has independent knowledge property right.? They can be used to control procedure data quality and data product quality , check the quality data which will be imported database.? Spatial data quality control rule base is founded according to the knowledge, such as quality control experience, data quality standard cartography rule, etc. On the basis of rule and model, the test scheme is made flexibly, so test content and evaluation standard for different scale and different quality demand can be adjusted conveniently to meet the requirements of different project data quality control and evaluation. Besides this, these soft can check data quality in different type of format. In short, they can be used universally.? Using database technique to manage and update spatial data standard, the result of data quality check and evaluation.? Provide data edit function to adjust the error during data quality control process.? Facing digital surveying and mapping production, these soft can be used to check and evaluate the quality of different data by means of adjusting test scheme.Single function test and comparative test of these soft shows that these soft can be used universally, testing and evaluating result is reliable, quality control productivity is improved greatly.
近年来,空间数据位置不确定性成为研究热点,并已取得一些成果:点位不确定性采用一系列误差区间来度量,线位不确定性采用误差带来度量,采用构成面元边界线段的不确定性描述面元不确定性。以往研究的重点集中在建立位置不确定性模型及度量指标、遥感分类数据的不确定性等方面,对于如何在数据获取过程中进行质量控制以确保成果数据符合质量要求探讨较少,是值得深入研究的课题。
本文首先分析空间数据质量问题,归纳可能出现的质量问题,并以地形图扫描数字化为例,分析空间数据的误差来源;然后,建立统一的空间数据成果质量模型;接着,从GIS数据采集过程着手,研究如何在数据获取过程进行质量控制从而确保成果数据质量,以及研究空间数据质量指标的检验与评价方法,尤其是采用程序进行检验的方法:最后,开发相应的软件,实现空间数据质量控制与评价,从而建立完整的空间数据质量控制与评价技术体系。本文的主要研究成果包括:
1.分析了空间数据质量
分析了空间数据质量问题,并将其分为误差和错误两大类。针对GIS数据获取方式多、工序复杂,以地形图扫描数字化为例,分析空间数据误差来源,探讨各作业工序可能引入的误差、误差表现形式及其对成果数据质量的影响;通过误差分布检验,分析了地形图扫描数字化数据误差分布,为地形图扫描数字化数据质量控制提供依据。
2.建立了统一的空间数据质量模型
在提出的各种空间数据质量元素基础上,针对GIS数据格式、数据类型多种多样,目前尚无统一的数据质量模型,通过归纳、指标细分等方法,提出采用“精度”、“一致性”、“完整性与正确性”作为描述空间数据质量的一级质量元素,并详细列出了各个一级质量元素相应的二级质量元素、各个二级质量元素相应的三级质量元素,建立基于GIS数据内容的、统一的空间数据质量模型,作为GIS数据质量控制、质量评价的依据。然后,以统一的空间数据质量模型为基础,建立了数字线划图(DLG)、数字正射影像(DOM)、数字高程模型(DEM)的质量评价模型,作为产品质量检验与评价的标准。
3.提出了空间数据质量控制方法
提出了空间数据质量总体控制方法,并以地形图扫描数字化为例,探讨了如何从选择数据源、地图扫描、扫描图像几何纠正、图纸定向、屏幕数字化、数据编辑、成果数据位置精度限差规定、位置精度检测时检测点个数的确定等方面进行工序质量控制,确保获得高质量的DLG成果数据、应用相关软件生成高质量的DEM成果数据。
4.提出了空间数据质量检验与评价方法
首先,根据GIS数据质量模型,研究了需要检验的质量指标,探讨了不同质量指标的检查方法;进一步区分出可以采用程序检查的质量指标;最后,研究质量检查、质量评价的实现方法。主要成果包括:
With the development of the information technique, the use of Geographical Information System(GIS) becomes broader and broader. At the GIS development beginning stage in China, Prof. Deren Li (1991 ) pointed that the following problems must be solved: how to build quality model of GIS, which index is used to measure accurate data and uncertainty data, quantitative data and qualitative data in GIS.GIS data uncertainty and GIS data quality control technique becomes a research issue.Recent years, positional accuracy of the spatial data is a research issue, and some research result is gained. Point uncertainty is measured by error intervals, line positional uncertainty is measured by error belt, area positional uncertainty is described by uncertainty of lines which form the boundary of the area. The former research emphases on the foundation of positional uncertainty and measurement index, remote sensing classification data uncertainty etc. Fewer discussion is made on how to control data quality in the process of data collection to insure data production quality to meet the quality requirements, which deserves deep research.At first, spatial data quality problem is analyzed and possible quality problem is summed up. Map scanning digitization is used an example to discuss the error source of spatial data. After that, an uniform spatial data quality model is built. Then starting from the GIS data collection process, how to control data quality in the process of data collection to insure data product quality is researched. Next, spatial data quality control and evaluation method is discussed, and the program check arithmetic is emphasized. Finally, the correspond soft of the spatial data quality control and evaluation is developed to control and evaluate spatial data quality. So a complete spatial data quality control and evaluation technique system is founded. The main research result is shown as the following:l.Spatila data quality is analyzed.Spatial data quality problem is analyzed, and is divided into error and mistake. Aiming at GIS data can be collected by much methods and working procedure is complicated, map scanning digitization is used as an example to analyze the error source of spatial data. The error source of map scanning digitization is detailedly analyzed. Possibly imported error, error representation form and its impact on the accuracy of data product is probed. Error distribution of map scanning digitization is analyzed by the way of error distribution test to give the basis of map scanning digitization data quality control.2.An uniform spatial data quality model is founded.Aiming at much GIS data format and data type, and there is not an uniform spatial data quality model, on the basis of GIS data content, quality elements Accuracy, Consistency and Completeness & correctness are suggested to measure spatial data quality by the way of induction and subdivision. And data quality elements and their quality subelements is given in detail. As a result, an uniform spatial data quality model is advanced, which is used as the basis of GIS data quality control and evaluation. Using this data quality model, data quality evaluation models of DLG,DOM and DEM are founded, which are used as a standard of product quality testing and evaluation.3.Spatial data quality control method is advanced.Using map scanning digitization as an example, general spatial data quality control method is advanced. To insure the data product to meet quality requirements, the following method were discussed as process quality control: select data source, map scan, geometrical rectify, map orientation, screen digitization, data edit, positional accuracy limitation defining of data product, testing point number of positional accuracy test, etc. By this way, DLG data with high quality can be gotten, and DEM data with high quality can also be gotten using correlative DEM making software.
4.Spatial data quality control and evaluation method is suggested.At first, data quality test index is researched according to GIS data quality model. And test method of the different quality index is discussed. Next, quality index which can be tested by program is distinguished. Finally, quality test and quality evaluation method is researched. The main research results is introduced here.? Using template match technique to check attribute data and metadata.? Using special topological relation test to check the topological consistency.? As for data cartography rule, element relative relation among different data layer, edgematch of different data file, etc., rule base is founded to check data consistency of different data by the way of rule defining by user.? Using mathematical method to check positional accuracy.? Vision model of man eye is established using experiences, the statistics value of the testing image is computed. They are compared to check image quality.? To check completeness and correctness automatically using the specific demands of the specification and technique design.? To represent error information in different ways, especially by means of graphic to become convenient for error affirming and editing.? To evaluate data quality automatically with the comparison of quality standard database and data quality testing result database.5.Spatial data quality control and evaluation software is developed.New spatial data quality test and evaluation idea is advanced. The complicated spatial data quality characteristics is abstracted as rule and model, which is used as the theoretic basis to check and evaluate the different data quality by means of program.Based on above research results, two universal software is developed, which is named as Vector Data Quality Control and Evaluation System(DLG-Checker) and Image Data Quality Check and Evaluation system(DOM-Checker) respectively. They have the following merits:? The graphic and image operation environment are developed by advanced language and database, which has independent knowledge property right.? They can be used to control procedure data quality and data product quality , check the quality data which will be imported database.? Spatial data quality control rule base is founded according to the knowledge, such as quality control experience, data quality standard cartography rule, etc. On the basis of rule and model, the test scheme is made flexibly, so test content and evaluation standard for different scale and different quality demand can be adjusted conveniently to meet the requirements of different project data quality control and evaluation. Besides this, these soft can check data quality in different type of format. In short, they can be used universally.? Using database technique to manage and update spatial data standard, the result of data quality check and evaluation.? Provide data edit function to adjust the error during data quality control process.? Facing digital surveying and mapping production, these soft can be used to check and evaluate the quality of different data by means of adjusting test scheme.Single function test and comparative test of these soft shows that these soft can be used universally, testing and evaluating result is reliable, quality control productivity is improved greatly.
引文
[1] CH 1002-95《测绘产品检查验收规定》.北京:国家测绘局,1995年
[2] CH 1003-95《测绘产品质量评定标准》.北京:国家测绘局,1995年
[3] 《4D测绘产品质量监督抽检实施细则》(报批稿).北京:国家测绘局,2001年
[4] 邸凯昌,李德仁,李德毅.Rough集理论及其在GIS属性分析和知识发现中的应用.ISSN 1671-8860 CN 42-1676/TN,1999,24(1):6-10
[5] 戴洪磊.矢量GIS中位置不确定性度量与传播的理论和方法.武汉:武汉测绘科技大学博士学位论文,2000年
[6] 杜道生,王占宏,马聪丽.空间数据质量模型研究.ISSN 1006-8961 CN 11-3758/TB,2000,5(7):559-562
[7] GB/T18316-2001《数字测绘产品检查验收规定和质量评定》.北京:国家质量技术监督局,2001年
[8] 龚健雅.地理信息系统基础.北京:科学出版社,2001年
[9] 郭仁忠.空间分析.武汉:武汉测绘科技大学出版社,1997年
[10] 胡鹏,吴艳兰,胡海.数字高程模型精度评定的基本理论.地球信息科学,2003,No.3,pp64-70
[11] 黄加纳.地图数字化的坐标转换及数据的精度与相关性.ISSN 1671-8860 CN 42-1676/TN,2001,26(3):213-216
[12] 郝向阳,钱曾波.地图扫描数字化的点位精度分析.ISSN 1001-1595 CN11-2089/P,1996,25(1):46-52
[13] 蒋景瞳等译.美国国家数字制图数据标准.北京:测绘出版社,1990年
[14] 李德仁,龚健雅,边馥苓.地理信息系统导论.北京:测绘出版社,1993年
[15] 林宗坚,钟业喜,陈天恩,黄福来.改善城市GIS数据库空间数据几何精度的一种试验方法.1994年地理信息系统学术讨论会论文集,pp329-338
[16] 林宗坚.地图扫描采样分辨率的研究.ISSN 1009-2307 CN 11-4415/P,2000,25(1):13-15
[17] 刘大杰,史文中,童小华,孙红春.GIS空间数据的精度分析与质量控制.上海:上海科学技术文献出版社,1999年
[18] 刘春,史文中,刘大杰.GIS属性数据精度的缺陷率度量统计模型.ISSN 1001-1595 CN11—2089/P,2003,32(1):36-41
[19] 刘文宝,邓敏,夏宗国.矢量GIS图上地理曲线的定位误差模型.CN 11-3841/TP,2000,4(4):316-320
[20] 刘文宝,邓敏,夏宗国.矢量GIS中属性数据的不确定性分析.ISSN 1001-1595 CN11-2089/P,2000,29(1):76-81
[21] 刘文宝.GIS空间数据的不确定性理论.武汉:武汉测绘科技大学博士学位论文,1995.5
[22] 刘文宝.矿图手工数字化位置数据系统误差的控制.ISSN 1006-9097 CN 11-3747/TD,1998,23(4):443-447
[23] 刘建军,王东华,商瑶玲.数字化等高线质量的软件自动检查方法.ISSN 1009-2307 CN 11-441 5/P,2001,26(4):36-38
[24] 刘建军,陈军,王东华等.等高线邻接关系的表达及应用研究.ISSN 1009-2307 CN 11-4415/P,2004,33(2)174-178
[25] 刘学军,龚健雅,周启鸣等.基于DEM坡度坡向算法精度的分析研究.ISSN 1009-2307 CN 11-4415/P,2004,33(3):258-263
[26] 柳宗伟,王新州,陈顺清.城市人口GIS中数据的不确定性.ISSN 1671-8860 CN 42-1676/TN,2002,27(6):627-631
[27] 李大军,龚健雅,谢刚生等.GIS中线元的误差熵带研究.ISSN 1671-8860 CN 42-1676/TN,2002,27(5):462-466
[28] 李大军,龚健雅,谢刚生等.GIS中面元的误差熵模型.ISSN 1001-1595 CN11-2089/P,2003,32(1):31-35
[29] 李大军,龚建雅,谢刚生.点位不确定性熵指标的确定.ISSN 1000-1433 CN 11-2025/TU,2002(2),pp.33-36
[30] 马龙,杜道生.GIS中DEM产品精度的分析和评价.ISSN 1007-3817 CN 42-1415/P,2003,28(3):4-5
[31] 史文中.地理信息系统中几何特征不确定性的通用模型:从1维到N维.ISSN 1001-1595 CN11-2089/P,1997,26(2):161-167
[32] 史文中,童小华,刘大杰.GIS中一般曲线的不确定性模型.CN 11-3841/TP,2000,29(1):52-57
[33] 史文中,王树良.GIS中属性不确定性综述.中国地理信息系统协会2001年年会论文集,172-189
[34] 史文中,王树良.GIS中属性不确定性的处理方法及其发展.CN 11-3841/TP,2002,6(5):394-400
[35] 史文中,刘春,刘大杰.基于一般抽样原理的GIS属性数据精度评定方法.ISSN 1671-8860 CN 42-1676/TN 2002,27(5):445-451
[36] 《数字地形图产品质量标准》(讨论稿).北京:国家测绘局,1995年
[37] 童小华,周德意.地形(籍)图扫描纠正的精度分析.ISSN 0253—374X CN 31-1267/N,31(1):77-81
[38] 邬伦,于海龙,高振纪,承继成.GIS不确定性框架体系与数据不确定性研究方法.地理学与国土研究,2002,18(4):1-5
[39] 毋河海.地图数据库系统[M].北京:测绘出版社,1990年
[40] 毋河海,龚健雅.地理信息系统(GIS)空间数据结构与处理技术.北京:测绘出版社,1997年
[41] 吴芳华,金澄.数字地图数据质量评价软件的设计.CN 61-1365/E,2001,21(2):43-47
[42] 吴芳华,金澄.矢量地图数据属性精度的检查与控制.ISSN 1009-427X CN 41-1205/P,2003,20(1):65-68
[43] 吴芳华,张跃鹏,金澄.GIS空间数据质量的评价.ISSN 1009-427X CN 41-1205/P,2001(1),63-66
[44] 许金钊编译.数理统计与产品质量.北京:中国标准出版社,1986年
[45] 阎正,城市地理信息标准化指南。北京:科学出版社,1999年
[46] 杨元喜,赵丽华,吴芳华等.地图数字化的精度评定与控制.CN 61-1365/E,2003,23(2):1-4
[47] 余晓红,刘大杰.地图数字化数据坐标变换的相关性分析.ISSN 1671-8860 CN 42-1676/TN,2002,27(5):456-460
[48] 杨启和,杨晓梅.数字化地形图数据处理方法分析.ISSN 0494-0911 CN 11-2246/P,1995,No.2:31-35
[49] 杨恒山.地图数字化中图纸定向的若干问题探讨.ISSN 1000-9779 CN 43-1073/U,17(2):43-48
[50] 杨元喜,赵丽华,吴芳华等.地图数字化的精度评定与控制.CN 61-1365/E,2003,23(2):1-4
[51] 张景雄,杜道生,孙家柄.用随机模拟方法建立矢量数据的误差模型.ISSN 1671-8860,2000,25(1):49-54
[52] 张景雄,杜道生.位置不确定性与属性不确定性的场模型.ISSN 1671-8860 CN 42-1676/TN,1999,28(3):244-249
[53] 周成虎.地理信息系统理论与方法.北京:中国科学技术大学出版社,1996年
[54] 曾衍伟.矢量GIS数据位置精度评价.ISSN 1007-3817 CN 42-1415/P,2002.
[55] 曾衍伟.影像数据质量检验与评价系统设计与实现.CN 11-3841/TP,2003,
[56] 曾衍伟.地形图扫描数字化图纸定向精度探讨.ISSN 0494-0911 CN 11-2246/P,2004.
[57] 曾衍伟.空间数据质量控制与评价方法及实现技术.ISSN 1671-8860 CN 42-1676/TN,2004.
[58] Andreas Busch, Felicitas Willrich. System Design for Automated Quality Control of GIS and Imagery. ISPRS 2002, Volume ⅩⅩⅩⅣ: 53-58
[59] Akos Detrekoi. Data quality management in GIS systems. Computers, Environment and Urban Systems, Volume 18, Issue 2, March-April 1994, PP. 81-85
[60] Alistair Geddes, Alessandro Gimona and David A. Elston. Estimating local variation in landuse statistics. ISSN 1365-8816, 2003, 17 (4) : 299-319
[61] Alex Hagen. Fuzzy set approach to assessing similarity of categorical maps. ISSN 1365-8816, 2003, 17 (3) : 235-249
[62] Anton J. J. Van Rompaey, Gerard Govers. Data quality and model comlexity for regional scale soil erosion prediction. IS SN 1365-8816, 2002, 16 (7) : 663-680
[63] Aronoff, S. , 1989. Geographic Information Systems: A Management Perspective. Ottawa, Ontario, Canada: WDL.
[64] Bishnu P. Phuyal, Robert W. Schmidley, J. Raul rami. Automatic Quality Control for GIS Data conversion. Surveying and Land Information Systems. 1997, 57 (1) : 37-41
[65] Burrough P. A. , Mcdonnell R. A. Principles of Geogrphical Information System. New York: Oxford University Press, 1998
[66] Bheshem Ramlal, J. E. Drummond. A GIS uncertainty subsystem. In: ISPRS 1992: Vol. 29: Part B3, commission Ⅲ, pp. 356-362
[67] Bernhardsen, Tor. Geographic Information Systems: An Introduction(Third Edition). New York, USA: John Wiley & Sons. 2002, PP. 215-234
[68] Curtis E. Woodcock, Suchatita Gopal. Fuzzy set theory and thematic maps: accuracy assessment and area estimation. ISSN 1365-8816, 2000, 14 (2) : 153-172
[69] Chrisman NR. Methods of spatial analysis based on error in categorical maps. phDThesis, University of Bristol, 1982a.
[70] Caspary W, Scheuring.Error-bands as measures of geometrical accuracy. Proceeding of EGIS' 92,1992, 226-233
[71] C.Lopez.Locating some types of random errors in Digital Terrain Models. ISSN 1365-8816,1997,11(7): 677-698
[72] C.P.J.M. van EIzakker, Bheshem Ramlal, J.E. Drummond. The visualization of GIS generated information quality . In: ISPRS 1992 : Vol. 29 : Part B4, commission IV, pp. 608-615
[73] Charles R.Ehlschlasger.Representing multiple spatial statistics in generalized elevation uncertainty models:moving beyond the variogram. ISSN 1365-8816,2002,16(3): 259-285
[74] C. Victor WuBarbara P. Buttenfield. Spatial data quality and its evaluation. ISSN 0198-9715, 1994, 18(3): 153-165
[75] Dong-Gyu Park, Hwan-Gue Cho.A Verification System for the Accuracy of the Digital Map. ADVANCES IN GIS RESEARCH II.Proceedings of the 7th InternationalSymposium on Spatial Data Handling, 1996: 287-299
[76] Drummond J.,Brown A.,Du Daosheng,etc.The development of a GIS information quality module. Archives of Spatial Accuracy Assessment in Natural Resources and Environmental Sciences: Second International Symposium.May 1996,pp. 189~198
[77] D.L. Moody. Metrics for evaluating the quality of entity relationship models. In: Conceptual modeling ER'98 : 17th international conference on conceptual modeling, Singapore November 16-19, 1998. pp. 211-225
[78] Giuseppe Arbia,Daniel Griffith and Roabert Haining.Error propagation modelling in raster GIS:overlay operations. ISSN 1365-8816,1998,12(2): 145-167
[79] Gerard B.M. Heuvelink.Identification of field attribute error under different models of spatial variation. ISSN 1365-8816,1996,10(8): 921-935
[80] G. Pillirone , D. Visintini. A Package for the Management of Data Quality in Geographic Information Systems[A]. Edited by L. Mussio, G. Forlani, F. Crosilia. Data Acquisition and Analysis for Multimedia GIS, Spinger Wien New York, pp77-86
[81] G. Edwards etc."Spatial Error and Uncertainty and the Decision-Making Process", Spatail Data Handling 2000 Conference Proceedings, pp6a.26-36.
[82] Herring, J, R.TIGRIS:Topologically Integrated Geographic Information System.In Proceedings of Auto Carto 8, Baltimore, edited by N.R.Chrisman, American Society for
Photoprammetry and Remote Sensing and American Congress on Surveying and Mapping, pp.282-291, 1987
[83] Hong Jiang,J.Ronald Eastman.Application of fuzzy measures in multi-criteria evaluation in GIS. ISSN 1365-8816,2000,14(2): 173-184
[84] Howard Veregin. " Error Propagation through the Buffer Operation for Probability Surface", Photogrammetric Engineering & Remote Sensing, Vol.62, No.4, April 1996, pp.419-428
[85] Havard Tveite,Sindre Langaas.An accuracy assessment method for grographical line data sets based on buffering. ISSN 1365-8816,1999,13(1): 27-47
[86] Hayati TASTAN , M.Orhan ALTAN.Auomatic Checking of Feature and Attribute Consistency of a Spatial Database. ISPRS 2000, Volume XXXIII: 1066-1073
[87] Howard VereginDavid P. Lanter. Data-quality enhancement techniques in layer-based geographic information systems. ISSN 0198-9715, 1995,19(1): 23-36
[88]Howard Verrgin.Quantifying positional errorr induced by line simplification. ISSN 1365-8816,2000,14(2): 113-130
[89] Igor V. Florinsky.Errors of signal processing in digital terrain modelling. ISSN 1365-8816,2002,16(5): 475-501
[90] Joshua Greenfeld.Evaluating the Accuracy of Digital Orthophoto Quadrangles(DOQ) in the Context of Parcel-Based GIS[J]. Photogrammetric Engineering & Remote Sensing, 2001, 67(2): 199-205
[91] Jerry H.Ratcliffe.On the accuracy of TIGER-type geocoded addess data in relation to cadastral and census areal units. ISSN 1365-8816,2001,15(5): 473-485
[92] J. P. Mills and I. Newton. A new approach to the verification and revision of large-scale mapping. ISPRS Journal of Photogrammetry and Remote Sensing, Volume 51, Issue 1, February 1996, Pages 17-27
[93] J.E. Drummond, A. Brown, Du Daosheng, C.P.J.M. van Elzakker.The development of a GIS information quality module. Spatial accuracy assessment in natural resources and environmental sciences : 2nd international symposium, May 21-23 1996, Colorado, pp. 189-198
[94] Kim Lowell etc. "Combining Map Geometry and Polygon Attributes to Estimate Spatial Uncertainty from Multiple Realisations", Spatail Data Handling 2000 Conference Proceedings, pp5a.32-43
[95] Kelly Chan. DIGEST A primer for the International GIS Standard[M], pp.117-120.CRC Press LLC, 1999
[96] K. Kraus and H. Kager. Accuracy of derived data in a geographic information system . ISSN 0198-9715, 1994,18(2): 87-94
[97] Lawrence V. Stanislawski etc." Estimating Positional Accuracy of Data Layers within a GIS through Error Propagation", Photogrammetric Engineering & Remote Sensing, Vol.62, No.4, April 1996, pp.429-433.
[98] Larry E.Stanfel etc. "Reliability of Polygonal Boundary of Land Parcel", Journal of Surverying Engineering, November 1995
[99] Lemonia Ragia, Stephan Winter. Contributions to a quality description of areal objects in spatial data sets. ISPRS Journal of Photogrammetry & Sensing 55(2000): 201-213
[100] Lowell,K. and Jaton.A.Spatial Accuracy Assessment:Land Information Uncertainty in Natural Resources.2001,Ann Arbor Press,Chelsea,Michigan
[101] Michele Crosetto,Stefano Tarantola.Uncertainty and sensitivity analysisrtools for GIS-based model implementation. ISSN 1365-8816,2001,15(5): 415-437
[102] Matt Duckham.Jane Drummond.Assessment of error in digital vector data using fractal geometry. ISSN 1365-8816,2000,14(1): 67-84
[103] Mark Gahegan, Manfred Ehlers .A Framework for the modelling of uncertainty between remote sensing and geographic information systems.ISPRS Journal of Photogrammetry & Sensing 55(2000)176-188
[104] Martien Molenaar, . "An Introduction to the Theory of Spatial Object Modelling for GIS", Published in 1998
[105] Martien Molenaar.Three conceptual uncertainty levels for spatial objects.International Archives of Photogrammetry and Remote Sensing.Vol.XXXIII,Part B4.Amsterdam 2000.pp.670-677
[106] Martien Molenaar.Spatial data modelling and the specification of semantics and its uncertainty aspects : keynote speech. In: Proceedings of the 2nd international symposium on spatial data quality 2003 : 19-20 March 2003, Hong Kong / ed. by Wenzhong Shi, M.F. Goodchild and P.F. Fisher. Hong Kong, The Hong Kong Polytechnic University
[107] Michael N.,DeMers.Fundmentals of Geographic Information Systems. New York,USA: John Wiley &Sons. 1997,Chapter 6,159-169
[108] Michael F. Goodchild,Gary J. Hunter.A simple positional accuracy measure for linear
features. ISSN 1365-8816,1997,11(3): 299-306
[109] Matej Gombosi,Borut Zalk and Sebastian Krivogard.Comparing two sets of polygons. ISSN 1365-8816,2003,17(5): 431-443
[110] M.J.C. Weir. Inconsistency of line convolution as a quality factor in the maintenance of spatial datbases : abstract. In: Spatial accuracy assessment in natural resources and environmental sciences : 2nd international symposium, May 21-23 1996, Colorado, pp. 713
[111] M. Lasserre. Errors derived from uncertainty in the accuracy of the Canadian national topographic series 1:50.000 maps . In: Canadian Journal of Remote Sensing, 15(1989)3, pp. 152-159
[112] Michael Worboys. Imprecision in Finite Resolution Spatial Data. ISSN 1384-6175, 1998,Vol.2 (3): 257-279
[113] M. Lasserre.Errors derived from uncertainty in the accuracy of the Canadian national topographic series 1:50,000 maps. In: Canadian Journal of Remote Sensing, 15(1989)3, pp. 152-159
[114] N.R. Chrisman. "The error component in spatial data" .in D.J. Maguire,M.F. Goodchild.and D.W.Rhind,(Eds.),Geographic information systems .Longman:Essesx,Vol(1),Chapter 12,165-174,1991
[115] N.J. Mulder, H. Middelkoop. Uncertainty in a GIS : proposal for a test for quantification of interpretation output. In: ISPRS 1990 : Vol. 28 : Commission Ⅲ : proceedings of the symposium progress in data analysis : May 20-25 1990, Wuhan, China, pp. 598-615
[116] N.J. Mulder, H. Middelkoop.Unceratinty in a GIS:proposal for a test for quantification of interpretation output. In: ISPRS 1990 : Vol. 28 : Commission Ⅲ : proceedings of the symposium progress in data analysis : May 20-25 1990, Wuhan, China, pp. 598-615
[117] Ola Ahlqvist,Johannes Keukelaar and Karim Oukbir.Rough classification and accuracy assessment. ISSN 1365-8816,2000,14(5): 475-496
[118] O.Kufoniyi etc. "Topology as Tool for Consistency Operations in Vector Maps", ISPRS 1994, Volume 30, Part 3/1
[119] Oliviera, J.P.de. Generation of Data Parameters in a GIS. 1992,MSC Thesis,ITC
[120] Phaedon C.Kyriakidis,Ashton M.Shortridge and Michael F.Goodchild.Geostatistics for conflation and accuracy assessment of digital elevation models. ISSN 1365-8816,1999,13(7): 677-707
[121] PhD thesis abstract: "Quality Assessment of SAR Interferometric Data", ITC
Journal 1998-3/4, p246
[122] P. D. Zwick and D. P. Costakis. Quality assurance for a local government geographic information system: A geo-facilities project perspective. ISSN 0198-9715, 1988, 12(1): 13-24
[123] Peter Fisher. Improved Modeling of Elevation Error with Geostatistics. ISSN 1384-6175,1998,2 (3): 215-233
[124]Q. Zhan, M. Molenaar, K. TempfliUncertainty assessment for geo-spatial objects derived from high-resolution airborne imagery and laser data. In: Proceedings of the 2nd international symposium on spatial data quality 2003 : 19-20 March 2003, Hong Kong / ed. by Wenzhong Shi, M.F. Goodchild and P.F. Fisher. - Hong Kong, The Hong Kong Polytechnic University. 2003. 79-88
[125]Qiming Zhou,Xuejun Liu.Error assessment of grid-based flow routing algorithms used in hydrological models. ISSN 1365-8816,2002,16(8): 819-842
[126]R.P. Nikhil, J.C. Bezdek.Measuring fuzzy uncertainty. IEEE transactions on fuzzy systems, 2(1994)2, pp. 107-118
[127] R.J. Ackermann. Quality control procedure for photogrammetric digital mapping. In: International Archives of Photogrammetry and Remote Sensing, 1996 Vol. XXXI, Part B4, pp. 12-17
[128] Stephan Winter. "Uncertainty of Topological Relations in GIS", ISPRS 1994, Volume 30, Part 3/2.
[129] Sylvie Servigne etc. " A Methodology for Spatial Consistency Improvement of Geographic Databases", ISSN 1384-6175,2000, 4(1):7-34
[130] Sophie Cockcroft. A Taxonomy of Spatial Data Integrity Constraints. ISSN 1384-6175, 1997 Vol.1 (4): 327-343
[131] Sophie Cockroft.The design and implementation of a repository for the management of spatial data integrity constraints. ISSN 1384-6175,2004,8(1): 49-69
[132] Sytze De Bruin,Arnold Bregt and Marc Van De Ven.Assessing fitness for use:the expected value of spatial data sets. ISSN 1365-8816,2001,15(5): TSSN 1365-8816
[133] Tor Bernhardsen: Geographic Information System: An Introduction (Second Edition)
[134] Tarmok K. Remmel,Ajith H.Perera.Accuracy of discontinuous binary surfaces:a case study using boreal forest fires. ISSN 1365-8816,2002,16(3): 287-298
[135] T.Oberthur etc. "Using Auxiliary Information to Adjust Fuzzy Membership Functions
for Improved Mapping of Soil Qualities", ISSN 1365-8816,2000, 14(5): 431-454.
[136] T. Bouloucos, Raja Ram Chhatkuli, Olajide Kufoniyi. A multi - theme vector data structure for modelling data quality in spatial databases. In: ISPRS 1994 : Vol. 30 : part 4, commission Ⅳ : proceedings of the symposium mapping and Geographic Information Systems : May 31 - June 3 1994, Athens, Georgia, USA / ed. by R. Welch and M. Remillard, pp. 649-656
[137]Veregin,H..Developing and Testing of An Error Propagation Model for GIS Overlay Operations. ISSN 1365-8816,1995,9(6): 595-619
[138]Veregin,H.V. Data Quality Parameters.In Geographic information systems: Principles and Technical Issues(Second Edition). Edited by P.A.Longley,M.F. Goodchild,D.J. Maguire and D.W. Rhind, Vol(1),pp 177-189.New York.USA: John Wiley & Sons
[139] Wenzhong Shi,Chui Kwan Cheung and Changqing Zhu.Modelling error propagation in vector-based buffer analysis. ISSN 1365-8816,2003,17(3): 251-271
[140] Wei GUO, Wenzhong SHI, Jun CHEN.Topological Consistency Check for Spatial Data.ISPRS Proceedings, Volume 32, Part 4 W12, pp.63-66
[141]Wilhelm Caspary and Robert Scheuring. Positional accuracy in spatial databases. ISSN 0198-9715,1993,17(2): 103-110
[142] Yee Leung,Jianping Yan.A locational error model for spatial features. ISSN 1365-8816,1998,12(6): 607-620
[2] CH 1003-95《测绘产品质量评定标准》.北京:国家测绘局,1995年
[3] 《4D测绘产品质量监督抽检实施细则》(报批稿).北京:国家测绘局,2001年
[4] 邸凯昌,李德仁,李德毅.Rough集理论及其在GIS属性分析和知识发现中的应用.ISSN 1671-8860 CN 42-1676/TN,1999,24(1):6-10
[5] 戴洪磊.矢量GIS中位置不确定性度量与传播的理论和方法.武汉:武汉测绘科技大学博士学位论文,2000年
[6] 杜道生,王占宏,马聪丽.空间数据质量模型研究.ISSN 1006-8961 CN 11-3758/TB,2000,5(7):559-562
[7] GB/T18316-2001《数字测绘产品检查验收规定和质量评定》.北京:国家质量技术监督局,2001年
[8] 龚健雅.地理信息系统基础.北京:科学出版社,2001年
[9] 郭仁忠.空间分析.武汉:武汉测绘科技大学出版社,1997年
[10] 胡鹏,吴艳兰,胡海.数字高程模型精度评定的基本理论.地球信息科学,2003,No.3,pp64-70
[11] 黄加纳.地图数字化的坐标转换及数据的精度与相关性.ISSN 1671-8860 CN 42-1676/TN,2001,26(3):213-216
[12] 郝向阳,钱曾波.地图扫描数字化的点位精度分析.ISSN 1001-1595 CN11-2089/P,1996,25(1):46-52
[13] 蒋景瞳等译.美国国家数字制图数据标准.北京:测绘出版社,1990年
[14] 李德仁,龚健雅,边馥苓.地理信息系统导论.北京:测绘出版社,1993年
[15] 林宗坚,钟业喜,陈天恩,黄福来.改善城市GIS数据库空间数据几何精度的一种试验方法.1994年地理信息系统学术讨论会论文集,pp329-338
[16] 林宗坚.地图扫描采样分辨率的研究.ISSN 1009-2307 CN 11-4415/P,2000,25(1):13-15
[17] 刘大杰,史文中,童小华,孙红春.GIS空间数据的精度分析与质量控制.上海:上海科学技术文献出版社,1999年
[18] 刘春,史文中,刘大杰.GIS属性数据精度的缺陷率度量统计模型.ISSN 1001-1595 CN11—2089/P,2003,32(1):36-41
[19] 刘文宝,邓敏,夏宗国.矢量GIS图上地理曲线的定位误差模型.CN 11-3841/TP,2000,4(4):316-320
[20] 刘文宝,邓敏,夏宗国.矢量GIS中属性数据的不确定性分析.ISSN 1001-1595 CN11-2089/P,2000,29(1):76-81
[21] 刘文宝.GIS空间数据的不确定性理论.武汉:武汉测绘科技大学博士学位论文,1995.5
[22] 刘文宝.矿图手工数字化位置数据系统误差的控制.ISSN 1006-9097 CN 11-3747/TD,1998,23(4):443-447
[23] 刘建军,王东华,商瑶玲.数字化等高线质量的软件自动检查方法.ISSN 1009-2307 CN 11-441 5/P,2001,26(4):36-38
[24] 刘建军,陈军,王东华等.等高线邻接关系的表达及应用研究.ISSN 1009-2307 CN 11-4415/P,2004,33(2)174-178
[25] 刘学军,龚健雅,周启鸣等.基于DEM坡度坡向算法精度的分析研究.ISSN 1009-2307 CN 11-4415/P,2004,33(3):258-263
[26] 柳宗伟,王新州,陈顺清.城市人口GIS中数据的不确定性.ISSN 1671-8860 CN 42-1676/TN,2002,27(6):627-631
[27] 李大军,龚健雅,谢刚生等.GIS中线元的误差熵带研究.ISSN 1671-8860 CN 42-1676/TN,2002,27(5):462-466
[28] 李大军,龚健雅,谢刚生等.GIS中面元的误差熵模型.ISSN 1001-1595 CN11-2089/P,2003,32(1):31-35
[29] 李大军,龚建雅,谢刚生.点位不确定性熵指标的确定.ISSN 1000-1433 CN 11-2025/TU,2002(2),pp.33-36
[30] 马龙,杜道生.GIS中DEM产品精度的分析和评价.ISSN 1007-3817 CN 42-1415/P,2003,28(3):4-5
[31] 史文中.地理信息系统中几何特征不确定性的通用模型:从1维到N维.ISSN 1001-1595 CN11-2089/P,1997,26(2):161-167
[32] 史文中,童小华,刘大杰.GIS中一般曲线的不确定性模型.CN 11-3841/TP,2000,29(1):52-57
[33] 史文中,王树良.GIS中属性不确定性综述.中国地理信息系统协会2001年年会论文集,172-189
[34] 史文中,王树良.GIS中属性不确定性的处理方法及其发展.CN 11-3841/TP,2002,6(5):394-400
[35] 史文中,刘春,刘大杰.基于一般抽样原理的GIS属性数据精度评定方法.ISSN 1671-8860 CN 42-1676/TN 2002,27(5):445-451
[36] 《数字地形图产品质量标准》(讨论稿).北京:国家测绘局,1995年
[37] 童小华,周德意.地形(籍)图扫描纠正的精度分析.ISSN 0253—374X CN 31-1267/N,31(1):77-81
[38] 邬伦,于海龙,高振纪,承继成.GIS不确定性框架体系与数据不确定性研究方法.地理学与国土研究,2002,18(4):1-5
[39] 毋河海.地图数据库系统[M].北京:测绘出版社,1990年
[40] 毋河海,龚健雅.地理信息系统(GIS)空间数据结构与处理技术.北京:测绘出版社,1997年
[41] 吴芳华,金澄.数字地图数据质量评价软件的设计.CN 61-1365/E,2001,21(2):43-47
[42] 吴芳华,金澄.矢量地图数据属性精度的检查与控制.ISSN 1009-427X CN 41-1205/P,2003,20(1):65-68
[43] 吴芳华,张跃鹏,金澄.GIS空间数据质量的评价.ISSN 1009-427X CN 41-1205/P,2001(1),63-66
[44] 许金钊编译.数理统计与产品质量.北京:中国标准出版社,1986年
[45] 阎正,城市地理信息标准化指南。北京:科学出版社,1999年
[46] 杨元喜,赵丽华,吴芳华等.地图数字化的精度评定与控制.CN 61-1365/E,2003,23(2):1-4
[47] 余晓红,刘大杰.地图数字化数据坐标变换的相关性分析.ISSN 1671-8860 CN 42-1676/TN,2002,27(5):456-460
[48] 杨启和,杨晓梅.数字化地形图数据处理方法分析.ISSN 0494-0911 CN 11-2246/P,1995,No.2:31-35
[49] 杨恒山.地图数字化中图纸定向的若干问题探讨.ISSN 1000-9779 CN 43-1073/U,17(2):43-48
[50] 杨元喜,赵丽华,吴芳华等.地图数字化的精度评定与控制.CN 61-1365/E,2003,23(2):1-4
[51] 张景雄,杜道生,孙家柄.用随机模拟方法建立矢量数据的误差模型.ISSN 1671-8860,2000,25(1):49-54
[52] 张景雄,杜道生.位置不确定性与属性不确定性的场模型.ISSN 1671-8860 CN 42-1676/TN,1999,28(3):244-249
[53] 周成虎.地理信息系统理论与方法.北京:中国科学技术大学出版社,1996年
[54] 曾衍伟.矢量GIS数据位置精度评价.ISSN 1007-3817 CN 42-1415/P,2002.
[55] 曾衍伟.影像数据质量检验与评价系统设计与实现.CN 11-3841/TP,2003,
[56] 曾衍伟.地形图扫描数字化图纸定向精度探讨.ISSN 0494-0911 CN 11-2246/P,2004.
[57] 曾衍伟.空间数据质量控制与评价方法及实现技术.ISSN 1671-8860 CN 42-1676/TN,2004.
[58] Andreas Busch, Felicitas Willrich. System Design for Automated Quality Control of GIS and Imagery. ISPRS 2002, Volume ⅩⅩⅩⅣ: 53-58
[59] Akos Detrekoi. Data quality management in GIS systems. Computers, Environment and Urban Systems, Volume 18, Issue 2, March-April 1994, PP. 81-85
[60] Alistair Geddes, Alessandro Gimona and David A. Elston. Estimating local variation in landuse statistics. ISSN 1365-8816, 2003, 17 (4) : 299-319
[61] Alex Hagen. Fuzzy set approach to assessing similarity of categorical maps. ISSN 1365-8816, 2003, 17 (3) : 235-249
[62] Anton J. J. Van Rompaey, Gerard Govers. Data quality and model comlexity for regional scale soil erosion prediction. IS SN 1365-8816, 2002, 16 (7) : 663-680
[63] Aronoff, S. , 1989. Geographic Information Systems: A Management Perspective. Ottawa, Ontario, Canada: WDL.
[64] Bishnu P. Phuyal, Robert W. Schmidley, J. Raul rami. Automatic Quality Control for GIS Data conversion. Surveying and Land Information Systems. 1997, 57 (1) : 37-41
[65] Burrough P. A. , Mcdonnell R. A. Principles of Geogrphical Information System. New York: Oxford University Press, 1998
[66] Bheshem Ramlal, J. E. Drummond. A GIS uncertainty subsystem. In: ISPRS 1992: Vol. 29: Part B3, commission Ⅲ, pp. 356-362
[67] Bernhardsen, Tor. Geographic Information Systems: An Introduction(Third Edition). New York, USA: John Wiley & Sons. 2002, PP. 215-234
[68] Curtis E. Woodcock, Suchatita Gopal. Fuzzy set theory and thematic maps: accuracy assessment and area estimation. ISSN 1365-8816, 2000, 14 (2) : 153-172
[69] Chrisman NR. Methods of spatial analysis based on error in categorical maps. phDThesis, University of Bristol, 1982a.
[70] Caspary W, Scheuring.Error-bands as measures of geometrical accuracy. Proceeding of EGIS' 92,1992, 226-233
[71] C.Lopez.Locating some types of random errors in Digital Terrain Models. ISSN 1365-8816,1997,11(7): 677-698
[72] C.P.J.M. van EIzakker, Bheshem Ramlal, J.E. Drummond. The visualization of GIS generated information quality . In: ISPRS 1992 : Vol. 29 : Part B4, commission IV, pp. 608-615
[73] Charles R.Ehlschlasger.Representing multiple spatial statistics in generalized elevation uncertainty models:moving beyond the variogram. ISSN 1365-8816,2002,16(3): 259-285
[74] C. Victor WuBarbara P. Buttenfield. Spatial data quality and its evaluation. ISSN 0198-9715, 1994, 18(3): 153-165
[75] Dong-Gyu Park, Hwan-Gue Cho.A Verification System for the Accuracy of the Digital Map. ADVANCES IN GIS RESEARCH II.Proceedings of the 7th InternationalSymposium on Spatial Data Handling, 1996: 287-299
[76] Drummond J.,Brown A.,Du Daosheng,etc.The development of a GIS information quality module. Archives of Spatial Accuracy Assessment in Natural Resources and Environmental Sciences: Second International Symposium.May 1996,pp. 189~198
[77] D.L. Moody. Metrics for evaluating the quality of entity relationship models. In: Conceptual modeling ER'98 : 17th international conference on conceptual modeling, Singapore November 16-19, 1998. pp. 211-225
[78] Giuseppe Arbia,Daniel Griffith and Roabert Haining.Error propagation modelling in raster GIS:overlay operations. ISSN 1365-8816,1998,12(2): 145-167
[79] Gerard B.M. Heuvelink.Identification of field attribute error under different models of spatial variation. ISSN 1365-8816,1996,10(8): 921-935
[80] G. Pillirone , D. Visintini. A Package for the Management of Data Quality in Geographic Information Systems[A]. Edited by L. Mussio, G. Forlani, F. Crosilia. Data Acquisition and Analysis for Multimedia GIS, Spinger Wien New York, pp77-86
[81] G. Edwards etc."Spatial Error and Uncertainty and the Decision-Making Process", Spatail Data Handling 2000 Conference Proceedings, pp6a.26-36.
[82] Herring, J, R.TIGRIS:Topologically Integrated Geographic Information System.In Proceedings of Auto Carto 8, Baltimore, edited by N.R.Chrisman, American Society for
Photoprammetry and Remote Sensing and American Congress on Surveying and Mapping, pp.282-291, 1987
[83] Hong Jiang,J.Ronald Eastman.Application of fuzzy measures in multi-criteria evaluation in GIS. ISSN 1365-8816,2000,14(2): 173-184
[84] Howard Veregin. " Error Propagation through the Buffer Operation for Probability Surface", Photogrammetric Engineering & Remote Sensing, Vol.62, No.4, April 1996, pp.419-428
[85] Havard Tveite,Sindre Langaas.An accuracy assessment method for grographical line data sets based on buffering. ISSN 1365-8816,1999,13(1): 27-47
[86] Hayati TASTAN , M.Orhan ALTAN.Auomatic Checking of Feature and Attribute Consistency of a Spatial Database. ISPRS 2000, Volume XXXIII: 1066-1073
[87] Howard VereginDavid P. Lanter. Data-quality enhancement techniques in layer-based geographic information systems. ISSN 0198-9715, 1995,19(1): 23-36
[88]Howard Verrgin.Quantifying positional errorr induced by line simplification. ISSN 1365-8816,2000,14(2): 113-130
[89] Igor V. Florinsky.Errors of signal processing in digital terrain modelling. ISSN 1365-8816,2002,16(5): 475-501
[90] Joshua Greenfeld.Evaluating the Accuracy of Digital Orthophoto Quadrangles(DOQ) in the Context of Parcel-Based GIS[J]. Photogrammetric Engineering & Remote Sensing, 2001, 67(2): 199-205
[91] Jerry H.Ratcliffe.On the accuracy of TIGER-type geocoded addess data in relation to cadastral and census areal units. ISSN 1365-8816,2001,15(5): 473-485
[92] J. P. Mills and I. Newton. A new approach to the verification and revision of large-scale mapping. ISPRS Journal of Photogrammetry and Remote Sensing, Volume 51, Issue 1, February 1996, Pages 17-27
[93] J.E. Drummond, A. Brown, Du Daosheng, C.P.J.M. van Elzakker.The development of a GIS information quality module. Spatial accuracy assessment in natural resources and environmental sciences : 2nd international symposium, May 21-23 1996, Colorado, pp. 189-198
[94] Kim Lowell etc. "Combining Map Geometry and Polygon Attributes to Estimate Spatial Uncertainty from Multiple Realisations", Spatail Data Handling 2000 Conference Proceedings, pp5a.32-43
[95] Kelly Chan. DIGEST A primer for the International GIS Standard[M], pp.117-120.CRC Press LLC, 1999
[96] K. Kraus and H. Kager. Accuracy of derived data in a geographic information system . ISSN 0198-9715, 1994,18(2): 87-94
[97] Lawrence V. Stanislawski etc." Estimating Positional Accuracy of Data Layers within a GIS through Error Propagation", Photogrammetric Engineering & Remote Sensing, Vol.62, No.4, April 1996, pp.429-433.
[98] Larry E.Stanfel etc. "Reliability of Polygonal Boundary of Land Parcel", Journal of Surverying Engineering, November 1995
[99] Lemonia Ragia, Stephan Winter. Contributions to a quality description of areal objects in spatial data sets. ISPRS Journal of Photogrammetry & Sensing 55(2000): 201-213
[100] Lowell,K. and Jaton.A.Spatial Accuracy Assessment:Land Information Uncertainty in Natural Resources.2001,Ann Arbor Press,Chelsea,Michigan
[101] Michele Crosetto,Stefano Tarantola.Uncertainty and sensitivity analysisrtools for GIS-based model implementation. ISSN 1365-8816,2001,15(5): 415-437
[102] Matt Duckham.Jane Drummond.Assessment of error in digital vector data using fractal geometry. ISSN 1365-8816,2000,14(1): 67-84
[103] Mark Gahegan, Manfred Ehlers .A Framework for the modelling of uncertainty between remote sensing and geographic information systems.ISPRS Journal of Photogrammetry & Sensing 55(2000)176-188
[104] Martien Molenaar, . "An Introduction to the Theory of Spatial Object Modelling for GIS", Published in 1998
[105] Martien Molenaar.Three conceptual uncertainty levels for spatial objects.International Archives of Photogrammetry and Remote Sensing.Vol.XXXIII,Part B4.Amsterdam 2000.pp.670-677
[106] Martien Molenaar.Spatial data modelling and the specification of semantics and its uncertainty aspects : keynote speech. In: Proceedings of the 2nd international symposium on spatial data quality 2003 : 19-20 March 2003, Hong Kong / ed. by Wenzhong Shi, M.F. Goodchild and P.F. Fisher. Hong Kong, The Hong Kong Polytechnic University
[107] Michael N.,DeMers.Fundmentals of Geographic Information Systems. New York,USA: John Wiley &Sons. 1997,Chapter 6,159-169
[108] Michael F. Goodchild,Gary J. Hunter.A simple positional accuracy measure for linear
features. ISSN 1365-8816,1997,11(3): 299-306
[109] Matej Gombosi,Borut Zalk and Sebastian Krivogard.Comparing two sets of polygons. ISSN 1365-8816,2003,17(5): 431-443
[110] M.J.C. Weir. Inconsistency of line convolution as a quality factor in the maintenance of spatial datbases : abstract. In: Spatial accuracy assessment in natural resources and environmental sciences : 2nd international symposium, May 21-23 1996, Colorado, pp. 713
[111] M. Lasserre. Errors derived from uncertainty in the accuracy of the Canadian national topographic series 1:50.000 maps . In: Canadian Journal of Remote Sensing, 15(1989)3, pp. 152-159
[112] Michael Worboys. Imprecision in Finite Resolution Spatial Data. ISSN 1384-6175, 1998,Vol.2 (3): 257-279
[113] M. Lasserre.Errors derived from uncertainty in the accuracy of the Canadian national topographic series 1:50,000 maps. In: Canadian Journal of Remote Sensing, 15(1989)3, pp. 152-159
[114] N.R. Chrisman. "The error component in spatial data" .in D.J. Maguire,M.F. Goodchild.and D.W.Rhind,(Eds.),Geographic information systems .Longman:Essesx,Vol(1),Chapter 12,165-174,1991
[115] N.J. Mulder, H. Middelkoop. Uncertainty in a GIS : proposal for a test for quantification of interpretation output. In: ISPRS 1990 : Vol. 28 : Commission Ⅲ : proceedings of the symposium progress in data analysis : May 20-25 1990, Wuhan, China, pp. 598-615
[116] N.J. Mulder, H. Middelkoop.Unceratinty in a GIS:proposal for a test for quantification of interpretation output. In: ISPRS 1990 : Vol. 28 : Commission Ⅲ : proceedings of the symposium progress in data analysis : May 20-25 1990, Wuhan, China, pp. 598-615
[117] Ola Ahlqvist,Johannes Keukelaar and Karim Oukbir.Rough classification and accuracy assessment. ISSN 1365-8816,2000,14(5): 475-496
[118] O.Kufoniyi etc. "Topology as Tool for Consistency Operations in Vector Maps", ISPRS 1994, Volume 30, Part 3/1
[119] Oliviera, J.P.de. Generation of Data Parameters in a GIS. 1992,MSC Thesis,ITC
[120] Phaedon C.Kyriakidis,Ashton M.Shortridge and Michael F.Goodchild.Geostatistics for conflation and accuracy assessment of digital elevation models. ISSN 1365-8816,1999,13(7): 677-707
[121] PhD thesis abstract: "Quality Assessment of SAR Interferometric Data", ITC
Journal 1998-3/4, p246
[122] P. D. Zwick and D. P. Costakis. Quality assurance for a local government geographic information system: A geo-facilities project perspective. ISSN 0198-9715, 1988, 12(1): 13-24
[123] Peter Fisher. Improved Modeling of Elevation Error with Geostatistics. ISSN 1384-6175,1998,2 (3): 215-233
[124]Q. Zhan, M. Molenaar, K. TempfliUncertainty assessment for geo-spatial objects derived from high-resolution airborne imagery and laser data. In: Proceedings of the 2nd international symposium on spatial data quality 2003 : 19-20 March 2003, Hong Kong / ed. by Wenzhong Shi, M.F. Goodchild and P.F. Fisher. - Hong Kong, The Hong Kong Polytechnic University. 2003. 79-88
[125]Qiming Zhou,Xuejun Liu.Error assessment of grid-based flow routing algorithms used in hydrological models. ISSN 1365-8816,2002,16(8): 819-842
[126]R.P. Nikhil, J.C. Bezdek.Measuring fuzzy uncertainty. IEEE transactions on fuzzy systems, 2(1994)2, pp. 107-118
[127] R.J. Ackermann. Quality control procedure for photogrammetric digital mapping. In: International Archives of Photogrammetry and Remote Sensing, 1996 Vol. XXXI, Part B4, pp. 12-17
[128] Stephan Winter. "Uncertainty of Topological Relations in GIS", ISPRS 1994, Volume 30, Part 3/2.
[129] Sylvie Servigne etc. " A Methodology for Spatial Consistency Improvement of Geographic Databases", ISSN 1384-6175,2000, 4(1):7-34
[130] Sophie Cockcroft. A Taxonomy of Spatial Data Integrity Constraints. ISSN 1384-6175, 1997 Vol.1 (4): 327-343
[131] Sophie Cockroft.The design and implementation of a repository for the management of spatial data integrity constraints. ISSN 1384-6175,2004,8(1): 49-69
[132] Sytze De Bruin,Arnold Bregt and Marc Van De Ven.Assessing fitness for use:the expected value of spatial data sets. ISSN 1365-8816,2001,15(5): TSSN 1365-8816
[133] Tor Bernhardsen: Geographic Information System: An Introduction (Second Edition)
[134] Tarmok K. Remmel,Ajith H.Perera.Accuracy of discontinuous binary surfaces:a case study using boreal forest fires. ISSN 1365-8816,2002,16(3): 287-298
[135] T.Oberthur etc. "Using Auxiliary Information to Adjust Fuzzy Membership Functions
for Improved Mapping of Soil Qualities", ISSN 1365-8816,2000, 14(5): 431-454.
[136] T. Bouloucos, Raja Ram Chhatkuli, Olajide Kufoniyi. A multi - theme vector data structure for modelling data quality in spatial databases. In: ISPRS 1994 : Vol. 30 : part 4, commission Ⅳ : proceedings of the symposium mapping and Geographic Information Systems : May 31 - June 3 1994, Athens, Georgia, USA / ed. by R. Welch and M. Remillard, pp. 649-656
[137]Veregin,H..Developing and Testing of An Error Propagation Model for GIS Overlay Operations. ISSN 1365-8816,1995,9(6): 595-619
[138]Veregin,H.V. Data Quality Parameters.In Geographic information systems: Principles and Technical Issues(Second Edition). Edited by P.A.Longley,M.F. Goodchild,D.J. Maguire and D.W. Rhind, Vol(1),pp 177-189.New York.USA: John Wiley & Sons
[139] Wenzhong Shi,Chui Kwan Cheung and Changqing Zhu.Modelling error propagation in vector-based buffer analysis. ISSN 1365-8816,2003,17(3): 251-271
[140] Wei GUO, Wenzhong SHI, Jun CHEN.Topological Consistency Check for Spatial Data.ISPRS Proceedings, Volume 32, Part 4 W12, pp.63-66
[141]Wilhelm Caspary and Robert Scheuring. Positional accuracy in spatial databases. ISSN 0198-9715,1993,17(2): 103-110
[142] Yee Leung,Jianping Yan.A locational error model for spatial features. ISSN 1365-8816,1998,12(6): 607-620