DEM质量检查与精度评定研究
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摘要
空间数据质量的好坏直接影响着GIS的应用;作为国家地理信息的基础数据之一的DEM的质量成为人们日益关注的焦点。
对于任意一个DEM项目,精度、效率和经济效益是首要考虑的三个因素。其中,精度是最重要的因素。假如精度无法得到保证,那么效率和经济效益就无从谈起。因此,DEM精度成为DEM的研究热点之一,具有十分重要的理论意义和应用价值。
本文在系统地分析误差的产生、误差的传播、误差的不确定性,详细总结、分析各种DEM质量检查与精度评定模型的基础上,重点研究了对规则格网DEM进行粗差探测问题。主要进行了以下两方面的研究:
1)在趋势面拟合粗差探测方法中引入抗差估计,比较了最小二乘曲面拟合法和抗差最小二乘曲面拟合法的拟合效果;
2)提出了顾及地形特征的粗差探测方法,即先提取出地形特征点,对地形特征点和普通地形点分别使用分段曲线拟合法和抗差最小二乘曲面拟合法进行粗差探测;
研究表明,抗差最小二乘曲面拟合法对规则格网DEM粗差探测具有一定抗粗差能力,因而具有更好的粗差探测效果;对地形特征点和普通地形点使用不同的粗差探测方法,一定程度上降低了地形特征点对DEM粗差探测的影响;
此外,结合生产实际,利用Visual Basic6.0+ArcEngine开发出一套以既有地形图为数据源的DEM质量检查与精度评定实验系统。除基本GIS功能外,主要实现了格网点粗差检查、内插点精度统计、图幅接边精度统计、等高线叠加精度统计,以及分层设色、生成晕渲图、三维DEM等可视化辅助检查功能。
其中对格网点粗差检查、内插点精度统计和等高线叠加精度统计进行了更加深入的研究。研究表明,对于等高线叠加精度统计,原始等高线与反演等高线叠加的方法对DEM精度评定更加全面可靠、精度统计结果具有唯一性。
Spatial data quality has a direct impact on the application of GIS. DEM is one of Nation's Fundamental Geographic Information, and its quality has been increasingly becoming people's focus.
For any DEM project, precision, efficiency, and benefit are three main factors to be considered. Among these factors, precision is most important. Provided that precision can't be guaranteed, efficiency and benefit can't be gained. Therefore, the precision of DEM has gained more and more researcher's attention. The research of DEM's quality has both theory and application significance.
Based on the systematic analysis of error's generation, propagation and uncertainty, and detailed summarization and analysis of many DEM quality inspection and precision valuation models, this thesis mainly researched into gross error detection for grid DEM. Its main contents are summed up as follows.
1) The thesis had brought robust estimation into bend surface fitting algorithm and compared the effect of least squares surface fitting algorithm with robust estimation of least squares surface fitting algorithm.
2) The thesis also put forward a method of gross error detection considering the topographic characteristic, the method extracted topographic feature point and employed subsection curve fitting algorithm and robust estimation of least squares surface fitting algorithm for topographic feature point and common topographic point respectively.
It is shown that robust estimation of least squares surface fitting algorithm for grid DEM can reduce gross errors to a certain extent. So it has a better result too. It has reduced the influence of topographic feature point on DEM gross error detection to employ different gross error detection methods for topographic feature point and common topographic point respectively.
Furthermore, we also developed an application system of DEM quality inspection and precision evaluation with Visual Basic6.0+ArcEngine on the basis of topographic maps. Besides basic GIS functions, the system has realized some special functions which are listed as follows: gross errors detection for grid points, interpolation precision evaluation, chart junction precision evaluation and contour superposition precision evaluation, as well as creating hypsometric maps, hill-shading map, 3D DEM and other visualized assistant inspection functions.
Among which, we have done some deep research into gross errors detection for grid points, interpolation precision evaluation, contour superposition precision evaluation. And the results show that, for contour superposition precision evaluation, the superposition of original contour and derived contour has performed much better and had a more completed and reliable result of DEM precision evaluation, and the result is only and stable too.
对于任意一个DEM项目,精度、效率和经济效益是首要考虑的三个因素。其中,精度是最重要的因素。假如精度无法得到保证,那么效率和经济效益就无从谈起。因此,DEM精度成为DEM的研究热点之一,具有十分重要的理论意义和应用价值。
本文在系统地分析误差的产生、误差的传播、误差的不确定性,详细总结、分析各种DEM质量检查与精度评定模型的基础上,重点研究了对规则格网DEM进行粗差探测问题。主要进行了以下两方面的研究:
1)在趋势面拟合粗差探测方法中引入抗差估计,比较了最小二乘曲面拟合法和抗差最小二乘曲面拟合法的拟合效果;
2)提出了顾及地形特征的粗差探测方法,即先提取出地形特征点,对地形特征点和普通地形点分别使用分段曲线拟合法和抗差最小二乘曲面拟合法进行粗差探测;
研究表明,抗差最小二乘曲面拟合法对规则格网DEM粗差探测具有一定抗粗差能力,因而具有更好的粗差探测效果;对地形特征点和普通地形点使用不同的粗差探测方法,一定程度上降低了地形特征点对DEM粗差探测的影响;
此外,结合生产实际,利用Visual Basic6.0+ArcEngine开发出一套以既有地形图为数据源的DEM质量检查与精度评定实验系统。除基本GIS功能外,主要实现了格网点粗差检查、内插点精度统计、图幅接边精度统计、等高线叠加精度统计,以及分层设色、生成晕渲图、三维DEM等可视化辅助检查功能。
其中对格网点粗差检查、内插点精度统计和等高线叠加精度统计进行了更加深入的研究。研究表明,对于等高线叠加精度统计,原始等高线与反演等高线叠加的方法对DEM精度评定更加全面可靠、精度统计结果具有唯一性。
Spatial data quality has a direct impact on the application of GIS. DEM is one of Nation's Fundamental Geographic Information, and its quality has been increasingly becoming people's focus.
For any DEM project, precision, efficiency, and benefit are three main factors to be considered. Among these factors, precision is most important. Provided that precision can't be guaranteed, efficiency and benefit can't be gained. Therefore, the precision of DEM has gained more and more researcher's attention. The research of DEM's quality has both theory and application significance.
Based on the systematic analysis of error's generation, propagation and uncertainty, and detailed summarization and analysis of many DEM quality inspection and precision valuation models, this thesis mainly researched into gross error detection for grid DEM. Its main contents are summed up as follows.
1) The thesis had brought robust estimation into bend surface fitting algorithm and compared the effect of least squares surface fitting algorithm with robust estimation of least squares surface fitting algorithm.
2) The thesis also put forward a method of gross error detection considering the topographic characteristic, the method extracted topographic feature point and employed subsection curve fitting algorithm and robust estimation of least squares surface fitting algorithm for topographic feature point and common topographic point respectively.
It is shown that robust estimation of least squares surface fitting algorithm for grid DEM can reduce gross errors to a certain extent. So it has a better result too. It has reduced the influence of topographic feature point on DEM gross error detection to employ different gross error detection methods for topographic feature point and common topographic point respectively.
Furthermore, we also developed an application system of DEM quality inspection and precision evaluation with Visual Basic6.0+ArcEngine on the basis of topographic maps. Besides basic GIS functions, the system has realized some special functions which are listed as follows: gross errors detection for grid points, interpolation precision evaluation, chart junction precision evaluation and contour superposition precision evaluation, as well as creating hypsometric maps, hill-shading map, 3D DEM and other visualized assistant inspection functions.
Among which, we have done some deep research into gross errors detection for grid points, interpolation precision evaluation, contour superposition precision evaluation. And the results show that, for contour superposition precision evaluation, the superposition of original contour and derived contour has performed much better and had a more completed and reliable result of DEM precision evaluation, and the result is only and stable too.
引文
[1]李志林,朱庆.数字高程模型[M].武汉:武汉大学出版社,2003
[2]Hannah,M.,J.1981.Error Detection and Correction in Digital Terrain Models[J].Photogrammetric Engineering and Remote Sensing.23(47):pp.63-69
[3]单杰.一种交互式DEM粗差检测方法[J]。解放军测绘学院学报,1993,15(2):28-31
[4]Felicisimo,A.,1994.Parametric Statistical Method for Error Detection in Digital Elevation Models[J].ISPRS Journal of Photogrammetry and Remote Sensing.42(49):pp.29-33
[5]LOPEZ,C.,1997.Locating Types of Random Science in Digital Terrain Models.International Journal of Geographic Information,34(11):pp.677-698
[6]LOPEZ,C.,2000.On the Improving of Elevation Accuracy of Digital Elevation Models[J].A Comparison of Some Error Detecting Procedures.Transactions in GIS,25(4):pp.43-64
[7]杨晓云,顾利亚,岑敏仪,李志林.基于不同大小窗口移动曲面拟合法探测DEM粗差的一种方法[J].测绘学报,2005,34(2):148-153
[8]胡鹏,吴艳兰,胡海等。数字高程模型精度评定的基本理论[J].地球信息科学,2003,5(3):64-69
[9]汤国安,龚建雅。数字高程模型地形描述精度量化模拟研究[J].测绘学报,2001,30(4):361-365
[10]周启鸣,刘学军.数字地形分析[M]。北京:科学出版社,2006
[11]王光霞,崔凯,戴军。基于分形的DEM精度评估[J]。测绘学院学报,2005,22(2):107-109
[12]汤国安.等高线套合差及在DEM质量评价中的应用研究[J].测绘通报,2007,32(7):65-67
[13]朱长青,王志伟,刘海砚.基于重构等高线的DEM精度评估模型[J].武汉大学学报(信息科学版),2008,35(2):78-82
[14]史文中.空间数据与空间分析不确定性原理[M].北京:科学出版社,2005
[15]危拥军,祝志明。DEM精度评估与质量控制方法研究[J]。测绘科学与工程,2004,22(4):6-7
[16]汤国安,刘学军,闾国年.数字高程模型及地学分析的原理与方法[M]。北京:科学出 版社,2005
[17]李德仁。对空间数据不确定性研究的思考[J].测绘科学技术学报,2006,23(6):391-393
[18]Paul A.Longley Michael F.Goodchild等著,张晶,刘瑜,张洁等译.地理信息系统与科学[M].机械工业出版社,2007
[19]王光霞,朱长青.数字高程模型地形描述精度的研究[J]。测绘学报,2004,33(2):168-172
[20]国家测绘局.《中华人民共和国测绘行业标准-测绘产品质量评定标准CH 1003-95》
[21]曾衍伟.空间数据质量控制与评价技术体系研究[博士论文].武汉:武汉大学.2004
[22]王淑萍,朱长青。基于双二次插值多项式的DEM传递误差模型[J].测绘科学技术学报,2006,23(1):33-35
[23]国家质量技术监督局.数字测绘产品检查验收规定和质量评定,2001
[24]黄宏波,梁鑫,杨晓云等.基于参数统计的DEM粗差探测算法[J].测绘学报,2008,37(1):23-28
[25]杨元喜.抗差估计理论及其应用[M]。北京:八一出版社,1993
[26]李德仁,袁修孝。误差处理与可靠性理论[M]。湖北:武汉大学出版社,2002
[27]高伟,姜水生.分段曲线拟合与离散度加权的数据误差处理方法[J].中国测试技术,2005,31(6):55-57
[28]Jenson,S.K.,1991.Applications of Hydrologic Information Automatically Extracted from Digital Elevation Models[J].Hydrologic Process,34(5):pp.31-44
[29]黄建.数字高程模型的质量检查[J].测绘通报,2002,27(2):55-56
[30]朱长青.数值计算方法及其应用[M].北京:科学出版社,2006
[31]靳海亮,高井祥。基于矢量等高线数据提取山脊线山谷线的研究[J]。测绘通报,2005,30(4):15-17
[32]李金海。误差理论与测量不确定度评定[M]。北京:中国计量出版社,2003
[33]杨晓云,顾利亚,岑敏仪.数字高程模型的误差处理与精度评估[J].铁道勘察,2004,31(5):20-24
[34]国家测绘局.1:1万数字高程模型生产技术规定.1998
[35]柯正谊,何建帮,池天河.数字地面模型[M].北京:科学出版社,1993
[36]汤国安,赵牡丹.地理信息系统[M].北京:科学出版社,2001
[37]吕希奎,易思蓉,韩春华。基于坡度RMSE与3维可视化的格网DEM粗差检测与剔除[J]. 测绘通报,2007,32(9):23-26
[38]王东华,刘建军,商瑶玲.全国1:25万数字高程模型数据库的设计与建库[J].测绘通报,2001,26(1):27-29
[39]眭海刚,朱庆。一种从DLG生成高质量DEM的混合方式[J]。测绘通报,2006,31(4):16-18
[40]冯克忠,姜遵锋,徐杨,崔纪锋.ArcObjects开发指南(VB篇)。电子工业出版社,2007
[41]蒋波涛.ArcObjects开发基础与技术-基于VisualBasic.net.武汉:武汉大学出版社,2006
[42]马修斯(美)等著,周璐等译.数值方法(MATLAB版)[M]。北京:电子工业出版社,2005
[43]王春。规则格网DEM地形描述形态精度研究[J].地理信息世界,2008,34(2):45-47
[44]雷蓉,丘振戈等.基于遥感影像生成DEM的质量检查[J].测绘通报,2005,30(4):36-38
[45]Zhilin Li.1992.Variation of the Accuracy of Digital Terrain Models with Sampling Interval,Photogrammetric Record,36(14):pp.98-102
[46]ESRI公司.ArcGIS Engme开发指南.美国:ESRI公司,2006
[47]Rees,W.G.,2000.The Accuracy of Digital Elevation Interpolated to Higher Resolutions [J].International Journal of Remote Sensing,21(1):pp.7-20
[48]Kyriakidis,P.C.,Shortridge,A.M.,Goodchild,M.F.,1999.Geostatistics for Conflation and Accuracy Assessment of Digital Elevation Models[J].International Journal of Geographical Information Science,13(7):pp.77-82
[49]Kidner,D.B.,2003.Higher-Order Interpolation of Regular Grid Digital Elevation Models [J].International Journal of Remote Sensing,(14):pp.55-59
[50]Rees,W.G.,2000.The Accuracy of Digital Elevation Interpolated to Higher Resolutions [J].International Journal of Remote Sensing,18(1):pp.7-20
[51]Shi,W.Z.,Li,Q.Q.,Zhu,C.Q.,2005.Estimating the Propagation Error of DEM from Higher-Order Interpolation Algorithms[J].international Journal of Remote Sensing,26(14):pp.3069-3084
[2]Hannah,M.,J.1981.Error Detection and Correction in Digital Terrain Models[J].Photogrammetric Engineering and Remote Sensing.23(47):pp.63-69
[3]单杰.一种交互式DEM粗差检测方法[J]。解放军测绘学院学报,1993,15(2):28-31
[4]Felicisimo,A.,1994.Parametric Statistical Method for Error Detection in Digital Elevation Models[J].ISPRS Journal of Photogrammetry and Remote Sensing.42(49):pp.29-33
[5]LOPEZ,C.,1997.Locating Types of Random Science in Digital Terrain Models.International Journal of Geographic Information,34(11):pp.677-698
[6]LOPEZ,C.,2000.On the Improving of Elevation Accuracy of Digital Elevation Models[J].A Comparison of Some Error Detecting Procedures.Transactions in GIS,25(4):pp.43-64
[7]杨晓云,顾利亚,岑敏仪,李志林.基于不同大小窗口移动曲面拟合法探测DEM粗差的一种方法[J].测绘学报,2005,34(2):148-153
[8]胡鹏,吴艳兰,胡海等。数字高程模型精度评定的基本理论[J].地球信息科学,2003,5(3):64-69
[9]汤国安,龚建雅。数字高程模型地形描述精度量化模拟研究[J].测绘学报,2001,30(4):361-365
[10]周启鸣,刘学军.数字地形分析[M]。北京:科学出版社,2006
[11]王光霞,崔凯,戴军。基于分形的DEM精度评估[J]。测绘学院学报,2005,22(2):107-109
[12]汤国安.等高线套合差及在DEM质量评价中的应用研究[J].测绘通报,2007,32(7):65-67
[13]朱长青,王志伟,刘海砚.基于重构等高线的DEM精度评估模型[J].武汉大学学报(信息科学版),2008,35(2):78-82
[14]史文中.空间数据与空间分析不确定性原理[M].北京:科学出版社,2005
[15]危拥军,祝志明。DEM精度评估与质量控制方法研究[J]。测绘科学与工程,2004,22(4):6-7
[16]汤国安,刘学军,闾国年.数字高程模型及地学分析的原理与方法[M]。北京:科学出 版社,2005
[17]李德仁。对空间数据不确定性研究的思考[J].测绘科学技术学报,2006,23(6):391-393
[18]Paul A.Longley Michael F.Goodchild等著,张晶,刘瑜,张洁等译.地理信息系统与科学[M].机械工业出版社,2007
[19]王光霞,朱长青.数字高程模型地形描述精度的研究[J]。测绘学报,2004,33(2):168-172
[20]国家测绘局.《中华人民共和国测绘行业标准-测绘产品质量评定标准CH 1003-95》
[21]曾衍伟.空间数据质量控制与评价技术体系研究[博士论文].武汉:武汉大学.2004
[22]王淑萍,朱长青。基于双二次插值多项式的DEM传递误差模型[J].测绘科学技术学报,2006,23(1):33-35
[23]国家质量技术监督局.数字测绘产品检查验收规定和质量评定,2001
[24]黄宏波,梁鑫,杨晓云等.基于参数统计的DEM粗差探测算法[J].测绘学报,2008,37(1):23-28
[25]杨元喜.抗差估计理论及其应用[M]。北京:八一出版社,1993
[26]李德仁,袁修孝。误差处理与可靠性理论[M]。湖北:武汉大学出版社,2002
[27]高伟,姜水生.分段曲线拟合与离散度加权的数据误差处理方法[J].中国测试技术,2005,31(6):55-57
[28]Jenson,S.K.,1991.Applications of Hydrologic Information Automatically Extracted from Digital Elevation Models[J].Hydrologic Process,34(5):pp.31-44
[29]黄建.数字高程模型的质量检查[J].测绘通报,2002,27(2):55-56
[30]朱长青.数值计算方法及其应用[M].北京:科学出版社,2006
[31]靳海亮,高井祥。基于矢量等高线数据提取山脊线山谷线的研究[J]。测绘通报,2005,30(4):15-17
[32]李金海。误差理论与测量不确定度评定[M]。北京:中国计量出版社,2003
[33]杨晓云,顾利亚,岑敏仪.数字高程模型的误差处理与精度评估[J].铁道勘察,2004,31(5):20-24
[34]国家测绘局.1:1万数字高程模型生产技术规定.1998
[35]柯正谊,何建帮,池天河.数字地面模型[M].北京:科学出版社,1993
[36]汤国安,赵牡丹.地理信息系统[M].北京:科学出版社,2001
[37]吕希奎,易思蓉,韩春华。基于坡度RMSE与3维可视化的格网DEM粗差检测与剔除[J]. 测绘通报,2007,32(9):23-26
[38]王东华,刘建军,商瑶玲.全国1:25万数字高程模型数据库的设计与建库[J].测绘通报,2001,26(1):27-29
[39]眭海刚,朱庆。一种从DLG生成高质量DEM的混合方式[J]。测绘通报,2006,31(4):16-18
[40]冯克忠,姜遵锋,徐杨,崔纪锋.ArcObjects开发指南(VB篇)。电子工业出版社,2007
[41]蒋波涛.ArcObjects开发基础与技术-基于VisualBasic.net.武汉:武汉大学出版社,2006
[42]马修斯(美)等著,周璐等译.数值方法(MATLAB版)[M]。北京:电子工业出版社,2005
[43]王春。规则格网DEM地形描述形态精度研究[J].地理信息世界,2008,34(2):45-47
[44]雷蓉,丘振戈等.基于遥感影像生成DEM的质量检查[J].测绘通报,2005,30(4):36-38
[45]Zhilin Li.1992.Variation of the Accuracy of Digital Terrain Models with Sampling Interval,Photogrammetric Record,36(14):pp.98-102
[46]ESRI公司.ArcGIS Engme开发指南.美国:ESRI公司,2006
[47]Rees,W.G.,2000.The Accuracy of Digital Elevation Interpolated to Higher Resolutions [J].International Journal of Remote Sensing,21(1):pp.7-20
[48]Kyriakidis,P.C.,Shortridge,A.M.,Goodchild,M.F.,1999.Geostatistics for Conflation and Accuracy Assessment of Digital Elevation Models[J].International Journal of Geographical Information Science,13(7):pp.77-82
[49]Kidner,D.B.,2003.Higher-Order Interpolation of Regular Grid Digital Elevation Models [J].International Journal of Remote Sensing,(14):pp.55-59
[50]Rees,W.G.,2000.The Accuracy of Digital Elevation Interpolated to Higher Resolutions [J].International Journal of Remote Sensing,18(1):pp.7-20
[51]Shi,W.Z.,Li,Q.Q.,Zhu,C.Q.,2005.Estimating the Propagation Error of DEM from Higher-Order Interpolation Algorithms[J].international Journal of Remote Sensing,26(14):pp.3069-3084