面向区域增量更新的等高线群混合相似性度量模型
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摘要
等高线是一种以曲线群簇展现地表起伏形态的表达方式,多源等高线数据之间的相似度能够反映地形地貌的变化程度,因此等高线群的相似性度量是地形图更新、多源数据融合及制图综合领域的关键环节之一。当前的等高线相似性度量方法主要基于要素的单一拓扑特征或几何特征,由于地理空间数据的复杂性和地理要素变化的多样性,这种通过计量多源数据数据单一特征之间的相似与差异程度的方法并不能完整表达多源数据之间的异同,在变化复杂区域、图幅边界区域以及等高线分布密集区域会导致不一致问题。因此,本文引入空间相似度理论,综合探讨了等高线群的相似性层次结构;研究了拓扑特征和几何特征在等高线群相似性度量中的关系和作用机理,构建了等高线群相似性层次结构;讨论了其中各个影响要素的相互关系和相似性度量方法,提出了一种基于拓扑特征和几何特征的区域等高线群混合相似性度量模型,并利用层次分析方法求解各级相似元的权重系数。通过模拟实验和真实数据实验对本文方法的可靠性和有效性进行验证,结果表明:本文提出的等高线群混合相似性度量模型能够定量描述不同尺度不同来源等高线群之间的相似与差异程度,并具有较好的有效性和可靠性;根据本文的混合相似性度量结果和更新阈值之间的关系,对满足更新要求的变化区域实施局部更新,且精度检验表明论文方法能够为等高线数据的更新应用提供可靠依据。
Contour line is used to express surface information through curve cluster. The degree of topography change can be reflected based on the similarity between multi-source contour data. Therefore, the similarity measurement of contour groups is an essential step in the map partial renewal, multi-source data merging and cartographic generalization of topographic maps. Previous measurement methods are mainly based on measuring the single topological feature or geometric feature. Due to the complexity of geospatial data and the diversity of geographic elements, the existing methods may not completely reflect the similarities and differences between multi-source data, which may cause inconsistencies in areas with intensive contours or extreme terrain changes and map boundaries in incremental renewal application. For this reason, the spatial similarity theory is introduced and the similarity structure of contour group is built. Through analyzing the relationship and mechanism of the topological relations and geometric features, the hierarchical structure of contour group similarity is constructed, and the mutual relationship and similarity measurement methods of each influencing factor are discussed. Based on the hierarchical structure, a mixed similarity measure model using topological relation tree and geometric similarity measures is proposed. In the mixed measure model, the weight coefficients are calculated based on the analytic hierarchy process. Simulated and real datasets experiments are used to verify the reliability and validity of the similarity measure model proposed in this paper. The experimental results show that:(1) The mixed similarity measure model can quantitatively describe the similarities and differences between contour data from different scales and sources.(2) According to the relationship between the mixed similarity measure results and the update thresholds, partial renewing is applied to the changing areas that meet the update requirements. The accuracy test shows that the proposed similarity measure method has a good validity and reliability.
Contour line is used to express surface information through curve cluster. The degree of topography change can be reflected based on the similarity between multi-source contour data. Therefore, the similarity measurement of contour groups is an essential step in the map partial renewal, multi-source data merging and cartographic generalization of topographic maps. Previous measurement methods are mainly based on measuring the single topological feature or geometric feature. Due to the complexity of geospatial data and the diversity of geographic elements, the existing methods may not completely reflect the similarities and differences between multi-source data, which may cause inconsistencies in areas with intensive contours or extreme terrain changes and map boundaries in incremental renewal application. For this reason, the spatial similarity theory is introduced and the similarity structure of contour group is built. Through analyzing the relationship and mechanism of the topological relations and geometric features, the hierarchical structure of contour group similarity is constructed, and the mutual relationship and similarity measurement methods of each influencing factor are discussed. Based on the hierarchical structure, a mixed similarity measure model using topological relation tree and geometric similarity measures is proposed. In the mixed measure model, the weight coefficients are calculated based on the analytic hierarchy process. Simulated and real datasets experiments are used to verify the reliability and validity of the similarity measure model proposed in this paper. The experimental results show that:(1) The mixed similarity measure model can quantitatively describe the similarities and differences between contour data from different scales and sources.(2) According to the relationship between the mixed similarity measure results and the update thresholds, partial renewing is applied to the changing areas that meet the update requirements. The accuracy test shows that the proposed similarity measure method has a good validity and reliability.
引文
[1]刘朋飞.基于矢量数据的中低分辨率影像道路提取和变化检测研究[D].武汉:武汉大学,2010.[Liu P F.Research on road extraction and change detection from medium or low resolution images with vector data[D].Wuhan:Wuhan University,2010.]
[2]王丽云,李艳,汪禹芹.基于对象变化矢量分析的土地利用变化检测方法研究[J].地球信息科学学报,2014,16(2):307-313.[Wang L Y,Li Y,Wang Y Q.Research on land use change detection based on an object-oriented change vector analysis method[J].Journal of Geo-information Science,2014,16(2):307-313.]
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[6]段修梅.基于1:1万地形数据更新1:5万DEM的方法研究[D].长沙:中南大学,2012.[Duan X M.Updating method of 1:50 000 scale DEM based on 1:10000 scale terrain data[D].Changsha:Central South University,2012.]
[7]周晓光,汪红松,吴志强.引入二维交细分类型的地表覆盖矢量数据增量更新[J].测绘学报,2017,46(1):114-122.[Zhou X G,Wang H S,Wu Z Q.An incremental updating method for land cover database using refined 2-dimensional intersection type[J].Acta Geodaetica et Cartographica Sinica,2017,46(1):114-122.]
[8]邢汉发,周晓光,许礼林.基于线/线拓扑关系的局部变化等高线融合[J].武汉大学学报·信息科学版,2010,35(11):1322-1326.[Xing H F,Zhou X G,Xu L L.Local contour line fusion based on line/line topological relations[J].Geomatics&Information Science of Wuhan University,2010,35(11):1322-1326.]
[9]Alt H,Godau M.Computing the Fréchet distance between two polygonal curves[J].International Journal of Computational Geometry&Applications,1995,5(01n02):75-91.
[10]刘鹏程,艾廷华,杨敏.基于傅里叶级数的等高线网络渐进式传输模型[J].测绘学报,2012,41(2):284-290.[Liu PC,Ai T H,Yang M.The internet progressive transmission model for contour based on Fourier series[J].Acta Geodaetica et Cartographica Sinica,2012,41(2):284-290.]
[11]唐炉亮,杨必胜,徐开明.基于线状图形相似性的道路数据变化检测[J].武汉大学学报·信息科学版,2008,33(4):367-370.[Tang L L,Yang B S,Xu K M.The road data change detection based on linear shape similarity[J].Geomatics&Information Science of Wuhan University,2008,33(4):367-370.]
[12]刘涛,杜清运,闫浩文.空间点群目标相似度计算[J].武汉大学学报·信息科学版,2011,36(10):1149-1153.[Liu T,Du Q Y,Yan H W.Spatial similarity assessment of point clusters[J].Geomatics&Information Science of Wuhan University,2011,36(10):1149-1153.]
[13]闫浩文,褚衍东.多尺度地图空间相似关系基本问题研究[J].地理与地理信息科学,2009,25(4):42-44.[Yan H W,Chu Y D.On the fundamental issues of spatial similarity relations in multi-scale maps[J].2009,25(4):42-44.]
[14]刘涛,杜清运,毛海辰.空间线群目标相似度计算模型研究[J].武汉大学学报·信息科学版,2012,37(8):992-995.[Liu T,Du Q Y,Mao H C.Spatial similarity assessment model and its application in line groups[J].Geomatics&Information Science of Wuhan University,2012,37(8):992-995.]
[15]安晓亚.空间数据几何相似性度量理论方法与应用研究[D].郑州:信息工程大学,2011.[An X Y.Research on theory,methods and applications of geometry Similarity Measurement for Spatial Data[D].Zhengzhou:Information Engineering University,2011.]
[16]宋敦江,岳天祥,杜正平,等.高线树构建及高保真DEM构建[J].中国图象图形学报,2011,16(7):1255-1261.[Song D J,Yue T X,Du Z P.Constructing contour tree and DEM construction of high fidelity[J].Journal of Image and Graphics,2011,16(7):1255-1261.]
[17]Cronin T.Automated reasoning with contour maps[J].Computers and Geosciences,1995,21(5):609-618.
[18]Cronin T.Classifying hills and valleys in digitized terrain[J].Photogrammetric Engineering&Remote Sensing,2000,66(9):1129-1137.
[19]夏慧琼,李德仁,郑春燕.基于相似度理论的时空变化定量描述方法[J].地理与地理信息科学,2010,26(3):1-5.[Xia HQ,Li D R,Zheng C Y.A method of qualitative change about spatio-temporal object based on similarity theory[J].Geography and Geo-information Science,2010,26(3):1-5.]
[20]孙群.空间数据相似性研究的若干基本问题[J].测绘科学技术学报,2013,30(5):439-442.[Sun Q.Research on some fundamental issues of spatial data similarity[J].Journal of Geomatics Science and Technology,2013,30(5):439-442.]
[21]韩敏,郑丹晨.基于模糊形态上下文特征的形态识别算法[J].自动化学报,2012,38(1):68-75.[Han M,Zheng D C.Shape recognition based on fuzzy shape context[J].Acta Automatica Sinica,2012,38(1):68-75.]
[22]Mokhtarian F,Abbasi S,Kittler J.Efficient and robust retrieval by shape content through curvature scale space[M]//Image Databases and Multi-Media Search,1997:51-58.
[23]Adamek T,O'Connor N E.A multiscale representation method for nonrigid shapes with a single closed contour[J].IEEE Transactions on Circuits and Systems for Video Technology,2004,14(5):742-753.
[24]Donoser M,Riemenschneider H,Bischof H.Efficient partial shape matching of outer contours[C]//Asian Conference on Computer Vision.Springer-Verlag,2009:281-292.
[25]Vlachos M,Kollios G,Gunopulos D.Discovering similar multidimensional trajectories[C]//Data Engineering,2002.Proceedings.18th International Conference on.IEEE,2002:673-684.
[26]Bruns T,Egenhofer M.Similarity of spatial scenes[C]//Seventh international symposium on spatial data handling.Delft,The Netherlands,1996:31-42.
[27]龚健雅,李小龙,吴华意.实时GIS时空数据模型[J].测绘学报,2014,43(3):226-232.[Gong J Y,Li X L,Wu H Y.Spatiotemporal data model for real-time GIS[J].Acta Geodaetica et Cartographica Sinica,2014,43(3):226-232.]
[28]段晓旗,刘涛,武丹.基于层次分析法的多尺度点群目标相似度计算[J].地球信息科学学报,2016,18(10):1312-1321.[Duan X Q,Liu T,Wu D.Spatial similarity assessment of point clusters in multi-scale map spaces based on analytic hierarchy process[J].Journal of Geo-information Science,2016,18(10):1312-1321.]
[29]张尧,樊红,黄旺.基于Delaunay三角网的等高线树生成方法[J].测绘学报,2012,41(3):461-467.[Zhang Y,Fan H,Huang W.The method of generating contour tree based on contour Delaunay triangulation[J].Acta Geodaetica et Cartographica Sinica,2012,41(3):461-467.]
[2]王丽云,李艳,汪禹芹.基于对象变化矢量分析的土地利用变化检测方法研究[J].地球信息科学学报,2014,16(2):307-313.[Wang L Y,Li Y,Wang Y Q.Research on land use change detection based on an object-oriented change vector analysis method[J].Journal of Geo-information Science,2014,16(2):307-313.]
[3]Radke R J,Andra S,Al-Kofahi O,et al.Image change detection algorithms:A systematic survey[J].IEEE transactions on image processing,2005,14(3):294-307.
[4]李德仁,夏松,江万寿,等.一种地形变化检测与DEM更新的方法研究[J].武汉大学学报·信息科学版,2006,31(7):565-568.[Li D R,Xia S,Jiang W T,et al.Approach for terrain change detection and DEM updating[J].Geomatics&Information Science of Wuhan University,2006,31(7):565-568.]
[5]李德仁,夏松,江万寿.基于正射影像匹配的地形变化检测与更新算法[J].地理与地理信息科学,2006,22(6):9-11.[Li D R,Xia S,Jiang W T.Approach for terrain change detection and updating based on orthoimage matching[J].Geography and Geo-information Science,2006,22(6):9-11.]
[6]段修梅.基于1:1万地形数据更新1:5万DEM的方法研究[D].长沙:中南大学,2012.[Duan X M.Updating method of 1:50 000 scale DEM based on 1:10000 scale terrain data[D].Changsha:Central South University,2012.]
[7]周晓光,汪红松,吴志强.引入二维交细分类型的地表覆盖矢量数据增量更新[J].测绘学报,2017,46(1):114-122.[Zhou X G,Wang H S,Wu Z Q.An incremental updating method for land cover database using refined 2-dimensional intersection type[J].Acta Geodaetica et Cartographica Sinica,2017,46(1):114-122.]
[8]邢汉发,周晓光,许礼林.基于线/线拓扑关系的局部变化等高线融合[J].武汉大学学报·信息科学版,2010,35(11):1322-1326.[Xing H F,Zhou X G,Xu L L.Local contour line fusion based on line/line topological relations[J].Geomatics&Information Science of Wuhan University,2010,35(11):1322-1326.]
[9]Alt H,Godau M.Computing the Fréchet distance between two polygonal curves[J].International Journal of Computational Geometry&Applications,1995,5(01n02):75-91.
[10]刘鹏程,艾廷华,杨敏.基于傅里叶级数的等高线网络渐进式传输模型[J].测绘学报,2012,41(2):284-290.[Liu PC,Ai T H,Yang M.The internet progressive transmission model for contour based on Fourier series[J].Acta Geodaetica et Cartographica Sinica,2012,41(2):284-290.]
[11]唐炉亮,杨必胜,徐开明.基于线状图形相似性的道路数据变化检测[J].武汉大学学报·信息科学版,2008,33(4):367-370.[Tang L L,Yang B S,Xu K M.The road data change detection based on linear shape similarity[J].Geomatics&Information Science of Wuhan University,2008,33(4):367-370.]
[12]刘涛,杜清运,闫浩文.空间点群目标相似度计算[J].武汉大学学报·信息科学版,2011,36(10):1149-1153.[Liu T,Du Q Y,Yan H W.Spatial similarity assessment of point clusters[J].Geomatics&Information Science of Wuhan University,2011,36(10):1149-1153.]
[13]闫浩文,褚衍东.多尺度地图空间相似关系基本问题研究[J].地理与地理信息科学,2009,25(4):42-44.[Yan H W,Chu Y D.On the fundamental issues of spatial similarity relations in multi-scale maps[J].2009,25(4):42-44.]
[14]刘涛,杜清运,毛海辰.空间线群目标相似度计算模型研究[J].武汉大学学报·信息科学版,2012,37(8):992-995.[Liu T,Du Q Y,Mao H C.Spatial similarity assessment model and its application in line groups[J].Geomatics&Information Science of Wuhan University,2012,37(8):992-995.]
[15]安晓亚.空间数据几何相似性度量理论方法与应用研究[D].郑州:信息工程大学,2011.[An X Y.Research on theory,methods and applications of geometry Similarity Measurement for Spatial Data[D].Zhengzhou:Information Engineering University,2011.]
[16]宋敦江,岳天祥,杜正平,等.高线树构建及高保真DEM构建[J].中国图象图形学报,2011,16(7):1255-1261.[Song D J,Yue T X,Du Z P.Constructing contour tree and DEM construction of high fidelity[J].Journal of Image and Graphics,2011,16(7):1255-1261.]
[17]Cronin T.Automated reasoning with contour maps[J].Computers and Geosciences,1995,21(5):609-618.
[18]Cronin T.Classifying hills and valleys in digitized terrain[J].Photogrammetric Engineering&Remote Sensing,2000,66(9):1129-1137.
[19]夏慧琼,李德仁,郑春燕.基于相似度理论的时空变化定量描述方法[J].地理与地理信息科学,2010,26(3):1-5.[Xia HQ,Li D R,Zheng C Y.A method of qualitative change about spatio-temporal object based on similarity theory[J].Geography and Geo-information Science,2010,26(3):1-5.]
[20]孙群.空间数据相似性研究的若干基本问题[J].测绘科学技术学报,2013,30(5):439-442.[Sun Q.Research on some fundamental issues of spatial data similarity[J].Journal of Geomatics Science and Technology,2013,30(5):439-442.]
[21]韩敏,郑丹晨.基于模糊形态上下文特征的形态识别算法[J].自动化学报,2012,38(1):68-75.[Han M,Zheng D C.Shape recognition based on fuzzy shape context[J].Acta Automatica Sinica,2012,38(1):68-75.]
[22]Mokhtarian F,Abbasi S,Kittler J.Efficient and robust retrieval by shape content through curvature scale space[M]//Image Databases and Multi-Media Search,1997:51-58.
[23]Adamek T,O'Connor N E.A multiscale representation method for nonrigid shapes with a single closed contour[J].IEEE Transactions on Circuits and Systems for Video Technology,2004,14(5):742-753.
[24]Donoser M,Riemenschneider H,Bischof H.Efficient partial shape matching of outer contours[C]//Asian Conference on Computer Vision.Springer-Verlag,2009:281-292.
[25]Vlachos M,Kollios G,Gunopulos D.Discovering similar multidimensional trajectories[C]//Data Engineering,2002.Proceedings.18th International Conference on.IEEE,2002:673-684.
[26]Bruns T,Egenhofer M.Similarity of spatial scenes[C]//Seventh international symposium on spatial data handling.Delft,The Netherlands,1996:31-42.
[27]龚健雅,李小龙,吴华意.实时GIS时空数据模型[J].测绘学报,2014,43(3):226-232.[Gong J Y,Li X L,Wu H Y.Spatiotemporal data model for real-time GIS[J].Acta Geodaetica et Cartographica Sinica,2014,43(3):226-232.]
[28]段晓旗,刘涛,武丹.基于层次分析法的多尺度点群目标相似度计算[J].地球信息科学学报,2016,18(10):1312-1321.[Duan X Q,Liu T,Wu D.Spatial similarity assessment of point clusters in multi-scale map spaces based on analytic hierarchy process[J].Journal of Geo-information Science,2016,18(10):1312-1321.]
[29]张尧,樊红,黄旺.基于Delaunay三角网的等高线树生成方法[J].测绘学报,2012,41(3):461-467.[Zhang Y,Fan H,Huang W.The method of generating contour tree based on contour Delaunay triangulation[J].Acta Geodaetica et Cartographica Sinica,2012,41(3):461-467.]