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同源多尺度海图生产体系设计及其关键技术研究
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摘要
数字化解决了数据从无到有的问题,而信息化则需要进一步实现数据的融合共享,以达到数据的一致性、实时性、高效性。我国的海图生产虽然已经实现了数字化,但是相比于发达国家的海图生产水平而言,存在着产品数据不一致、更新周期相对较慢和生产效率难以较大提高等问题。针对这些问题,本文提出了一个新的海图生产体系,并对其关键技术进行了研究。论文主要工作和取得的成果有:
     1.对现代海图生产过程中涉及到的“海图生产体系”、“海图数据模型”、“自动综合算法”和“空间数据匹配”等四个关键问题的国内外研究现状进行了评述和分析。
     2.提出了同源多尺度海图生产体系的概念、框架结构,分析了其主要生产工序和关键技术。该生产体系通过多源海图数据的融合,保证源数据的唯一性、现势性和产品数据的同宗同源;同时允许产品数据之间存在派生关系,避免了因源数据和产品数据的比例尺跨度过大导致数据生产的困难;引入了“空间几何实例共享池”,实现不同产品数据之间空间几何数据的共享,保证了产品数据之间的一致性。
     3.针对实体模型存在数据冗余、容易导致数据不一致,而拓扑模型则过于复杂以及存在关系冗余的问题,本文提出了一个无缝无级空间数据融合模型,不仅能够实现多源空间数据的融合,而且避免了传统空间数据模型中的数据冗余和不一致等问题;结合S-100和S-57两个海图数据国际标准,给出了海图要素模型和海图属性模型,提出了“最小拓扑”空间模式;同时,依据海图源数据融合模型,提出了一套海图源数据库设计与实现的方案:通过海图概念字典和要素目录实现海图数据语义的统一,通过要素集合和空间集合的解耦合实现了海图源数据库的无缝无级表达。
     4.针对外部数据与海图源数据不一致的问题,本文提出了一种基于XML,由代词、名词、形容词、条件语句、操作语句等语法结构构成的转换语言,实现了要素和属性的自动转换,并通过拓扑重构技术实现了空间模式的自动转换,进而实现了DNC和CDC数据等外部数据向海图源数据的转换;研究了新数据与源数据库中要素的自动匹配方法,给出了一种“基于误差理论的改进型Hausdorff距离”;最后分析总结了不同海图源数据之间的质量评价因子和质量评价规则知识。
     5.针对从源数据库中派生产品数据的情况,本文重点研究了海图水深的自动综合方法。通过对现有水深点群综合方法的分析,发现传统方法将水深点群视为平面点集、过分强调空间分布特征,导致水深自动综合难以实用化;针对现有水深点群自动综合方法的不足,提出了“将水深点群视为空面点集、以海底地形特征识别为基础进行背景水深自动综合”的新思路;通过建立Delaunay三角网和局部动态更新技术,以“离散曲率最小”、“平均间距约束”、“深度变化约束”及其组合方式为约束条件,实现了基于TIN空间曲面的水深点群渐进式自动综合。
     6.针对海图源数据库出现更新时,需要将变化信息传递至产品数据的情况,本文重点分析了产品数据中曲线的更新方法。利用曲线约束Delaunay三角网建立CDT-Btree,并通过伪弯曲剔除、重采样等优化以及并列弯曲识别和调整等方法,构造了一种与视觉感受相一致的曲线弯曲特征CDT-Mtree;以CDT-Mtree为基础,通过多级弯曲匹配,实现了源曲线和产品曲线的弯曲匹配和变化识别,进而实现了产品曲线中变化弯曲的增量更新。
     7.给出了一个同源多尺度海图生产的实验。以DNC和CDC实验数据为基础构建了海图源数据库原型;对ENC产品规范中关于数据内容的规定进行了总结;以ENC为例,给出了从海图源数据库中生产ENC新数据和更新数据的基本示例,初步验证了同源多尺度生产的可行性。
Digitalization means converting paper data into digital data, while informatization aims tointegrate data based on digitalization, to ensure consistency, updating in time and highefficiency of the data. China charts production has been realized digitalization, howevercompared with developed countries, some technologies are still lagging behind, such as lowefficiency, not timely data update as well as data inconsistency in different products. In order tosolve these problems, a solution is proposed in this dissertation, as well as its key problems.The main works are as following:
     1. Four issues related to modern chart production-"chart product architecture","chartdata model","auto generalization algorithm","matching algorithm of spatial data" aresummarized and analyzed in the front of this dissertation.
     2."One Source, Multi Representation" Chart Production System is proposed, including itsconcept, theory architecture, main process and key technique.By multi-source chart data fusion,this production system can ensure all the source data be unique, update in real-time, all theproduct data be consistent; it allows product data derivating from another product data, whichavoid difficulty from producing product data from source data of larger scale;"Geometry SharePool" realizes geometry share among different product data, which ensure all the product databe consistent.
     3."Entity Model" is redundant in geometry and has problem of topological inconsistency,and "Topology Model" is redundant in topological relation and its realization and operation isvery difficult. So, an seamless, scaleless, not layered, and irredundant geospatial data model-"Seamless, Scaleless Source Data Fusion Model" is promoted in this dissertation, which can notonly integrate various chart data,but also avoid data redundancy or relation redundancy intraditional data models. Considering the international chart standard of S-57and S-100, afeature data model and attribute data model of chart is given, and a spatial data model withminimized topology is brought out too. According to "Seamless, Scaleless Source Data FusionModel", a schema of chart source database is put forward: chart data semantic is unified byestablishing chart concept collection and features catalogue, seamless and scaleless chart sourcedata is constructed by decoupling feature collection and spatial geometry collection.
     4. After analyzing the transfer relationships of different chart data, the dissertation putsforward a XML-based transfer language, which is consisted of pronoun, noun, adjective,condition sentence, operation sentence and other syntax structures, feature and attribute can betransferred automaticlly by this language; by topology reconstruction, spatial schema can be transferred automatically. With the XML-based transfer language and topology reconstruction,transforming from CDC, DNC and other exterior data to chart source data can be the realized.Automatic feature matching method between new data and data in source database is alsoresearched, and a new line feature matching method based on "improved Hausdorff distancebased on error theory" is put forward in this dissertation. At last, chart data quality evaluationcriteria are given.
     5. In order to produce product data from source database, chart soundings' selectionmethod is researched in this dissertation. By analyzing existing research on soundings' selection,we can draw a conclusion that the traditional soundings' selection method taking soundings asplane points and lay stress on spatial distribution characteristics, which causes soundings' autoselection difficult to practical; and space points' selection, and then an idea of how to selectsoundings is put forward. In view of existing shortcomings of soundings' auto selectionmethods, an idea of select background soundings in space points, in order to preserve seabedcharacteristic, is advanced, then based on Delaunay triangle net and local dynamic update, aprogressive method of soundings' auto selection base on TIN surface is put forward, thenseveral experiments with "minimum curvature limit","average spacing limit","depth valuechange limit", and all these limit combined are carried out and compared, from which we candraw a conclusion that sounding selection in combined limit has better effect.
     6. In order to update product data once source database changes, a method to update curvein product is researched. Based on construction of Constraint Delaunay Triangle Net, Bend-Binary-Tree of curve can be built, that is called CDT-Btree. Optimization of CDT-Btree can becarried out by resembling, branch node adjustment, then a Multi-way Tree, called CDT-Mtree,can be built after neighbor bends recognized, which represents the curve bend characteristiccompatible with visual perception. Based on CDT-Mtree method, an incremental updating andincremental generalization method is proposed with the basic element of curve bend. With themulti-level curve bend matched, the change between source curve and product curve bend ismatched and recognized.
     7. An experience conforming to "One Source, Multi Representation" Chart Production iscarried out. A basic chart source database is built from DNC and CDC experiment data; themain regulation on data content of ENC product specification is introduced; then twoexperiment about chart production and update from source database is introduced taking ENCas an example, which proved the feasibility of "One Source, Multi Representation" chartproduction.
引文
[1]翟京生.多波束测量技术与海洋测绘工序的调整[J].武汉大学学报·信息科学版,2007,32(11):994-997.
    [2] US DEPARTMENT OF DEFENSE. DEPARTMENT OF DEFENSE INTERFACE STANDARD FORVECTOR PRODUCT FORMAT[S].1996.
    [3] http://www.ukho.gov.uk/pages/Home.aspx[OL].2011.
    [4]韩范畴,李春菊,贾建军.海洋测绘数据库支撑下的航海图书生产与保障[J].测绘科学技术学报,2010,27(3):213-216.
    [5] M. Hampe&M. Sester. Generating and Using A Multi-Representation Database (MRDB) for MobileApplications. ICA Workshop on Generalization and Multiple Representation[C].20-21August2004–Leicester.
    [6]刘海砚.地图制图与空间数据生产一体化理论和技术的研究[D].郑州:中国人民解放军信息工程大学,2002.
    [7]李霖,吴凡.空间数据多尺度表达模型及其可视化[M].北京:科学出版社,2005.
    [8]刘国辉.海图产品一体化更新服务模式研究[D].郑州:中国人民解放军信息工程大学,2010.
    [9] CARIS. Getting Started with CARIS Hydrographic Production Database [M].2007: VII.
    [10] Dauidssan, F. The Solution for Production of Hydrographic Information[C]. Proceeding of theInternational Cartographic Conference,2003, South Africa. http://www.ign.fr[OL].2011.
    [11] NIMA.MIL-PRF-89023: PERFORMANCE SPECIFICA-TION:DIGITAL NAUTICAL CHART
    [S].1997.
    [12] International Hydrographic Organization. IHO Transfer Standard for Digital Hydrographic Data Edition3.1[M]. Monaco: International Hydrographic Bureau,2000.
    [13] International Hydrographic Organization. S-100-Universal Hydrographic Data Model Edition1.0.0[M].Monaco: International Hydrographic Bureau,2010.
    [14]翟京生,元建胜,陈长林,陆毅. S-100通用海洋测绘数据模型[M].中国航海图书出版社,2010.
    [15]陈长林,翟京生,陆毅.海洋测绘国际标准S-100的空间模式研究[J].测绘科学技术学报,2012,29(1):61-65.
    [16]陈长林,翟京生,陆毅.IHO海洋测绘地理空间数据新标准分析与思考[J].测绘科学技术学报,2011,28(4):300-303.
    [17] Shea K S,McMaster R B.Cartographic Generalization in a Digital Environment:When and How toGeneralize[C]. In: Proceedings of Autocarto6,1995.56-89.
    [18]郭庆胜.地图自动综合问题的分解和基本算子集合[J].武汉测绘科技大学学报,1999,24(2):149-153.
    [19]武芳,钱海忠.自动综合算子分析及算法库的建立[J].解放军测绘学院学报,2002,19(1):50-52.
    [20] Douglas D, Peucker T, Algorithms for the Reduction of the Number of Points Required to Represent aDigitized Line or its Caricature[J].Canadian Cartographer,1973,10(2):112-122.
    [21] Peter van Oosterom, Jan vanden Bos. An Object-oriented Approach to the Design of GeographicInformation Systems[M]. In: Buchman A P, Günther O,Smith T R,et al. eds. Design and Implementationof Large Spatial Databases. Berlin: Springer Verlag,1989:255-269.
    [22]毋河海.基于多叉树结构的曲线综合算法[J].武汉大学学报·信息科学版,2004,29(6):479-483.
    [23] Saalfeld, A.(1999). Topologically consistent line simplification with the Douglas-Peucker algorithm[J].Cartography and Geographic Information Science,26(1):7–18.
    [24] Da Silva Adler. C. G. and Wu S. T.(2006) A Robust Strategy for Handling Linear Features inTopologically Consistent Polyline Simplification[C]. In AMV Monteiro and CA Davis, editors,GeoInfo,VIII Brazilian Symposium on Geoinformatics,19-22November, Campos doJordao, Sao Paulo, Brazil,pages19–34.
    [25] Wu, S.-T. and Márquez, M. R. G.(2003). A non-self-intersection Douglas-Peucker algorithm[C]. In The16th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI), pages60–66.IEEE Press.
    [26]张传明.保持拓扑一致性的等高线化简算法研究[J].北京大学学报(自然科学版),2007,43(2):216-222.
    [27]王净,江刚武.无拓扑矢量数据快速压缩算法的研究与实现[J].测绘学报,2003,32(2):173-177.
    [28]翟战强.一种快速空间矢量数据压缩方法[J].计算机工程,2003,29(2):94-95.
    [29]陈轶,彭认灿,郑义东,等.基于Douglas双侧多叉树的曲线综合算法研究[J].测绘学报,2010,39(3):310-315.
    [30] Butterfield B P. Object-oriented map generalization: modeling and cartographic considerations[M]. In:J-C Müller, J-P Lagrange, and R Weibel (eds) GIS and Generalization: Methodology and Practice.London, UK: Taylor&Francis.
    [31]田鹏,郑扣根,潘云鹤,等.基于Strip-Tree的无级比例尺GIS多边形化简技术[J].软件学报,2001,12(10):1495-1503.
    [32] Oliver Günther. Efficient Structures for Geometric Data Management[C]. Number337in Lecture Notesin Computer Science. Springer-Verlag, Berlin,1988.
    [33]翟京生,陆毅.数字海图线性特征的识别、量测与综合[J].测绘学报,2000,29(3):273-279.
    [34] Jones, C., Bundy, G. and Ware, J., Map Generalisation with a Triangulated Data Structure[J].Cartography and Geographical Information Systems,1995,22(4):313-317.
    [35] Van der Poorten, P. M, and Jones, C. B., August1999, Customisable Line Generalisation using DelaunayTriangulation[C]. In Proceedings of the19th ICA Conference (Ottawa: International CartographicCongress), section8, CD Rom.
    [36] P. M. van der Poorten, Sheng Zhou and Christopher B. Jones. Topologically-Consistent MapGeneralisation Procedures and Multi-Scale Spatial Databases[J]. Geographic InformationSCIENCE,2002,Vol16,No8.773-794.
    [37] Van der Poorten,P. and Jones, C.(2002). Characterisation and Generalisation of Cartographic LinesUsing Delaunay Triangle[J]. International Journal of Geographical Information Science,Vol.16, NO.8,773-794.
    [38] Ai, T., Guo, R, Zhong, G., and Yaolin, L.,2000, A Binary Tree Representation of Curve HierarchicalStructure Based on Gestalt Principles[C]. In Proceedings of9th International Symposium on SpatialData Handling (Beijing: International Geographical Union), section2a, pp.30–43.
    [39]艾廷华,郭仁忠,刘耀林.曲线弯曲深度层次结构的二叉树表达[J].测绘学报,2001,30(4):343-348.
    [40]翟仁健,武芳,朱丽,等.曲线形态的结构化表达[J].测绘学报,2009,38(2):175-182.
    [41]翟仁健,武芳,朱丽,等.利用地理特征约束进行曲线化简[J].武汉大学学报·信息科学版,2009,34(9):1021-1024.
    [42]艾廷华,郭仁忠.支持地图综合的面状目标约束Delaunay三角网剖分[J].武汉测绘科技大学学报,2000,25(1):35-41.
    [43]艾廷华,郭仁忠,陈晓东,等.Delaunay三角网支持下的多边形化简与合并[J].中国图像图形学报,2001,(7):701-709.
    [44]艾廷华,刘耀林.土地利用数据综合中的聚合与融合[J].武汉大学学报·信息科学版,2002,27(5):487-489.
    [45]艾廷华,祝国瑞,张根寿,等.基于Delaunay三角网模型的等高线地形特征提取及谷地树结构化组织[J].遥感学报,2003,7(4):291-294.
    [46]艾廷华.Delaunay三角网支持下的空间场表达[J].测绘学报,2006,35(1):71-76.
    [47]艾廷华,郭仁忠.基于格式塔识别原则挖掘空间分布模式[J].测绘学报,2007,36(3):302-308.
    [48]刘颖,翟京生,陆毅,等.数字海图水深注记的自动综合研究[J].测绘学报,2005,34(2):179-184.
    [49]闫浩文,王家耀.基于Voronoi图的点群目标普适综合算法[J].中国图象图形学报:A辑,2005,10(5),633-636.
    [50] Haowen Yan, Robert Weibel. An algorithm for point cluster generalization based on the Voronoidiagram[J]. Computers&Geosciences,Volume34, Issue8, August2008, Pages939–954.
    [51]闫浩文,王家耀.地图群(组)目标描述与自动综合[M].北京:科学出版社,2009.
    [52]武芳.空间数据的多尺度表达与自动综合[M].北京:解放军出版社,2003.
    [53]钱海忠,武芳,张琳琳,等.基于极化变换的点群综合几何质量评估[J].测绘学报,2005,34(4):361-369.
    [54]钱海忠,武芳,邓红艳,等.基于CIRCLE特征变换的点群选取算法[J].测绘科学,2005,30(3).:83-86
    [55]钱海忠,武芳,谢鹏,等.基于CIRCLE特征变换的点群选取改进算法.测绘科学,2006,31(5).69-71.
    [56] Müller, J. C..1987. Fractal and Automated Line Generalisation[J]. The Cartographic Journal., v.24, no.1,p.27-34.
    [57]王桥.分形理论在地图图形数据自动处理中的若干扩展与应用研究[D].武汉测绘科技大学,1996.
    [58]王桥,毋河海.地图信息的分形描述与自动综合研究[M].武汉:武汉测绘科技大学出版社,1998.
    [59]毋河海.地图信息的分形描述[J].测绘通报,2001(2):24-26.
    [60]吴凡.地理空间数据的多尺度处理与表示的研究[D].武汉:武汉大学,2002.
    [61]朱长青,王玉海,李清泉,等.基于小波分析的等高线数据压缩模型[J].中国图象图形学报,2004,9(7):841-845.
    [62] Su B.Li Z, Lodwick G et al. Algebraic models for the aggregation of area features based uponmorphological operators [J]. Int.J. Geographical Information Science,1997,11(3):233-246.
    [63]张青年,秦建新.面状分布地物群识别与概括的数学形态学方法[J].地理研究,2000,19(1):93-100.
    [64]王辉连,武芳,张琳琳,等.数学形态学和模式识别在建筑物多边形化简中的应用[J].测绘学报,2005,34(3):269-276.
    [65]田震.基于神经元网络的自动综合研究[D].郑州:解放军测绘学院,2000.
    [66]王家耀,田震.海图水深综合的人工神经元网络方法[J].测绘学报,1999,28(4):335-339.
    [67] Steven van Dijk, Dirk Thierens, Mark de Berg. Robust genetic algorithms for high quality maplabeling[D]. Technical Report TR-1998-41, Utrecht University1998.
    [68]樊红,刘开军,张祖勋,等.基于遗传算法的点状要素注记的整体最优配置[J].武汉大学学报·信息科学版.2002,27(6):560-561.
    [69]邓红艳,武芳,钱海忠,等.基于遗传算法的点群目标选取模型[J].中国图象图形学报,2003,8(A)(8):970-976.
    [70]邓红艳,武芳,翟仁健,等.基于遗传算法的道路网综合模型[J].武汉大学学报·信息科学版.2006,31(2):164-167.
    [71]王家耀,邓红艳.基于遗传算法的制图综合模型研究[J].测绘学报,2005,30(7):565-569.
    [72]翟仁健.基于遗传多目标优化的人工河网自动选取模型[D].郑州:中国人民解放军信息工程大学,2006.
    [73]武芳,邓红艳.基于遗传算法的线状要素自动化简模型[J].测绘学报,2003.32(4):349-355.
    [74] Lang, T.(1969). Rules for robot draughtsmen[J]. Geographical Magazine,22:50–51.
    [75] Reumann, K. and Witkam, A. P. M.(1974). Optimizing curve segmentation in computer graphics[C]. InProceedings of the International Computing Symposium, pages467–472.
    [76] Li, Z., Openshaw, S.(1992). Algorithms for Automated Line Generalization Based on a NaturalPrinciple of Objective Generalization[J]. International Journal of Geographical Information Systems,6(5),373-389.
    [77] Visvalingam, M. and Whyatt, J. D.(1993). Line Generalisation by Repeated Elimination of Points[J].Cartographic Journal,30(1):46–51.
    [78] de Berg, M., van Kreveld, M., and Schirra, S.(1998). Topologically correct subdivision simplificationusing the bandwidth criterion[J]. Cartography and Geographic Information Systems,25(4):243–257.
    [79]应申,李霖.基于约束点的曲线一致性化简[J].武汉大学学报·信息科学版,2003,28(4):488-491.
    [80] Dutton G. Scale, Sinuosity and Point Selection in Digital Line Generalization [J]. Cartography andGeographic Information Systems,1999,26(1):33-53
    [81]杨云,孙群,朱长青,等.曲线数据压缩的总体最小二乘算法[J].西安电子科技大学学报(自然科学版),2008,35(5):946-949.
    [82] Walter, V.&Fritsch, D.,1999: Matching spatial datasets: a statistical approach [J]. International Journalof Geographical Information Science13(5), pp.445-473.
    [83] Saalfeld A. Automated Map Conflation [D]. Washington: University of Maryland,1993.
    [84] Mantel&Lipeck,2004, Mantel, D.&Lipeck, U. W.,2004: Matching Cartographic Objects in SpatialDatabases[J]. Int.Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.35, Part B4, pp.172-176, ISPRS, Istanbul,2004.
    [85] Shi W.&Meng, L.(2006): Some ideas for integrating multidisciplinary spatial data[J]. InternationalArchives of Photogrammetry, Remote Sensing and Spatial Information Sciences36(Part2/W40), p.30-35.
    [86] Hild, H., Automatische Georeferenzierung von Fernerkundungsdaten[J]. Deutsche Geod tischeKommission, Reihe C, Nr.562, München2003.
    [87] Rosin, P., Techniques for Assessing Polygonal Approximations to Curves[C]. IEEE Trans. PAMI,19(6),pp.659-666,1997.
    [88] SAMAL A, SETH S, CUETO K. A Feature-based Approach to Conflation of Geospatial Sources [J].International Journal of Geographical Information Science,2004.
    [89] Olteanu A-M.Matching geographical data using the Theory of Evidence[C]. Proceedings of20th ICC,5-9August2007, Moscow, Russie.
    [90] Patrick Revell and Beno t Antoine. AUTOMATED MATCHING OF BUILDING FEATURES OFDIFFERING LEVELS OF DETAIL: A CASE STUDY[C]. ICC2009.
    [91]张桥平,李德仁,龚健雅,等.城市地图数据库面实体匹配技术[J].遥感学报,2004,8(2):107-112.
    [92]童小华,邓愫愫,史文中,等.基于概率的地图实体匹配方法[J].测绘学报,2007,35(2):210-217.
    [93]陈玉敏,龚健雅,史文中,等.多尺度道路网的距离匹配算法[J].测绘学报,2007,36(1):84-90.
    [94]郝燕玲,唐文静,赵玉新,等.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.
    [95]帅赟,艾廷华,帅海燕,等.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,2008,33(12):1267-1270.
    [96]艾廷华,帅赟,李精忠,等.基于形状相似性识别的空间查询[J].测绘学报,2009,38(4):356-362.
    [97]唐炉亮,李清泉,杨必胜,等.空间数据网络多分辨率传输的几何图形相似度度量[J].测绘学报,2009,38(4):336-340.
    [98]邓敏,徐凯,赵彬彬,等.基于结构化空间关系信息的节点层次匹配方法[J].武汉大学学报·信息科学版,2010,35(8):913-916.
    [99]付仲良,邵世维,童春芽,等.基于正切空间的多尺度面实体形状匹配[J].计算机工程,2010,35(17):216-217.
    [100]安晓亚,孙群,肖强,等.一种形状多级描述方法及在多尺度空间数据几何相似性度量中的应用[J].测绘学报,2011,40(4):495-501.
    [101]王斌.一种基于多级弦长函数的傅立叶形状描述子[J].计算机学报.2010,33(12):2387-2396.
    [102] Kilpel inen, T. and Sarjakoski, T.,1995, Incremental generalization for multipleRepresentations of geographical objects[C].Chapter15in GIS and Generalization-Methodology andPractice, GISDATA1,209-218.
    [103] Lars E. Harrie. Incremental generalisation: a feasibility study[C].Sweden,GISRUK Edinburgh, UK31st March-2nd April.
    [104] David Skogan. Towards a Rule-based Incremental Generalization System[C].5th AGILEConference on Geographic Information Science, Palma (Mallorca, Spain) April25th-27th2002.
    [105] Anders, K.-H.&Bobrich J.2004: MRDB approach for automatic incremental update[C]. ICAWorkshop on Generalisation and Multiple Representation, August2004, Leicester, England.
    [106] Karl-Heinrich Anders, Monika Sester. INCREMENTAL UPDATE IN AN MRDB. ICC2007.
    [107]蒋捷,陈军.基础地理信息数据库更新的若干思考[J].测绘通报,2000,(5):1-3.
    [108]陈军,李志林,蒋捷,等.基础地理数据库的持续更新问题[J].地理信息世界,2004,2(5):1-5.
    [109]傅仲良,吴建华.多比例尺空间数据库更新技术研究[J].武汉大学学报·信息科学版,2007,32(12):1115-1118.
    [110]应申,李霖,刘万增,等.版本数据库中基于目标匹配的变化信息提取与数据更新[J].武汉大学学报·信息科学版,2009,34(6):752-755.
    [111]王育红,陈军.基础地理数据库更新信息船舶实施方法研究[J].武汉大学学报·信息科学版,2010,35(9):1116-1120.
    [112] Mattos, N., Meyer-Wegener, K. and Mitschang, B.(1993). Grand tour of concepts forobject-orientation from a database point of view[C]. Data and Knowledge Engineering,9,321-352.
    [113] Jones, C. B., Abraham, I.1986, Design Considerations for a Scale-Independent Database[C].Second International Symposium on Spatial Data Handling, Seattle, International Geographical Union,384-398.
    [114] Guptill S C. Speculations on seamless, scaleless cartographic databases[C]. Proceedings ofAUTOCARTO9. ASPRS, Falls Church.1989:436-443.
    [115] JONES C.B., KIDNER D.B., LUO, L.Q., et al. Database design for a multi-scale spatialinformation system[J]. Geographical Information Systems,1996,10(8):901-920.
    [116]黄慧.基于边-节点和原子属性的多比例尺GIS数据模型[J].武汉大学学报·信息科学版,2004,29(12):1067-1070.
    [117]栗松延.单级比例尺电子地图数据库多级表现系统的设计[J].武汉测绘科技大学学报,1999,24(2):158-161.
    [118]吴建华.基于通比例尺思想的多尺度空间数据组织方法[J].测绘通报,2008,(8):10-13.
    [119]朱欣焰,张建超,李德仁,等.无缝空间数据库的概念、实现与问题研究[J].武汉大学学报·信息科学版,2002,27(4):382-286.
    [120]李爱勤.无缝空间数据组织及其多比例尺表达与处理研究[D].武汉大学,2001.
    [121]王卉.无缝GIS相关理论与技术的研究[D].信息工程大学,2004.
    [122] James R. Munkres著,熊金城,吕杰,谭枫,等译.拓扑学[M].北京:机械工业出版社,2008.
    [123]郭薇,陈军.基于流形拓扑的三维空间实体形式化描述[J].武汉测绘科技大学学报,1997,22(3).
    [124]尤承业.基础拓扑学讲义[M].北京大学出版社,1997.
    [125] Sim D G,Kwon O K,Park R H.Object mathing algorithm using robust Hausdorff distancemeasures[J].IEEE Transactions on Image Processing,1999,8(3):425-429.
    [126]邓敏,钮沭联,李志林.GIS空间目标的广义Hausdorff距离模型[J].武汉大学学报(信息科学版),2007,32(7):641-645.
    [127] Orass S.R. Automated Sounding Selection [J].The International Hydrographic Review,1975,22(2):103-115.
    [128] Jones, R.W.,1986: Computer Assisted Sounding Selection for the Shipboard Data System III,Ocean86[T]. the Washington D.C. Section of the Marine Technology Society, Washington D.C., USA,Vol.1, pp.141-147.
    [129] Steven Zoraster, Stephen Bayer. Automated Cartographic Sounding Selection [C]. InternationalHydrographic Review, Monaco, LXIX (1), March1992,39(1):57-61.
    [130] Lysandros T. Sounding selection for nautical charts: An expert system approach[C].The18th ICC,Stockholm.1997:2021-2028.
    [131] Langran, G.E., Poiker, T.K... Integration of name selection and name placement[C]. In Proc.2ndInternational Symposium on Spatial Data Handling,1986, pp.50-64.
    [132] Marc van Kreveld. Efficient Settlement Selection for Interactive Display[C]. In:Proceeding ofAutoCarto12,Bethesda,Md.,1995:287~296.
    [133]毋河海.凸壳原理在点群目标综合中的应用[J].测绘工程,1997,6(1):1-6.
    [134]陆毅,翟京生,杜景海,等.数字海图点群状特征的识别、量测与综合[J].武汉大学学报·信息科学版,2001,6(2):133-139.
    [135] Lu, Y., Du, J. and Zhai, J.,2001: A Model of Point Cluster Generalization with Spatial DistributionFeatures Recognized and Measured[C]. Proceedings of20th International Cartographic Conference,Beijing, pp.2123—2128.
    [136]艾廷华,刘耀林.保持空间分布特征的群点化简方法[J].测绘学报,2002,31(2):175-181.
    [137]毛政元.集聚型空间点模式结构信息提取研究[J].测绘学报,2007,36(2):181-186.
    [138]李雯静,林志勇,龙毅,等.粗集分类思想在GIS点群综合中的应用[J].武汉大学学报信息科学版,2008,33(9):896-899.
    [139]李雯静,邱佳,龙毅,等.粗集方法在地图综合中的应用[J].测绘学报,2012,41(1):298-301,30.
    [140] Sui H.G., CHENG P.G., ZHANG A,M.,et al, An Algorithm for Automatic Cartographic SoundingSelection[J].Geo-Spatial Information Science,2(1)96-99,1999
    [141] Sui H.G., HUA L., ZHAO H.T., et al. A Fast Algorithm of Cartographic SoundingSelection[J].Geo-Spatial Information Science,2005,8(4):262-268.
    [142] Dey, T., Edelsbrunner, H., Guha, S., Nekhayev, D..Topology Preserving Edge Contraction[C].Technical Report RGI-Tech-98-018, Raindrop Geomagic Inc., Research Triangle Park, North Carolina(1998).
    [143] Bajaj C L, Schikore R.1998, Topology Preserving Data Simplification with Error Bounds[J].Computers&Graphics,1998,22(1):3-12.
    [144]周昆,潘志庚,石教英,等.基于三角形折叠的网格简化算法[J].计算机学报,1998,21(6):506-513
    [145]夏仁波,刘伟军,王越超,等.保持拓扑和尖角特征的网格简化算法[J].计算机工程2006,32(19):14-16
    [146] Rossignac J., Borrel P. Multi-resolution3D Approximations for Rendering[C]. In Modeling inComputer Graphics, pages455-465. Springer-Verlag, June-July1993.
    [147] Schroeder W. A Topology Modifying Progressive Decimation Algorithm[C]. In IEEE Visualization'97Proceedings, pages205-212. ACM/SIGGRAPH Press,1997.
    [148]陶志良,成迟薏,潘志庚,等.拓扑结构可变的动态多细节层次模型[J].自动化学报,2001,27(2):200-206.
    [149]陈鹏,高宇,吴玲达,等.视点相关且拓扑可变的多分辨网格动态构造算法[J].中国图象图形学报,2009,14(1):161-168.
    [150] Schroeder, W., Zarge, J., Lorensen, W. Decimation of Triangle Meshes[C]. Computer Graphics,1992,26(2):65~70.
    [151] Hugues Hoppe, Tony DeRose, Tom Duchamp, et al. Mesh Optimization [C]. In SIGGRAPH’93Conference Proceedings (1993). pp.19-26.
    [152] Hugues Hoppe. Progressive Meshes [C]. In SIGGRAPH '96Conference Proceedings (1996). pp.99-108.
    [153] Hugues Hoppe. Efficient Implementation of Progressive Meshes[J]. In Computers&Graphics.1998,22(1):27-36.
    [154] Hugues Hoppe. Smooth View Dependent Level-of-Detail Control and Its Application to TerrainRendering [C].IEEE, Visualization Proeeedings,1998:35-42.
    [155] Michael Garland, Paul S. Heckbert. Surface Simplification using Quadric Error Metrics[C]. InSIGGRAPH '97Conference Proceedings (1997). pp.209-216.
    [156] Michael Garland, Paul S. Heckbert. Simplifying Surfaces with Color and Texture using QuadricError Metrics[C]. In Visualization '98Proceedings (1998). IEEE, pp.263–269.
    [157] Lindstrom, P., Turk, G. Fast and Memory Efficient Polygonal Simplification [C]. In: Proceedings ofthe IEEE Visualization’98.1998.279~284.
    [158] Hugues Hoppe. New Quadric Metric for Simplification Meshes with Appearance Attributes [C]. In:IEEE Visualization.1999.59~66.
    [159]陶志良,潘志庚,石教英,等.基于能量评估的网格简化算法及其应用[J].软件学报,1997,8(12):881-888.
    [160]陶志良,潘志庚,石教英,等.支持快速恢复的可逆递进网格及其生成方法[J].软件学报,1999,10(5):503-507.
    [161] Paul S. Heckbert, Michael Garland. Survey of Polygonal Surface Simplification Algorithm [C].Proceedings of SIGGRAPH’97[C],1997:5-23.
    [162]何晖光,田捷,张晓鹏,等.网格模型化简综述[J].软件学报,2002,13(12):2215-2224.
    [163] Xia, Julie C., Jihad El-Sana, and Amitabh Varshney. Adaptive Real-Time Level-of-Detail-BasedRendering for Polygonal Models[J]. IEEE Transactions on Visualization and Computer Graphics. vol.3(2).1997. pp.171-183.
    [164] Luebke, D., Erikson, C.: View-dependent Simplification of Arbitrary Polygonal Environments[C].In: ACM SIGGRAPH1997Conference Proceedings, Los Angeles, California, pp.199-208(1997)
    [165] D. Luebke, A Developer's Survey of Polygonal Simplification Algorithms[C]. IEEE ComputerGraphics and Applications, vol.21, no.3, pp.24-35,2001.
    [166] J. Cohen, M. Olano, and D. Manocha, Appearance Preserving Simplification[C]. ComputerGraphics (Proc. Siggraph98), vol.32, ACM Press, New York,1998, pp.115-122.
    [167] Turk, G. Re-Tiling polygonal surfaces[J]. Computer Graphics, Vol.26, No.2(July1992). pp.55-64.
    [168]蒋遂平,周明天,戴颖,等.基于法向的网格简化[J].计算机学报[J].1999,22(10):1074-1079.
    [169]周昆,潘志庚,石教英,等.一种新的基于顶点聚类的网格简化算法[J].自动化学报[J].1999,25(1):1-8.
    [170]王军安,魏生民.距离加权的二次误差测度网格简化算法[J].计算机辅助设计与图形学学报2001,13(2):189-192.
    [171]周儒荣,唐杰,张丽艳,等.基于检测球控制的网格模型简化算法研究[J].软件学报[J].2001,12(11):1680-1686.
    [172]张丽艳,周儒荣,唐杰,等.带属性的三角网格模型简化算法研究[J].计算机辅助设计与图形学学报[J].2002,14(3):1-5.
    [173]唐杰,张福炎.一种任意网格模型的选择细化算法[J].计算机辅助设计与图形学学报,2005,17(1):28-33.
    [174]陆国栋,许鹏,温星,等.基于向量夹角的三角网格模型简化算法[J].工程设计学报[J].2005,12(2):124-128.
    [175]刘晓利,刘则毅,高鹏东,等.基于尖特征度的边折叠简化算法[J].软件学报,2005,16(5):669-675.
    [176]左小清,李清泉,方源敏,等.一种渐进格网模型的改进算法[J].中国矿业大学学报,2006,35(2):225-230.
    [177]周元峰,张彩明,贺平,等.体积平方度量下的特征保持网格简化方法[J].计算机学报,2009,32(2):203-212.
    [178]周晓云,刘慎权.基于特征角准则的多面体模型简化方法.计算机学报.1996(增刊):212~223.
    [179]潘志庚,马小虎,石教英,等.多细节层次模型自动生成技术综述[J].中国图像图形学报,1998,3(9):744-749.
    [180]李胜,冀俊峰,刘学慧,等.超大规模地形场景的高性能漫游[J].软件学报,2006,17(3):535-545.
    [181] Lindstrom P,Koller D,Ribarsky W,et al.Real-Time Continuous Level of Detail Rendering of HeightFields[J].ACM Computer Graphics(SIGGRAPH’96),1996,30(3):109-118.
    [182] Duchaineau Mark A,Wolinsky Murray,Sigeti David E.ROAMing Terrain:Real-time OptimallyAdapting Meshes [C]. IEEE Visualization1997.Los Alamitos:IEEE Computer Society Press,1997:81-88.
    [183]王宏武,董士海.一个与视点相关的动态多分辨率地形模型[J].计算机辅助设计与图形学学报,2000,12(8):575-579.
    [184]谭兵,徐青,马东洋,等.用约束四叉树实现地形的实时多分辨率绘制[J].计算机辅助设计与图形学学报,2003,15(3):270-276.
    [185]曾俊,陈天泽,匡纲要,等.一种基于二叉树结构的大规模地形实时渲染方法[J].计算机仿真,2004,21(11):177-177.
    [186]张立强,杨崇俊.多进制小波和二叉树实现大规模地形的实时漫游[J].计算机辅助设计与图形学学报,2005,17(3):467-472.
    [187]许妙忠.大规模地形实时绘制的算法研究[J].武汉大学学报信息科学版,2005,30(5):392-395.
    [188] Desmet P. J. J.. Effects of Interpolation Errors on the Analysis of DEMs[J]. Earth Surface Processesand Landforms. June1997,Volume22, Issue6, pages563–580.
    [189] Aguilar, F.J., Agüera, F., Aguilar, M.A., Carvajal, F.,2005. Effects of Terrain Morphology,Sampling Density, and Interpolation Methods on Grid DEM Accuracy[J]. Photogrammetric Engineeringand Remote Sensing, July2005, Vol.71, No.7, pp.805–816.
    [190] Chaplot et al. Accuracy of Interpolation Techniques for the Derivation of Digital Elevation Modelsin Relation to Landform Types and Data Density[J], Geomorphology,2006,77(12), pp.126-141
    [191] Ai, T.H. and Li, J.Z.. A DEM Generalization by Minor Valley Branch Detection and Grid Filling[J].ISPRS Journal of Photogrammetry and Remote Sensing,2010,65(2),198–207.
    [192] Zhou Q.M., Chen Y.M.Generalization of DEM for Terrain Analysis Using a Compound Method [J].ISPRS Journal of Photogrammetry and Remote Sensing, January2011,Volume66, Issue1, Pages38–45.
    [193] Chen Y.M., John P. Wilson, Zhu Q.S, et al. Comparison of Drainage-constrained Methods for DEMGeneralization[J]. Computers&Geosciences,2012, http://dx.doi.org/10.1016/j.cageo.2012.05.002.
    [194] Emanuel Mahler. Scale-Dependent Filtering of High Resolution Digital Terrain Models in theWavelet Domain [D]. University of Zurich,2001.
    [195]蔡先华,郑天栋.数字高程模型数据压缩及算法研究[J].测绘通报,2003,(12):16-18.
    [196]王建,杜道生.规则格网DEM化简的一种改进方法[J].测绘信息与工程,2007,32(2):34-36.
    [197]万刚,朱长青.多进制小波及其在DEM数据有损压缩中的应用[J].测绘学报,1999,28(1):36-40.
    [198]吴凡.基于小波分析的地貌多尺度表达与自动综合[J].武汉大学学报信息科学版,2001,26(2):170-176.
    [199]杨族桥,郭庆胜,牛冀平,等.DEM多尺度表达与地形结构线提取研究[J].测绘学报,2005,34(2):134-137.
    [200]李精忠,艾廷华,王洪,等.一种基于谷地填充的DEM综合方法[J].测绘学报,2009,38(3):272-275.
    [201] R. Pajarola, M. Antonijuan and R. Lario. QuadTIN: Quadtree Based Triangulated IrregularNetworks[C]. Proceedings IEEE Visualization.2002. pp.395-402.
    [202]赵友兵,石教英,周骥,等.一种大规模地形的快速漫游算法[J].计算机辅助设计与图形学学报,2002,14(7):624-628.
    [203]潘志庚,马小虎,石教英,等.虚拟环境中多细节层次模型自动生成算法[J].软件学报,1996,7(9):526-531.
    [204]张建保,杨涛,孙济舟,等.基于顶点删除算法的连续多分辨率模型显示[J].中国图像图形学报,1999,4(5):395-399.
    [205]陈刚,杨明果,王科伟,等.地形TIN模型的实时连续LOD算法设计与实现[J].测绘学院学报,2003,20(4):286-289.
    [206]许妙忠,李德仁.基于点删除的地形TIN连续LOD模型的建立和实时动态显示[J].武汉大学学报信息科学版,2003,28(6):321-324.
    [207]张寅宝,王光霞,王国庆,等.基于点重要度的地形LOD简化算法及精度[J].测绘学院学报,2003,22(4):281-284.
    [208]余明,左小清,李清泉,等.一种基于TIN的视相关动态多分辨率地形模型[J].武汉大学学报信息科学版,2004,29(12):1106-1120.
    [209]陈准,姚国清,梁凤林,等.基于点删除的TIN简化算法改进[J].国土资源遥感,2005,25(3):24-26.
    [210]蒲浩,宋占峰.基于可见性预处理的地形模型视相关简化算法[J].武汉大学学报信息科学版,2005,30(7):636-639.
    [211]费立凡,何津,马晨燕,等.3维Douglas-Peucker算法及其在DEM自动综合中的应用研究[J].测绘学报,2006,35(3):278-284.
    [212] Lifan Fei&Jin He: A Three-dimensional Douglas–Peucker Algorithm and Its Application toAutomated Generalization of DEMs [J]. International Journal of Geographical Information Science,2009,23(6),703-718.
    [213]张立华,贾帅东,吴超,等.顾及不确定度的数字水深模型内插方法[J].测绘学报,2011,40(3):359-365.
    [214]张立华,贾帅东,元建胜,等.一种基于不确定度的水深控浅方法[J].测绘学报,2012,41(2):184-190.
    [215] Wang, Z. and Müller, J. C.(1998). Line generalization based on analysis of shape characteristics[J].Cartography and Geographic Information Systems,22(4):264–275.
    [216] Wang Z, Müller, J. C. Line Generalization Based on Analysis of Shape Characteristics[J].Cartography and Geographic Information Systems,1998,25(1):3-15.
    [217] Visvalingam M, Herbert S. A Computer Science Perspective on the Bend Simplification Algorithm[J]. Cartography and Geographic Information Science,1999,26(4):253-270.
    [218]毋河海.数字曲线拐点的自动确定[J].武汉大学学报·信息科学版,2003,28(13):330-335.
    [219]罗广祥,祝国瑞,毋河海,等.坐标单调性分析下地图曲线弯曲识别模型的研究[J].测绘通报,2005,10:21-24.
    [220]罗广祥,陈晓羽,赵所毅,等.软多边形地图要素弯曲识别模型及其应用研究[J].武汉大学学报·信息科学版,2006,31(2),160-163.
    [221]郭庆胜,黄远林,章莉萍,等.曲线的弯曲识别方法研究[J].武汉大学学报·信息科学版,2008,33(6):596-599.
    [222] He, X.C., Yung, N.H.C.(2004). Curvature Scale Space Corner Detector with Adaptive Thresholdand Dynamic Region of Support[C]. Proceedings of the17th International Conference on PatternRecognition,2,791-794.
    [223] He, X.C., Yung, N.H.C.(2008). Corner Detector Based on Global and Local CurvatureProperties[J]. Optical Engineering,47(5).
    [224] Hongshan Nie, Zhijian Huang. A New Method of Line Feature Gerealization Based on ShapeCharacteristic Analysis[C]. Meas. Syst., Vol. XVIII (2011), No.4, pp.597–606.

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