摘要
随着互联网软硬环境建设的不断发展,互联网因其固有的分布式特征已逐步成为数据发布、数据共享、分布式计算的平台,借助于互联网这一广阔的信息传输平台,GIS应用领域得到了更大限度的拓展,在网络技术,多媒体技术、空间信息技术等的推动下,WebGIS技术得到了更为深层次方面的发展与应用。
在GIS应用中主要存在两类数据分别为矢量数据与栅格数据,矢量数据由于数据结构紧凑、冗余度低,有利于网络和检索分析,图形显示质量好,精度高等优点而得到广泛地应用,而栅格数据则凭借着数据结构简单,便于空间分析和地表模拟,现势性较强等优势在目前国土监测、灾害分析、环境监测等方面发挥了重要的作用。
目前由于矢量数据应用的广泛性和实用性,使得矢量数据成为空间信息化建设的基石,同时也因为针对不同的应用需求,各种GIS软件商对数据结构和模型采用不同的设计理念,使得矢量数据的数据结构呈现的多样性和复杂性,但目前以上的各种数据模型还不能很好地解决WebGIS中矢量数据的快速传输和客户端显示等问题。
随着web2.0技术的发展与成熟,基于栅格数据下的高性能网络传输已经通过分块模型得到了基本的解决,使得以栅格图片格式为基础的WebGIS技术成熟起来,并投入到国家信息化建设的各个领域,但由于栅格数据自身所固有的缺陷,使得目前基于栅格图片技术建立的WebGIS使用受到了功能的限制。因此,基于矢量数据的WebGIS的研究与探索就成了目前关注的焦点话题之一。
文章首先从WebGIS基本特征、实现的技术模式以及体系结构等方面详细叙述了WebGIS实现机制,从应用方面分析了各种WebGIS搭建方法的优势和不足,结合目前成熟的基于地图图片的WebGIS技术,通过实验分析了这种技术下数据组织模型、数据交互式传输以及数据展示等方面的,同时也分析当前采用矢量数据渐进式传输的数据组织思想、特点以及存在的问题。
其次,本文从缓存的存储方式、服务器端缓存和客户端缓存等方面讨论了如何将这种技术应用到基于矢量数据的WebGIS中,从而最终减少数据的重复性传输；阐述了四叉树数据结构,提出了基于文件存储的线性四叉树构建方法,并讨论了同一等级和上下级之间的拓扑关系；同时结合矢量数据渐进式传输中用到的模型以及WebGIS的理论,采用以空间换时间的思想,提出了基于层次增量分块矢量模型的服务器端矢量数据组织模型,并给出了相应的矢量块的剪裁及文件命名存储等的方法,同时也给出了客户端的矢量块文件数据融合实现机制。
接着,本文从与网络传输密切相关的矢量数据数据量入手,从数据压缩的基本原理和一般方法阐述了数据压缩的实质,从局部压缩思想和整体压缩思想两方面对矢量数据五种有损压缩算法进行了阐述与分析,考虑到以上压缩方法存在数据信息丢失的问题,所以本文从基于统计模型和基于字典模型两方面阐述了Huffman编码、算术编码以及基于第一类字典编码、第二类字典编码的无损压缩算法,同时结合矢量数据特点、网络传输以及数据压缩,指出除了要建立一种合适的矢量数据模型外,还要对矢量数据传输前进行多种组合的压他缩,并给出了矢量数据坐标几何压缩的方法以及基于Gzip编码的网络压缩与传输的思路,从而减少了网络传输的矢量数据量；同时结合服务器端的矢量数据组织,提出了从控制刷新数据量,采取基于特征要素交互式传输和基于Web Service的交互式异步传输等方面的传输策略来提高矢量数据的传输效率,最终达到提高用户体验的目的。
文章最后通过实验从网络传输数据量、传输时间以及客户端数据显示与编辑等方面对前面叙述的数据压缩、缓存技术运用、传输策略以及数据融合等进行验证,同时也指出以上方式存在的问题。
With the development of the hardware and software, the Internet has gradually become the platform of data releasing, date sharing, and distributed computing. Because of it's inherently distributed features. By means of the Internet and driven by the network technology, multimedia technology and spatial information technology, WebGIS has broad development and applications.
In GIS applications, there are two main types of data:vector data and raster data. Vector data has the features of compact data structure, low redundancy, good graphical display quality, and high precision. So vector data are conductive to networking and search analysis. The raster data has the features of simple data structure, easy to surface modeling and spatial analysis, etc. Raster data has played an important role in land monitoring, hazard analysis, environmental monitoring, and so on.
At present, because of the extensive and practical applications of vector data, it has become the cornerstone of spatial information construction. In order to meet the different application requirements, a variety of GIS software have their different data structures and business models to make the vector data structure to demonstrate the diversity and complexity. However, above all the data models can not solve the issues of rapid vector data transmission and display in the clients of WebGIS.
With the development of Web2.0, the high-performance network transmission of raster data has been solved by the block model. The WebGIS technology based on the raster image formats has become matured and applied in the fields of national information construction. But because of raster data's inherent deficiencies, WebGIS based on the raster image technology has the restrictions of its function applications. Therefore, the exploration of WebGIS based on vector data has become one of the current hot topics of concern.
This paper firstly describes WebGIS implement mechanism in detail from the aspects of its basic features, technical model and architecture, And WebGIS construction methods from the applications. What's more, combined with current mature WebGIS technology based on map image, the author analyzes not only the data organization model, interactive data transmission, data presentation, but also data organization thinking, characteristics and problems of the current progressive transmission of vector data through the experiments.
Secondly, this paper discusses how to apply the cache technology to the WebGIS based on vector data in order to reduce the repeatability of data transmission. Then, the author analyzes quadtree data structure, proposes a linear quadtree construction method based on file storage and discusses the topological relations of the same level and different levels. Combined with progressive transmission model of vector data, WebGIS theory and idea of space for time, the author proposes vector data organization model based on block-level incremental vector model in the server, the corresponding methods of cutting vector blocks and file storage, and the methods of data fusion in the client.
Thirdly, this paper describes the essence of the vector data compression and five lossy compression algorithms from the local compression and the overall compression. Taking into account the loss of data compression, this paper analyzes the Huffman coding, arithmetic coding, dictionary coding, Combined with vector date features, network transmission and data compression, the author analyzes the establishment of a suitable vector data model, compression vector data before data transmission, the geometric compression of vector data coordinates, and idea of network compression and transmission based on Gzip coding to reduce the amount of vector data transmission. Meanwhile I propose a new strategy to enhance transmission efficiency of vector data through a combination of vector data organization at server side, reducing update data volumes, interactive transmission based on feature characteristics, as well as interactive as asynchronous transmission methods. By means of these methods, we finally achieve the goal of promoting user experience.
Finally, the author verifies the described data compression, cache application, transmission strategy, and data fusion, by the experiments from the amount of network data transmission, transmission time, data display and editing in the client. Furthermore, the author points out the problems as above.
引文
[1]龚健雅.地理信息系统基础[B].科学出版社,2001,5-5.
[2]宋关福,钟耳顺,王尔琪.webGIS—基于Internet的地理阿信息系统[J].中国图象图形学报,1998(3).
[3]周强中,谈俊忠,SVG在WebGIS中的运用[J].计算机应用研究,2003,(1)：108-121
[4]王兴玲,基于XML的地理信息Web服务研究[D].北京：中科院遥感所,2002.
[5]Bertolotto, M.and Egenhofer, M.2001.Progressive Transmission of Vector Map Data over the World Wide Web.Geolnformatica,5(4):345-373
[6]Bertolotto,M. and Egenhofer,M.1999. Progressive Vector Transmission. Proceedings,7th International Symposium on Advances in Geographic Information Systems.Kansas City, MO:p152-157
[7]Buttenfield,B.E 2002. Transmitting Vector Geospatial Data across the Internett,Egenhofer,M. J. and Mark,D.M(eds.)Proceedings GIScience 2002. Berlin:Springer Verlag. Lecture Notes in Computer Science No 2478:51-64
[8]Han, H, Tan, V and Wh, H.2003. Progressive Vector Data Transmission, Proceedings of 6th AGILE, Lyon,France
[9]李军,周成虎,地球空间数据集成多尺度问题基础研究,《地球科学进展》,2000年1期
[10]王家耀、成毅,空间数据的多尺度特征与自动综合,《海洋测绘》,2004.4
[11]王艳慧,陈军,GIS中地理要素多尺度概念模型的初步研究,《中国矿业大学学报》,2003
[12]王晏民,李德仁,龚健雅,一种多比例尺GIS方案及其数据模型,《武汉大学学报》信息科学2003
[13]Oosterom P Van. Reactive Data Structure for Geographoc Information Systems [M]. Oxford:Oxford University Press,1994
[14]Yang B, Purves R, Weibei R. Efficient Transmission of Vector Data Over The Internet [J]. International Journal of Geographical Information Science,2007,21 (2):215-237
[15]Douglas, D. H. and Peucker, T. K.1973. Algorithms for the Reduction of the Number ofPoints Required to Represent a Line or Its Caricature. The Canadian Cartographer,v01.10(2):112-122
[16]艾廷华.多尺度空间数据库建立中的关键技术与对策.科技导报.2004,12：4-8
[17]艾波.网络地图矢量数据流媒体传输的研究.武汉大学硕士论文.2005：1-11.
[18]王玉海,崔铁军,吴天君.基于提升型小波变换的矢量数据渐进式传输的研究[J].地理信息世界.2009,7(5)
[19]马荣华.地理空间认知与GIS空间数据组织研究.南京大学博士学位论文,2002年
[20]王宇翔.分布式网络地理信息系统研究.中科院遥感技术应用研究所,博士学位论文,2002
[21]Peuquet D.A hybrid structure for the storage and manipulation of very large spatial data sets.Computer Graphics and Image Processing.1983, (24):14-27
[22]Paul Hardy.Multi-scale database generalisation for topographic mapping. Hydrography and Web-mapping. Using active object techniques.IAPRS.Vol.ⅩⅩⅩ Ⅲ.Amsterdam,2000
[23]李小鹃.基于特征的时空数据模型及其在土地利用动态监测信息系统中的应用.北京：中国科学院遥感应用研究所,博士学位论文,1999
[24]杜海平,詹长根,李兴林.现代地籍测量理论与实践.深圳：海天出版社,1999.5
[25]王家耀.空间信息系统原理.北京：科学出版社,2001
[26]肖乐斌.面向对象整体GIS数据模型的研究及其软件系统的研制.中国科学院遥感应用研究所博士后士学位论文,2001.12
[27]Ballard, D.1981. Strip Trees:A Hierarchical Representation for Curves. Communication of the Association for Computing Machinery, vol.14:310-321.
[28]Buttenfield, B.1984. Line Structure in Graphic and Geographic Space. Unpublished
[29]Ph.D. Thesis, Department of Geography, University of Washington, Seattle
[30]Buttenfield, B.1989. Scale-Dependence and Self-Similarity in Cartographic Lines. Cartographica, vol.26(1),79-100.
[31]Ramer, U.1972. An Iterative Procedure for the Polygonal Approximation of Plane Curves.Computer Vision Graphics and Image Processing, vol.1:244-256.
[32]Douglas, D. and Peucker, T.K.1973. Algorithms for the Reduction of the Number of
[33]Points Required to Represent a Line or Its Caricature. The Canadian Cartographer, vol
[34]艾廷华,城市地图数据库综合的支撑数据模型与方法的研究,[博士论文],2000年4月,武汉测绘科技大学
[35]吴乐南.《数据压缩》,电子工业出版社,2000.6第一版
[36]单玉香.矢量数据压缩模型与算法的研究.太原理工大学硕士论文.2004
[37]王平,朱雪梅.计算机互联网络中的数据压缩技术应用.计算机工程.2002,28(12)：P153-154
[38]王平,茅忠明.中文文本的LZSS算法实现及研究.微电子学与计算机.2001,(2)：P14-17
[39]林小竹,籍俊伟.一种改进的LZ77压缩算法.计算机工程.2005,31(14)
[40]王平.无损压缩算法的实现与研究.计算机工程.2002,28(7)：P98-99
[41]杨国粱,张光年.无损LZW压缩算法及实现.首都师范大学学报(自然科学版).2004,25：P11-13
[42]MicrosoftTerraServe.http://teraserver.homeadvisor.man.com/
[43]TerraShare-An Image Storage and Distribution Solution, http://www.ziimageing.com
[44]Jau-Yuen Chen, Charles A. Bouman, and John C. Dalton. Similarity Pyramids for Browsing and Organization of Large Image Database[C]. In Proc. SPIE/IS&I Conf. Human Vision and Electronic Imaging Ⅲ, Vol.3299, San Jose, CA, Jan.1998
[45]Walid G Aref and Hanan Samet. Efficient Window Block Retrieval in Quadtree-Based Spatial Databases [J]. Geolnformatica,1(1):59-91, April 1997
[46]Richard Szeliski and Heung-Yeung Shum. Motion Estimation with Quadtree Splines[R]. Technical Report 95/1, Digital Equipment Corporation, Cambridge Research Lab, March 1995
[47]David Cline and Parris K. Egbert. Terrain Decimation through Quadtree Morphing [J]. IEEE Transactions on Visualization and Computer Graphics, Vol.7(1), pp.62-69,2001
[48]Hamid R. Rabiee, R. L. Kashyap, and S. R. Safavian. Multiresolution Segmentation-based Image Coding with Hierarchical Data Structures[C]. IEEE ICAMSSP'96, Atlanta, GA, May 1996
[49]严蔚敏,吴伟民.数据结构.北京：清华大学出版社,1992
[50]Renato Pajarola. Large Scale Terrain Visualization Using the Restricted Quadtree Triangulation[C]. Proceedings of IEEE Visualization 1998
[51]Hanan Samet. Applications of Spatial Data Structures:Computer Graphics, Image Proceeding, and GIS[M]. Addison Wesley, Reading, MA,1990
[52]Theodoros Tzouramanis, Michael Vassilakopoulos, and Yannis Manolopoulos.Multiversion Linear Quadtree for Spatio-Temporal Data[A]. Proceedings of the Database Systems for Advanced Applications Conference (DASFAA), pp.279-292,2000
[53]Hanan Samet. Spatial Data Structures.http://infolab.usc.edu/csci585/Spring2003/den_ar/
[54]Nickolas Faust, William Ribarsky, T. Y Jiang, and Tony Wasilewski. Real-Time Global Data Model for the Digital Earth[C]. Proceedings of International Conference on Discrete Global Grids (2000)
[55]Cecconi, A., Galanda, M.:Adaptive zooming in Web cartography. In:SVGOpen 2002 (2002)
http://www.svgopen.org/2002/papers/cecconi_galanda_adaptive_zooming/index.html
[56]Lehto, L., Sarjakoski, L.T. Real-time generalization of XML-encoded spatial data for the Web and mobile devices. International Journal of Geographical Information Science 19(8),957-973 (2005)
[57]Jones, C.B., Ware, and J.M.:Map generalization in the Web age. International Journal of Geographical
Information Science 19(8),859-870 (2005)
[58]Martin Reddy, Yvan Levlerc, Lee Iverson, and Nat Bletter. TerraVisionⅡ:Visualzing Massiove Terrain Database in VRML[J].IEEE Computer Graphics & Application, Vol.19.pp.30-38, March/April 1999.
[59]张永生.数字摄影测量[M].解放军出版社,1997
[60]Hamid R.Rabiee,R.L.Kashyap, and S.R.Safavuan.Multiresolution Segmantation-based Image Codeing with Hierachical Data Structures[C].IEEE ICAMSSP'96, Atlanta, GA, May 1996
[61]Jay-Yuen Chen, Charles A.Bouman, and John C.Dalton. Similarity Pyramids for Browsing and Organization of Large Image Database[C].In Proc.SPIE&I Conf. Human Vision and Electronic Imaging Ⅲ, Vol.3299, San Jose, Ca, Jan.1998
[62]Jay-Yuen Chen, Charles A.Bouman, and John C.Dalton. Hierarchical Browsing and Search of Large Image Databases [J].IEEE Transactions on Image Proceeding, Vo19, No3, March 2000
[63]David Cline and Parris K.Egbert. Interactive Display of Very Large Textures. [A] In IEEE Visualization, page343-350,1998
[64]张海勤,欧阳为民,蔡庆生,聚类金字塔树：一种新的高维空间数据索引方法[J].中国科学技术大学学报,Vol.31, No.6,12.2001
[65]Bertolotto, M. Progressive Techniques for Efficient Vector Map Data Transmission:An Overview. In: Belussi, A., Catania, B., Clementini, E., Ferrari, E. (eds.) Spatial Data on the Web:Modeling and Management, pp.65-84. Springer, New York (2007)
[66]Dykes, J.A.:Exploring spatial data representation with dynamic graphics. Computers & Geosciences 23(4),345-370 (1997)
[67]Cook, D., Symanzik, J., Majure, J.J., and Cressie, N. Dynamic graphics in a GIS:More examples using linked software. Computers & Geosciences 23,371-385 (1997)
[68]Andrienko, G.L., Andrienko, N.V.:Interactive maps for visual data exploration. International Journal of Geographical Information Science 13(4),355-374 (1999)
[69]Zhao, H., Shneiderman, B.:Colour-coded pixel-based highly interactive Web mapping for georeferenced data exploration. International Journal of Geographical Information Science 19(4),413-428 (2005)
[70]Goodchild, M.:Citizens as sensors:the world of volunteered geography. GeoJournal 69(4),211-221 (2007)
[71]汪国平等.高速网上3维海量地形数据的实时交互浏览的实现[J],测绘学报,vol.31, Nol, Feb 2002
[72]单玉香.矢量数据压缩模型与算法的研究.太原理工大学硕士论文.2004
[73]Lehto, L., Sarjakoski, L.T.:Real-time generalization of XML-encoded spatial data for the Web and mobile devices. International Journal of Geographical Information Science 19(8),957-973 (2005)
[74]Jones, C.B., Ware, and J.M.:Map generalization in the Web age. International Journal of Geographical Information Science 19(8),859-870 (2005)
[75]Weibel, R., Dutton, and G.:Generalizing spatial data and dealing with multiple representations. In: Longley, A.P., Goodchild, F.M., Maguire, J.D., Rhind, W.D. (eds.) Geographical information systems. John Wiley & Sons, Chichester (1999)
[76]Yang, C., Wong, W.D., Yang, R., Kafatos, M., Li, Q.:Performance-improving techniques in web-based GIS. International Journal of Geographical Information Science 19(3),319-342 (2005)
[77]Weibel, R., Dutton, G. Generalizing spatial data and dealing with multiple representations.In:Longley, A.P., Goodchild, F.M., Maguire, J.D., Rhind, W.D. (eds.) Geographicalinformation systems. John Wiley & Sons, Chichester (1999)
[78]Campin, B.:Use of vector and raster tiles for middle-size Scalable Vector Graphics' mapping applications. In:SVGOpen 2005 (2005), http://www.svgopen.org/2005/papers/VectorAndRaster Tiles for Mapping Applications/
[79]Rigaux, P., Scholl, M., Voisard, A. Spatial Databases:With Application to GIS. Morgan Kaufmann Publishers, San Francisco (2002)
[80]Yang, B.:A multi-resolution model of vector map data for rapid transmission over the Internet. Computers & Geosciences 31(5),569-578 (2005)
[81]Antoniou, V, Morley, J., Haklay, and M.:Is your Web map fit for purpose? Drawing a line under raster mapping. In:AGI Geocommunity 2008 (2008),http://www.agi.org.uk/site/upload/document/Events/AG 12008/Papers/VyronAntoniou.pdf
[82]骆新,陈睿.数据压缩实用技术.[M].北京：学苑出版社.1993
[83]Spatial User's Guide and Reference[R/OL]. http://ahiti.oracle.eom/pls/Tahiti/tahifidrilldown? levelnum=2&toplevel=ag5337&method=FULI-ehaptem=0&book=&wildeards=1&preference=&expand— all=&verb=&word=Spatial#a85337,2004-03
[84]陆峰,周成虎一种基于Hilbert排序码的GIS空间索引方法闭.计算机辅助设计与图形学报,Vol.13, No.5, May,2001
[85]艾廷华.面向流媒体传输的空间数据变化累积模型[J].测绘学报.Vol.38, No.6 Dec.2009
[86]Molina HG, Unman JD, Widom J. Database System lmplefnentation[M]. Standford Unvemity Press, 2000
[87]钱国祥、孙宏、彭振云.数据压缩技术经典[M].北京：学苑出版社.1994
[88]Cecconi, A., Galanda, M.:Adaptive zooming in Web cartography. In:SVGOpen 2002 (2002), http://www.svgopen.org/2002/papers/cecconi_galanda_adaptive_zooming/index.html
[89]黄培之.具有预测功能的曲线矢量数据方法.测绘学报.1995,24(4)：P316-319
[90]杨建宁,杨崇峻,明东萍,任应超,李津平.WebGIS系统中矢量数据的压缩与化简方法综述.计算机工程与应用.2004,32：P36-38
[91]Nirwan Ansari and Edward J Delp. On Detecting Dominant Points. Pattern Recognition. Report No.379/Dept.of Geodetic Science and Surveying.The Ohio State University.1987
[92]严华.常用的数据压缩方法及其效果.计算机世界周刊.1994,(4)：P24-27
[93]李青元,刘晓东,曹代勇.WebGIS矢量空间数据压缩方法探讨.中国图形图像学报.2001,6(12),P1225-1229
[94]李琦,杨超伟,陈爱军.WebGIS中的地理关系数据库模型研究.中国图象图形学报.2000,5(2)：P119-123
[95]Selvakumar S, Prabhaker P. Implementation and Comparison of Distributed Caching Schemes. Computer Communication,2001 (24):677-684
[96]http://hwg86.blog.163.com/blog/static/655869102009101614327898/
[97]http://www.silverlight.net/
[98]Antoniou V, Morley J, Haklay M.Tiled Vectors:A Methed for Vector Transmission over the Web [J].Springer-Verlag Berlin Heidelberg.2009, LNCS 5586:56-71
[99]David Cline and Parris K.Egbert.Terrain Decimation through Quadtree Morphing [J]. IEEE Transactions on Visualization and Computer Graphics, Vol.7(1), pp.62-69,2001
[100]Hamid R. Rabiee, R. L. Kashyap, and S. R. Safavian. Multiresolution Segmentation-based Image Coding with Hierarchical Data Structures[C]. IEEE ICAMSSP'96, Atlanta, GA, May 1996
[101]Laurent Balmelli, Jelena Kovacevic, and Martin Vetterli. Solving the Coplanarity Problem of Regular Embedded Triangulations[C]. Proceedings of Vision, Modeling and Visualization, Nov.1999. Laurent Balmelli, Jelena Kovacevic, and Martin Vetterli. Quadtrees for Embedded Surface Visualization: Constraints and Efficient Data Structures[A]. Proceedings of IEEE International Conference on Image Processing (ICIP), Vol.2, p.487-491, Oct.1999
[102]Jau-Yuen Chen, Charles A. Bouman, and John C. Dalton. Similarity Pyramids for Browsing and Organization of Large Image Database[C]. In Proc. SPIE/IS&I Conf. Human Vision and Electronic Imaging Ⅲ, Vol.3299, San Jose, CA, Jan.1998
[103]Renato Pajarola. Large Scale Terrain Visualization Using the Restricted Quadtree Triangulation[C]. Proceedings of IEEE Visualization 1998
[104]John S. Falby, Michael J. Zyda, David R. Pratt, and Randy L. Mackey. NPSNET:Hierarchical Data Structures for Real-Time Three-Dimensional Visual Simulation [J]. Computers and Graphics, Vol.17, No.1,1993,pp.65-69
[105]Hanan Samet. Applications of Spatial Data Structures:Computer Graphics, Image Proceeding, and GIS [M]. Addison Wesley, Reading, MA,1990
[106]Walid G. Aref and Hanan Samet. Efficient Window Block Retrieval in Quadtree-Based Spatial Databases[J]. Geolnformatica,1(1):59-91, April 1997
[107]Sabine Timpf and Andrew U. Frank. Using Hierarchical Spatial Data Structures for Hierarchical Spatial Reasoning[C]. International Conference COSIT'97
[108]Theodoros Tzouramanis, Michael Vassilakopoulos, and Yannis Manolopoulos.Multiversion Linear Quadtree for Spatio-Temporal Data [A]. Proceedings of the Database Systems for Advanced Applications Conference (DASFAA), pp.279-292,2000
[109]Richard Szeliski and Heung-Yeung Shum. Motion Estimation with Quadtree Splines[R]. echnical Report 95/1, Digital Equipment Corporation, Cambridge Research Lab, March 1995
[110]Hanan Samet. Spatial Data Structures.http://infolab.usc.edu/csci585/Spring2003/den_ar/
[111]Gennady Agranov and Craig Gotsman. Algorithms for Rendering Realistic Terrain Image Sequences and Their Parallel Implementation [M]. The Visual Computer 11(9):455-464,1995
[112]Nickolas Faust, William Ribarsky, T. Y Jiang, and Tony Wasilewski. Real-Time Global Data Model for the Digital Earth[C]. Proceedings of International Conference on Discrete Global Grids (2000)
[113]艾廷华,成建国.对空间数据多尺度表达有关问题的思考.武汉大学学报,2005(5)
[114]徐颖.基于B/S和C/S相结合的网络架构系统对比分析.电脑知识与技术,2005.04.27
[115]M. Robert Parry, Brendan Hannigan, William Ribarsky, Christopher D. Shaw, and Nickolas Faust. Hierarchical Storage and Visualization of Real-Time 3D Data [J]. SPIE Aerosense, Vol.4368A,2001.