基础地理信息地形数据库信息量度量方法研究
|
摘要
国内外的地理信息、地图信息研究主要侧重于地理信息的获取方法、传递方法、加工处理方法、存储方法,缺乏信息的描述和度量方法及信息的调控和利用方法。从地理信息信息量度量的研究现状和发展方向看,国内外研究主要侧重于图像信息容量研究和DEM信息容量研究。本文将全面探讨基础地理地形数据库的各种要素的信息量及不同比例尺的信息容量的关系,一方面深化研究的广度和深度,又可以为西部测图工程现实的需要做些贡献,是一项很有实际意义的工作。
地理信息属于空间信息。它与一般信息的区别在于它具有区域性,多维性和动态性。区域性是指地理信息的定位特征,且这种定位特征是通过公共的地理基础来体现的;所谓多维性是指在一个坐标位置上具有多个专题和属性信息;动态性是指地理信息的动态变化特征,即时序特性。无论地理信息以点、线、面等哪种方式存在,其基本的信息内容包括以下三个部分:空间分布位置信息:与实体有关的空间分布、空间度量等空间信息,也就是通常所说的几何信息;属性信息:描述实体的非空间信息特征,如居民点的行政等级,道路的技术等级等;拓扑空间关系信息:描述实体之间的空间关系信息,如相邻、相交、包含等。因此地理信息的信息量量算内容就包含了上述内容。
首先,本文从信息理论和地图的地图信息信息量量算出发,总结研究了一般信息和地理地图信息的度量理论和方法,针对数字地图时代的地理信息度量需求和基础地理信息的要素特征(点、线、面),定义了点、线、面要素的统计信息、几何信息、拓扑信息、专题信息模型和voronoi图几何信息量、最大voronoi图几何信息量,提出了几何空间均衡度、几何空间集中度的概念并进行了定义,将地图信息量的度量拓展到了地理信息的属性信息度量、注记信息度量并提出了度量方法。
其次,针对基础地理信息的核心要素居民地、道路、等高线等开展了信息量度量方法的进一步精细化研究。主要包括:在一般的几何信息量算基础上,提出了顾及要素级别的几何量算模型,它是结合了要素的空间分布特征以及要素的属性特征的度量模型核方法,通过此方法可以获得对要素的某个信息的更准确的数量认识;在单一的属性信息量算基础上提出了要素的多属性联合信息量模型,这一模型既能够对要素的属性信息合理度量同时还能发现各个属性之间的相关性,找到要素的某些分布规律性,可作为进行信息挖掘的一个重要手段;针对线状要素的几何信息量度量特点,提出了基于形态特征点的形状度量模型,反映要素的形态复杂性、自相似性的分维和信息熵相结合的几何信息度量方法。这些研究进一步拓展了地理信息的度量方法。
最后,通过基础地理信息度量模型和方法在国家基础地理信息地形数据库中的应用研究,包括不同地貌区域的信息量比较、系列比例尺地形图信息量之间的关系、以及西部测图1:50 000地形图空白区新旧地图信息量对比等应用研究和评价,验证分析了基础地理信息量计算方法的有效性和可行性。
研究结果表明针对地理信息的信息特征及其相互之间的差别开展定义和研究,定义这些特征和差别并用一定的方法进行统计或量算,然后利用经典的信息熵公式或者是它的拓展公式进行计算,可得到地理信息的信息量。同时,几何信息及其量算是地理信息量量算中最主要的内容,其他属性信息、拓扑信息、专题信息的量算与其高度相关。要素的空间信息和属性信息相结合的信息量算可以进一步精细化地理信息度量,可以从要素的属性信息的联合度量中发现有意义的信息。
Research of geographic information and map information focused on geographic information acquisition, delivery, processing and storage methods, lack of information description , quantity measurement and utilization .Most researches of current geographic information measuring focused on image information measurement and information capacity of DEM. This paper will concentrate on various elements and methods of information quantity measurement about fundamental topographic database and information capacity of the relationship among different scales of terrain maps.
Geographic information is part of the spatial information. There are three kinds of unique characteristics compared with general information and they are regional or positional, multidimensional and dynamic properties. The position is a common geographical basis to reflect the geographic information; the multidimensional character reflects multiple feature and attribute information located on the same coordinate; dynamic refers to the geographic information of variation and sequence characteristics. The basic geographic information according to the information geometry character is divided into three kinds of feature -point feature, linear feature and area feature. Regardless of the geographic information based on point, line and area, the following three parts composed its basic information characteristics: the first is spatial distribution or location information: entity-related spatial measure information, spatial distribution, and so on spatial information, which is known as a geometric information; the second is property information: describe the substance and non-spatial information characteristics, such as the administrative class of the residential area, technical level of roads, and so on; the third is topological information on the relationship between entities: the descriptions of space relationship information between entities, such as adjacency, intersection, and so on. Therefore geographic information quantity measurement will contain the above contents.
Firstly, beginning from information theory and map information measurement this paper, for the digital map of the geographic information measurement requirements and basic geographic information features (point, line and polygon), separately defines statistical information , geometric information, topological information and thematic information model for point, line and surface elements. The concepts of the voronoi diagram geometric information and largest voronoi diagram geometric information are also defined. The definitions reflect geometric space balance and geometric spatial concentration.
Secondly, for core elements of geographic information involving residents, roads and contours further research has been done to contribute to the amount of the fine measurement. This paper proposed to take into account the measurement model concerned the elements of attributes or classes. It is a combination of elements of the spatial distribution and features’attributes measurement model, which allows obtaining more accurate understanding of the information amount. The paper also proposed joint information measurement model of elements on the basis of single count of property. This model has the ability to find correlations between the various properties while measuring the elements information and helps to discover some distribution rules, and can be used as information mining. For linear feature geometric information measurement the shape measurement model including the characteristics points, entropy of geometric information and fractal measure based on morphological characteristics of the elements, which reflecting elements of complexity and self-similarity. All these studies further expand the geographic information measurement.
Lastly, through the several application experiments of above models and methods including different topographical regions comparison, series topographic information relationships, as well as 1: 50 000 new maps of Western mapping project and the old comparative map information measurement, verification of the effectiveness and feasibility of the above basic geographic information calculation method are studied.
Study results indicate that first research on the characteristics of geographical information and their commons or differences, definition of these characteristics and differences with certain method consisting of statistical measuring and calculation, and then use of the classic information entropy formula or expansion formula contributes to the amount of geographic information. The geometric information and its amount is the main content in the geographical information measurement. Other measurement of property information, topological information and thematic information are highly relevant to it. The combination of spatial information and property information can be further refined for geographic information measurement and joint attributes information can help to find extra meaningful information.
地理信息属于空间信息。它与一般信息的区别在于它具有区域性,多维性和动态性。区域性是指地理信息的定位特征,且这种定位特征是通过公共的地理基础来体现的;所谓多维性是指在一个坐标位置上具有多个专题和属性信息;动态性是指地理信息的动态变化特征,即时序特性。无论地理信息以点、线、面等哪种方式存在,其基本的信息内容包括以下三个部分:空间分布位置信息:与实体有关的空间分布、空间度量等空间信息,也就是通常所说的几何信息;属性信息:描述实体的非空间信息特征,如居民点的行政等级,道路的技术等级等;拓扑空间关系信息:描述实体之间的空间关系信息,如相邻、相交、包含等。因此地理信息的信息量量算内容就包含了上述内容。
首先,本文从信息理论和地图的地图信息信息量量算出发,总结研究了一般信息和地理地图信息的度量理论和方法,针对数字地图时代的地理信息度量需求和基础地理信息的要素特征(点、线、面),定义了点、线、面要素的统计信息、几何信息、拓扑信息、专题信息模型和voronoi图几何信息量、最大voronoi图几何信息量,提出了几何空间均衡度、几何空间集中度的概念并进行了定义,将地图信息量的度量拓展到了地理信息的属性信息度量、注记信息度量并提出了度量方法。
其次,针对基础地理信息的核心要素居民地、道路、等高线等开展了信息量度量方法的进一步精细化研究。主要包括:在一般的几何信息量算基础上,提出了顾及要素级别的几何量算模型,它是结合了要素的空间分布特征以及要素的属性特征的度量模型核方法,通过此方法可以获得对要素的某个信息的更准确的数量认识;在单一的属性信息量算基础上提出了要素的多属性联合信息量模型,这一模型既能够对要素的属性信息合理度量同时还能发现各个属性之间的相关性,找到要素的某些分布规律性,可作为进行信息挖掘的一个重要手段;针对线状要素的几何信息量度量特点,提出了基于形态特征点的形状度量模型,反映要素的形态复杂性、自相似性的分维和信息熵相结合的几何信息度量方法。这些研究进一步拓展了地理信息的度量方法。
最后,通过基础地理信息度量模型和方法在国家基础地理信息地形数据库中的应用研究,包括不同地貌区域的信息量比较、系列比例尺地形图信息量之间的关系、以及西部测图1:50 000地形图空白区新旧地图信息量对比等应用研究和评价,验证分析了基础地理信息量计算方法的有效性和可行性。
研究结果表明针对地理信息的信息特征及其相互之间的差别开展定义和研究,定义这些特征和差别并用一定的方法进行统计或量算,然后利用经典的信息熵公式或者是它的拓展公式进行计算,可得到地理信息的信息量。同时,几何信息及其量算是地理信息量量算中最主要的内容,其他属性信息、拓扑信息、专题信息的量算与其高度相关。要素的空间信息和属性信息相结合的信息量算可以进一步精细化地理信息度量,可以从要素的属性信息的联合度量中发现有意义的信息。
Research of geographic information and map information focused on geographic information acquisition, delivery, processing and storage methods, lack of information description , quantity measurement and utilization .Most researches of current geographic information measuring focused on image information measurement and information capacity of DEM. This paper will concentrate on various elements and methods of information quantity measurement about fundamental topographic database and information capacity of the relationship among different scales of terrain maps.
Geographic information is part of the spatial information. There are three kinds of unique characteristics compared with general information and they are regional or positional, multidimensional and dynamic properties. The position is a common geographical basis to reflect the geographic information; the multidimensional character reflects multiple feature and attribute information located on the same coordinate; dynamic refers to the geographic information of variation and sequence characteristics. The basic geographic information according to the information geometry character is divided into three kinds of feature -point feature, linear feature and area feature. Regardless of the geographic information based on point, line and area, the following three parts composed its basic information characteristics: the first is spatial distribution or location information: entity-related spatial measure information, spatial distribution, and so on spatial information, which is known as a geometric information; the second is property information: describe the substance and non-spatial information characteristics, such as the administrative class of the residential area, technical level of roads, and so on; the third is topological information on the relationship between entities: the descriptions of space relationship information between entities, such as adjacency, intersection, and so on. Therefore geographic information quantity measurement will contain the above contents.
Firstly, beginning from information theory and map information measurement this paper, for the digital map of the geographic information measurement requirements and basic geographic information features (point, line and polygon), separately defines statistical information , geometric information, topological information and thematic information model for point, line and surface elements. The concepts of the voronoi diagram geometric information and largest voronoi diagram geometric information are also defined. The definitions reflect geometric space balance and geometric spatial concentration.
Secondly, for core elements of geographic information involving residents, roads and contours further research has been done to contribute to the amount of the fine measurement. This paper proposed to take into account the measurement model concerned the elements of attributes or classes. It is a combination of elements of the spatial distribution and features’attributes measurement model, which allows obtaining more accurate understanding of the information amount. The paper also proposed joint information measurement model of elements on the basis of single count of property. This model has the ability to find correlations between the various properties while measuring the elements information and helps to discover some distribution rules, and can be used as information mining. For linear feature geometric information measurement the shape measurement model including the characteristics points, entropy of geometric information and fractal measure based on morphological characteristics of the elements, which reflecting elements of complexity and self-similarity. All these studies further expand the geographic information measurement.
Lastly, through the several application experiments of above models and methods including different topographical regions comparison, series topographic information relationships, as well as 1: 50 000 new maps of Western mapping project and the old comparative map information measurement, verification of the effectiveness and feasibility of the above basic geographic information calculation method are studied.
Study results indicate that first research on the characteristics of geographical information and their commons or differences, definition of these characteristics and differences with certain method consisting of statistical measuring and calculation, and then use of the classic information entropy formula or expansion formula contributes to the amount of geographic information. The geometric information and its amount is the main content in the geographical information measurement. Other measurement of property information, topological information and thematic information are highly relevant to it. The combination of spatial information and property information can be further refined for geographic information measurement and joint attributes information can help to find extra meaningful information.
引文
[1]王悦.我国信息产业对经济增长促进作用的计量分析[J].统计与决策(理论版), 2007(6):71-73.
[2]邵宇开,王洗尘,曾赛星.我国信息化发展水平与经济增长的相关性分析[J].情报科学. 2006, 24(2):172-174.
[3]徐红梅.我国信息资源水平与信息增长关系研究[D].江苏大学学位论文,2008: 6-23.
[4] Sukhov, V.I.. Information capacity of a map entropy[J] Geodesy and Aero photography, 1967,X:212-215.
[5] Neumann J·,The Topological Information Content of a Map-An Attempt at a Rehabilitation of Information Theory in Cartography [J]. Cartographica, 31 (1994): 26-34.
[6] Bjorke J.T. .Framework for entropy-based map evaluation [J].cartography and geographic information systems,1996,vol.23(2):78-95.
[7] Li , Zhilin and Huang , Peizhi , Quantitative Measures for Spatial Information of Maps[J].International Journal of Geographical Information Science,Vol. 16( 7),2002: 699-709.
[8] C. Armenakisa, F. Leduca,b, I. Cyra, F. Savopola, F. Cavayasb,A Comparative Analysis of Scanned Maps and Imagery for Mapping applications[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 57 (2003) 304- 314.
[9]卢林、吴纪桃,岛屿轮廓数据的熵信息研究[J].海洋测绘, 2005,25(5):1-3.
[10]王占宏,遥感影像信息量及质量度量模型的研究[D].武汉大学学位论文,2004年2月
[11]王占宏,杜道生,利用马尔可夫信源原理计算遥感影像信息量[J].遥感信息,2008年3月:26-30.
[12]郑学芬,遥感影像的不确定性及信息量的计算方法研究[D].山东科技大学学位论文,2006.
[13]林宗坚,张永红.遥感与地理信息系统数据的信息量及不确定性.[J].武汉大学学报?信息科学版,2006,31(7):569-571.
[14]王少一,王昭,杜清运,顾及地图要素级别的几何信息量量测方法[J].测绘科学, 2007,32(4):60-62.
[15]刘文锴、乔朝飞、陈云浩,赵仁亮,等高线图信息定量度量研究[J].武汉大学学报?信息科学版, 2008,33(2), 157-159.
[16] Frost, V.S.; Shanmugan, K.S. ,The Information Content of Synthetic Aperture Radar Images of Terrain,Aerospace and Electronic Systems, IEEE Transactions on Volume: AES-19 Issue: 5 Sept. 1983 Page(s): 768-774.
[17] Anuta, Paul E.; Bartolucci, Luis A.etc.,LANDSAT-4 MSS And Thematic Mapper Data Quality And Information Content Analysis,Geoscience and Remote Sensing, IEEE Transactions on Volume: GE-22 Issue: 3 May 1984 Page(s): 222-236.
[18] Price, John C. .Comparison of the Information Content of Data from the LANDSAT-4 Thematic Mapper And the Multispectral Scanner,Geoscience and Remote Sensing, IEEE Transactions on Volume: GE-22 Issue: 3 (1984): 272-281.
[19] Fuderer, M.,The information content of MR images,Medical Imaging[J]. IEEE Transactions on Volume: 7 Issue: 4 Dec 1988: 368-380.
[20] Lin, C.-Y. (IBM T.J. Watson Research Center); Chang, S.-F. ,Zero-error Information Hiding Capacity of Digital Images[J]. IEEE International Conference on Image Processing, Vol 3(2001) : 1007-1010.
[21] Liu, Jung-Kuan,Effects of JPEG2000 on the Information and Geometry Content of Aerial Photo Compression[J].Photogrammetric Engineering and Remote Sensing, Vol 71( 2), 2005: 157-167.
[22] LeHegaratMascle。Application of Shannon information theory to a comparison between L- and C-band SIR-C polarimetric data versus incidence angle [J].REMOTE SENSING OF ENVIRONMENT, 1997,60 (2):121-130.
[23]余建伟、朱海红、姜文亮、应申,基于熵的彩色晕渲图设色方案辅助设计[J].武汉大学学报?信息科学版, 2008,33(3):302-305.
[24]王昭、吴中恒、费立凡、李丽霞,基于几何信息熵的面状要素注记配置[J].测绘学报, 2009,38(2):83-188.
[25]田晶,郭庆胜,冯科.基于信息损失的街道渐进式选取方法[J].武汉大学学报?信息科学版, 2009,34(3):362-364.
[26]刘宏林.地图信息度量方法的研究[M].中国地图学年鉴,1992.
[27]刘宏林.利用地图信息量评价制图综合适宜程度[M].中国地图学年鉴,1992.
[28]邹建华.地图信息计量方法探讨.[J].解放军测绘学院学报,1991(4):72-77
[29]张法,地图信息量的量测和评价[J].四川测绘, 2006,29(1):21-24.
[30]何宗宜、白亭颖、滕艳敏.用信息方法确定地图的变化信息量[J].武汉测绘科技大学学报,1996,21(1):64-68.
[31]汤国安、龚健雅、陈正江等,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.
[32]杨玮莹,DEM地形信息容量与地形分析适宜性研究[D].西北大学学位论文,2002.
[33]王雷,黄土高原数字高程模型_DEM_的地形信息容量研究[D].西北大学学位论文,2005.
[34]张茜,黄土高原不同空间尺度DEM的地形信息量研究[D].西北大学学位论文,2006.
[35]陈楠、林宗坚、李成名等.1:10000及1:50000比例尺DEM信息容量的比较——以陕北韭园沟流域为例[J].测绘科学,2004,29(3):39-41.
[36]陶旸,DEM数值精度与地形形态精度分析[C].中国地理信息系统协会四次会员代表大会暨十一届年会论文集,2007.
[37] Maudood N. Khana, Mehmet T. Odmana, Hassan A. Karimib. Evaluation of Algorithms Developed for Adaptive Grid Air Quality Modeling using surface elevation data .Computers, Environment and Urban Systems, 29 (2005): 718–734.
[38]王妍,刘洪斌,武伟,宁茂歧,基于GIS的三峡库区地貌形态信息统计分析[J].测绘科学, 2006,31(2):93-95.
[39]刘慧明、许宝泉、李凤民等.祖厉河流域1∶50 000与1∶250 000比例尺DEM信息容量的比较[J].干旱区研究,2007,24(1):131-133.
[40]王红、王均,国家基本地理单元数据集的初步研究[J].测绘科学,2004, 29(3):23-24.
[41] Huayi Wu, Haijun Zhu, Yi Liu ,A Raster-based Map Information Measurement for QOS [C] . Proceedings of ISPRS'2004,Istanbul, Turkey.
[42]程昌秀、陆锋、牛方曲.栅格地图信息量计算方法的验证分析.[J].地球信息科学,2006,8(1):128-130.
[43]王郑耀、程正兴、汤少杰,基于视觉特征的尺度空间信息量度量[J].中国图象图形学报, 2005,10(7):922-927.
[44]李雯静,毋河海.地图综合中的地图目标自相似性分形衰减研究[J].测绘科学,2005,30(3):21-23.
[45]李雯静,毋河海.地图信息衰减中关键比例尺的研究[J].武汉大学学报?信息科学版,2006,31(12):1116-1119.
[46]傅祖芸编著.信息论-基础理论与应用(第二版)[M].电子工业出版社,2007.
[47]宛天巍、王浣尘,张旭,信息测度方法的综述[J].系统工程理论方法应用,2005年12月, 14(6), 481-486.
[48] Thomas M.Cover,Joy A.Thmas.Elements of Information Theory,信息论基础(原书第二版)[M].机械工业出版社,2008.1.
[49]http://en.wikipedia.org/wiki/Entropy_(information_theory)#Limitations_of_entropy_as_information_content.
[50]邬伦,刘瑜等,地理信息系统原理、方法和应用[M].科学出版社,2001年.
[51]国家测绘局,国家测绘局测绘标准化研究所,测绘标准汇编-地图制图及印刷卷[M].中国标准出版社,2004.
[52]测绘学名词(第二版),科学出版社, 2002年.
[53]葛颐龄、马晓萍、薛明.中华人民共和国国家标准GB/T 16820-1997地图学术语,国家技术监督局,1997年5月.
[54]屠德雍,"信息量悖论"及其有关问题[J].科学技术与辩证法, 2003,20(2):23-25.
[55]Shannon C E. A mathematical theory of communication[J]. The Bell System Technical Journal, 27 (1948,July, October.):379-423&623-656 .
[56]郭仁忠.空间分析(二版)[M].高等教育出版社,2001.
[57]陈军. Voronoi动态空间数据模型.[M].测绘出版社,2000年.
[58]陈军、赵仁亮、乔朝飞.基于Voronoi图的GIS空间分析研究[J].武汉大学学报信息科学版,2003,28卷特刊:32-35.
[59]舒红,概念、形式化和逻辑时空数据建模型原理初探[D].武汉测绘科技大学论文,1998年。
[60]乔朝飞、赵仁亮、陈军.基于树的等高线空间关系表达与计算[J].中国矿业大学学报,2005,34(5):571-573.
[61]刘建军、陈军、王东华等,等高线邻接关系的表达及应用研究[J].测绘学报, 33(2),2004年5月, 174-178.
[62]祝国瑞、张根寿.地图分析[M].测绘出版社,1994:58-67.
[63]张坤、肖学年、周一等,基础地理信息要素分类与代码(GB/T 13923-2006)[S].中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会,2006年5月.
[64]赵仁亮,基于Voronoi图的空间关系计算研究[D].中南大学学位论文,2002:13-17.
[65] Silverman, B.W. Density Estimation for Statistics and Data Analysis. New York: Chapman and Hall, 1986.
[66] http://downloads.esri.com/support/whitepapers/ao_/mapgen.pdf , Technical paper, ESRI, "Automation of Map Generalization: The Cutting-Edge Technology," 1996.
[67]毋河海.地图信息的分形描述[J].测绘通报,2001( 2):24.
[68]安巧绒.基于信息维数的地表分形特征研究——以黄土高原为例[D].西北大学学位论文,2008:32-35.
[69]柏春广,蔡先华.南京市交通网络的分形特征[J].地理研究,2008,27(6):1419-1425.
[70]曹颖.基于DEM的地貌分形特征研究——以陕北黄土高原部分样区为例[D].西北大学学位论文,2007:32-51.
[71]陈楠、林宗坚、李成名等.基于信息论的不同比例尺DEM地形信息比较分析[J].遥感信息,2004(3):5-8.
[72]陈彦光、刘继生.城市土地利用结构和形态的定量描述:从信息熵到分数维.[J].地理研究,2001,20(2):146-151.
[73]梁虹,卢娟.喀斯特流域水系分形、熵及其地貌意义[J].地理科学,1997,17(4):310-314.
[74]朱永清、李占斌、崔灵周等,基于GIS地貌形态特征分形信息维数与等高距关系研究[J].水土保持学报,2005, 19(1):105-113.
[75] Paul S.Addison ,Fractals and chaos: an illustrated course[M].Institute of Physics Publishing,1997:36-38.
[76]王丽琴,线状河流的扩展分维及其分析方法[D].南京师范大学学位论文,2008: 9-26.
[77]中华人民共和国国家测绘局,中国数字地图(1:100万,国际版)数据字典[M].中国地图出版社,1998.
[78] http://www.sbsm.gov.cn/article//jcch/jcdlxxxt.
[79] Chen Jun, Qiao Chaofei, Zhao Renliang. A Voronoi Interior Adjacency-Based Approach for Generating a Contour Tree [ J]. Computers and Geosciences,30( 2004) : 355-367.
[80] Gold C M. The Meaning of"Neighbour". [J].Lecture Notes in Computing Science ,39(1992) :220～235.
[81] Douglas, David H. and Thomas K. Peucker. Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or Its Caricature, Canadian Cartographer, 10, No. 2 ,December 1973.
[82]李成名.空间关系描述的Voronoi原理与方法[M].西安地图出版社,2000年.
[83]孙博玲,分形维数(Fractal dimension)及其测量方法[J].东北林业大学学报, 2004,32(3):116-119.
[84]李江,郭庆胜.基于信息熵的城市用地结构动态演变分析[J].长江流域资源与环境,2002,11(5):393-396.
[85]刘继生、陈彦光,城镇体系等级结构的分形维数及其测算方法[J].地理研究, 17(1),1998年3月, 82-88.
[86]王昭、费立凡,基于语法层的地图综合信息量原则[J].测绘科学,2007, 32(6): 21-23.
[87]王桥、吴纪桃,制图综合方根规律模型的分形扩展[J].测绘学报, 1996,25(2): 104-115.
[88] Sandro Bimonte,Anne Tchounikine,Maryvonne Miquel.Spatial OLAP:Open Issues and a Web Based Prototype[C].10th AGILE International Conference on Geographic Information Science, 2007:1-11.
[89]常宏宇.信息量和熵的关系[J].数学的实践与认识,2005,35(5):137-140.
[90]钟义信.信息科学原理[M].北京邮电大学出版社,2002.
[91]于江佩,基于ARCGIS的等高线与河流的自动综合[D].武汉测绘科技大学论文,2005.
[92]袁志发、静芋周,多元统计分析[M].科学出版社,2002: 257-287.
[93]张济忠,分形[M].北京:清华大学出版社,2001:65.
[94]王家耀,地图学与地理信息工程研究[M].科学出版社,2005:161-175.
[95]张宏才、汤国安,基于GIS的河网分形研究[J].西北大学学报(自然科学版),2006, 36(4):659-661.
[96]胡志勇、何建邦、柯正谊.地理空间意像模式的Voronoi模型[J].地理科学,2001,21(2):177-182.
[97]刘海容.形状的曲率表示与分解[D].华中科技大学学位论文,2009:11-26.参考书目
[98] Bin Jiang, Editorial: Some Thoughts on Geospatial Analysis and Modeling[J].Computers, Environment and Urban Systems,31 (2007):477–480.
[99] Carol J. Bartels , Arthur U.C.J. van Beurden,Using Geographic and Cartographic Principles for Environmental Assessment and Risk Mapping[J].Journal of Hazardous Materials, 61(1998):115–124.
[100] D.A. Holland, D.S. Boyd, P. Marshall,Updating Topographic Mapping in Great Britain Using imagery from High-resolution Satellite sensors. ISPRS Journal of Photogrammetry & Remote Sensing, 60 (2006): 212–223.
[101] Guo Ming-Ming,Entropy-based Complexity Measure for Aspect-Oriented Program,2007,Vol.43(5):509-518.
[102] Guo, D.Z.,Fan, A.M. ,Quality evaluation of spatial data in GIS based on information theory,Journal of China University of Mining & Technology, Vol. 30( 3), 2001:221-224 .
[103] Harry T. Uitermark a, Peter J.M. van Oosterom b, Nicolaas J.I. Mars c,Ontology-based integration of topographic data sets[J].International Journal of Applied Earth Observation and Geoinformation,7 (2005): 97–106.
[104] Jason A. Dykes,,Exploring Spatial Data Representation With Dynamic Graphics [J].Computers & Geosciences , Vol. 23, No. 4,1997: 345-370.
[105] Kronenfeld, Barry Joel,The Tradeoff Between Information Content And Cognitive Simplicity In Graded Area-Class Maps: A Case Study In Vegetation Mapping, Ph.D., State University Of New York At Buffalo, 2004: 162 .
[106] Liu, HY; Wang, X; Xiao, JH,Analog/digital Map Conversion and Cartographic Information Content Changes [C].15th International Conference on Geoinformatics, Nanjing, CHINA, 2007:25-27.
[107] M. Duckham,K. Mason,J. Stell,M. Worboys, A formal approach to imperfection in geographic information.Computers[J].Environment and Urban Systems, 25 (2001): 89-103.
[108] M. Weis,S. Muller, C.-E. Liedtke, M. Pahl, A Framework for GIS and Imagery Data Fusion in Support of Cartographic Updating ,[J].Information Fusion, 6 (2005) :311–317.
[109] Markus Gerke, Matthias Butenuth, Christian Heipke, Felicitas Willrich.Graph-supported Verification of Road Databases. [J].ISPRS Journal of Photogrammetry & Remote Sensing, 58 (2004): 152– 165.
[110] Papalazarou, C; Snoeren, RM; Willems, FMJ.Towards a Full-reference, Information-theoretic Quality Assessment Method for X-ray images[C].Medical Imaging 2008 Conference, FEB 17-19, 2008, San Diego, CA.
[111] Peggy Agouris,Anthony Stefanidis, and James D. Carswell,Sketch-Based Image Queries in Topographic Databases,[J].Journal of Visual Communication and Image Representation, 10 (1999): 113–129.
[112] Petkevich, Nl; Kurashov, Ag,The Information Capacity Of Synthesized Aperture Radars In Mapping Problems,[J].Telecommunications and Radio Engineering ,44 (11),1989:108-113 .
[113] Ron Store, Jukk Jokimki .A GIS-based Multi-scale Approach to Habitat Suitability Modeling, [J].Ecological Modeling,169 (2003) :1-15.
[114] S. Jodouin. Spatial Database Updating Using Active Contours for Multispectral Images: Application with Landsat 7,[J].ISPRS Journal of Photogrammetry & Remote Sensing, 57 (2003) :346– 355.
[115] Seth E. Spielman a, Jean-Claude Thill.Social Area Analysis, Data Mining, and GIS[J].Computers, Environment and Urban Systems 32 (2008) :110–122.
[116] Tomislav Heng.Finding the right pixel size [J].Computers & Geosciences,2006, 32: 1283–1298
[117]郭庆胜,毋河海,李沛川.等高线的空间关系规则和渐进式图形简化方法[J].武汉大学学报,2000,25(1):31-34.
[118]何丽丽.基于不同比例尺和分辨率DEM的数字地形分析[D].西南大学学位论文,2007:25-46.
[119]何宗宜.地图数据处理模型的原理与算法[M].武汉大学出版社,2004.
[120]何宗宜.用信息论方法确定地图分级[J].四川测绘,1995,18(l),:18-22.
[121]李艺.信息与信息量.[J].自然辩证法研究,1998,14(12):20-22.
[122]李公宜.汉字最高阶条件熵及其实验测定[J].上海交通大学学报,1994,28(2):113-120.
[123]刘继生、陈彦,交通网络空间结构的分形维数及其测算方法探讨[J].地理学报,1999年9月, 54(5):471-477.
[124]刘仁维、秦海燕、蒋庆华等,媒体(报纸)信息量分析[J].兰州教育学院学报,2002年4), 53-55.
[125]刘善存、邱菀华,熵用于信息评价的进一步探讨[J].系统工程理论与实践, 11),1999年11月, 8-12.
[126]刘怡,从哲学的角度看信息的本质[J].图书与情报,2008:80-84.,
[127]秦耀辰、刘凯,分形理论在地理学中的应用研究进展[J].地理科学进展, ,2003,22(4):426-434.
[128]阮沈勇、黄润秋,基于GIS的信息量法模型在地质灾害危险性区划中的应用[J].成都理工学院学报, 28卷,2001年1月, 89-92.
[129]史文中,空间数据与空间分析不确定性原理[M].科学出版社, 2005年6月
[130]帅方敏,王新生,朱超平等,中国省级行政区边界形状的GIS分析[J].地球信息科学, 10(1),2008年2月, 34-37.
[131]宋国杰,唐世渭,杨冬青,王腾蛟,基于最大熵原理的空间特征选择方法[J].软件学报, 2003,14(9): 1544-1546.
[132]宋华岭、冯述虎、李金克,基于信息量度量的企业管理复杂性评价方法-神东煤炭公司管理复杂性评价[J].数学的实践和认识, 2004,34(12):46-51.
[133]孙庆先、李茂堂、路京选等,地理空间数据的尺度问题及其研究进展[J].地理与地理信息科学,2007, 23(4):53-56.
[134]陶旸、汤国安、王春等.DEM子集划分对地形信息量计算的影响研究[C].中国测绘学会九届四次理事会暨2008年学术年会论文集,2008: 48-54.
[135]王华、晏磊、钱旭、朱明,基于地形熵和地形差异熵的综合地形匹配算法[J].计算机技术与发展, 2007,17(9):61-62.
[136]王平、卢珊、杨桄、刘湘南,地理图形信息分析方法及其在土地利用研究中的应用[J].东北师大学报自然科学版, 2002,34(1): 93-99.
[137]王桥,胡毓拒,基于分形分析的自动化制图综合研究[J].测绘学报,1995, 24(3):211-216.
[138]王涛,地貌信息提取中的结构化问题研究[D].武汉大学学位论文,2005:79-83.
[139]王占全,基于地理信息系统空间数据挖掘若干关键技术的研究[D].浙江大学学位论文,2005: 6-17.
[140]魏文展、钟业勋、黄仁涛、彭月英,地图符号视觉变量数学定义的研究[J].武汉大学学报?信息科学版, 2002,27(5):11-513.
[141]巫兆聪,分形分析中的无标度区确定问题[J].测绘学报, 2002,31(3): 240-244.
[142]吴宝玉,姜兴起,信息量统计学的形成[J].大连海事大学学报,1995, 21(2):105-109.
[143]吴立新,史文中,地理信息系统原理与算法[M].科学出版社,2003.
[144]吴秀芹,张洪岩等,ARCGIS 9地理信息系统应用与实践[M].清华大学出版社,2007.
[145]徐峥,基于ARCG15的居民地与道路的自动综合[D].武汉测绘科技大学论文,2005.
[146]许丽敏、薛安,基于Delaunay三角网与Voronoi图联合提取等高线骨架的地形重建算法研究[J].北京大学学报(自然科学版)网络版,2009(1): 43-48.
[147]许志海、张昭云,分形理论在交通网络分布形态研究中的应用[J].测绘工程, 2006,15(1):27-30.
[148]张宏敏,数学在地图分析中的运用[J].测绘科学,2006, 31(6):58-59.
[148]张克权,郭仁忠,专题制图数学模型[M].测绘出版社,1991: 42-51.
[150]张良,蔡生,信息量的度量及应用[J].沈阳大学学报, 2004,16(2):89-91.
[151]钟业勋,地图易读性的度量研究[J].武汉测绘科技大学学报,1994, 19(4):346-351.
[152]钟业勋,胡毓钜,吴剑辉,地图要素的分类定义及其度量化研究[J].测绘工程,1999, 8(2):11-15.
[153]钟业勋、魏文展,地图符号若干特征的数字化表达研究[J].测绘科学,2004, 29(4):23-25.
[154]钟业勋、魏文展,李占元,基本地貌形态数学定义的研究[J].测绘科学, 2002,27(3):16-18.
[155]周成虎、张健挺,基于信息熵的地学空间数据挖掘模型[J].中国图象图形学报, 1999,4(A版) ( 11):946-951.
[156]朱长青,史文中,空间分析建模与原理[M].科学出版社, 2006.
[157]祝国瑞、王建华.现代地图分析有关问题的探讨[J].测绘学报,1995,24(1):77-79.
[2]邵宇开,王洗尘,曾赛星.我国信息化发展水平与经济增长的相关性分析[J].情报科学. 2006, 24(2):172-174.
[3]徐红梅.我国信息资源水平与信息增长关系研究[D].江苏大学学位论文,2008: 6-23.
[4] Sukhov, V.I.. Information capacity of a map entropy[J] Geodesy and Aero photography, 1967,X:212-215.
[5] Neumann J·,The Topological Information Content of a Map-An Attempt at a Rehabilitation of Information Theory in Cartography [J]. Cartographica, 31 (1994): 26-34.
[6] Bjorke J.T. .Framework for entropy-based map evaluation [J].cartography and geographic information systems,1996,vol.23(2):78-95.
[7] Li , Zhilin and Huang , Peizhi , Quantitative Measures for Spatial Information of Maps[J].International Journal of Geographical Information Science,Vol. 16( 7),2002: 699-709.
[8] C. Armenakisa, F. Leduca,b, I. Cyra, F. Savopola, F. Cavayasb,A Comparative Analysis of Scanned Maps and Imagery for Mapping applications[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 57 (2003) 304- 314.
[9]卢林、吴纪桃,岛屿轮廓数据的熵信息研究[J].海洋测绘, 2005,25(5):1-3.
[10]王占宏,遥感影像信息量及质量度量模型的研究[D].武汉大学学位论文,2004年2月
[11]王占宏,杜道生,利用马尔可夫信源原理计算遥感影像信息量[J].遥感信息,2008年3月:26-30.
[12]郑学芬,遥感影像的不确定性及信息量的计算方法研究[D].山东科技大学学位论文,2006.
[13]林宗坚,张永红.遥感与地理信息系统数据的信息量及不确定性.[J].武汉大学学报?信息科学版,2006,31(7):569-571.
[14]王少一,王昭,杜清运,顾及地图要素级别的几何信息量量测方法[J].测绘科学, 2007,32(4):60-62.
[15]刘文锴、乔朝飞、陈云浩,赵仁亮,等高线图信息定量度量研究[J].武汉大学学报?信息科学版, 2008,33(2), 157-159.
[16] Frost, V.S.; Shanmugan, K.S. ,The Information Content of Synthetic Aperture Radar Images of Terrain,Aerospace and Electronic Systems, IEEE Transactions on Volume: AES-19 Issue: 5 Sept. 1983 Page(s): 768-774.
[17] Anuta, Paul E.; Bartolucci, Luis A.etc.,LANDSAT-4 MSS And Thematic Mapper Data Quality And Information Content Analysis,Geoscience and Remote Sensing, IEEE Transactions on Volume: GE-22 Issue: 3 May 1984 Page(s): 222-236.
[18] Price, John C. .Comparison of the Information Content of Data from the LANDSAT-4 Thematic Mapper And the Multispectral Scanner,Geoscience and Remote Sensing, IEEE Transactions on Volume: GE-22 Issue: 3 (1984): 272-281.
[19] Fuderer, M.,The information content of MR images,Medical Imaging[J]. IEEE Transactions on Volume: 7 Issue: 4 Dec 1988: 368-380.
[20] Lin, C.-Y. (IBM T.J. Watson Research Center); Chang, S.-F. ,Zero-error Information Hiding Capacity of Digital Images[J]. IEEE International Conference on Image Processing, Vol 3(2001) : 1007-1010.
[21] Liu, Jung-Kuan,Effects of JPEG2000 on the Information and Geometry Content of Aerial Photo Compression[J].Photogrammetric Engineering and Remote Sensing, Vol 71( 2), 2005: 157-167.
[22] LeHegaratMascle。Application of Shannon information theory to a comparison between L- and C-band SIR-C polarimetric data versus incidence angle [J].REMOTE SENSING OF ENVIRONMENT, 1997,60 (2):121-130.
[23]余建伟、朱海红、姜文亮、应申,基于熵的彩色晕渲图设色方案辅助设计[J].武汉大学学报?信息科学版, 2008,33(3):302-305.
[24]王昭、吴中恒、费立凡、李丽霞,基于几何信息熵的面状要素注记配置[J].测绘学报, 2009,38(2):83-188.
[25]田晶,郭庆胜,冯科.基于信息损失的街道渐进式选取方法[J].武汉大学学报?信息科学版, 2009,34(3):362-364.
[26]刘宏林.地图信息度量方法的研究[M].中国地图学年鉴,1992.
[27]刘宏林.利用地图信息量评价制图综合适宜程度[M].中国地图学年鉴,1992.
[28]邹建华.地图信息计量方法探讨.[J].解放军测绘学院学报,1991(4):72-77
[29]张法,地图信息量的量测和评价[J].四川测绘, 2006,29(1):21-24.
[30]何宗宜、白亭颖、滕艳敏.用信息方法确定地图的变化信息量[J].武汉测绘科技大学学报,1996,21(1):64-68.
[31]汤国安、龚健雅、陈正江等,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.
[32]杨玮莹,DEM地形信息容量与地形分析适宜性研究[D].西北大学学位论文,2002.
[33]王雷,黄土高原数字高程模型_DEM_的地形信息容量研究[D].西北大学学位论文,2005.
[34]张茜,黄土高原不同空间尺度DEM的地形信息量研究[D].西北大学学位论文,2006.
[35]陈楠、林宗坚、李成名等.1:10000及1:50000比例尺DEM信息容量的比较——以陕北韭园沟流域为例[J].测绘科学,2004,29(3):39-41.
[36]陶旸,DEM数值精度与地形形态精度分析[C].中国地理信息系统协会四次会员代表大会暨十一届年会论文集,2007.
[37] Maudood N. Khana, Mehmet T. Odmana, Hassan A. Karimib. Evaluation of Algorithms Developed for Adaptive Grid Air Quality Modeling using surface elevation data .Computers, Environment and Urban Systems, 29 (2005): 718–734.
[38]王妍,刘洪斌,武伟,宁茂歧,基于GIS的三峡库区地貌形态信息统计分析[J].测绘科学, 2006,31(2):93-95.
[39]刘慧明、许宝泉、李凤民等.祖厉河流域1∶50 000与1∶250 000比例尺DEM信息容量的比较[J].干旱区研究,2007,24(1):131-133.
[40]王红、王均,国家基本地理单元数据集的初步研究[J].测绘科学,2004, 29(3):23-24.
[41] Huayi Wu, Haijun Zhu, Yi Liu ,A Raster-based Map Information Measurement for QOS [C] . Proceedings of ISPRS'2004,Istanbul, Turkey.
[42]程昌秀、陆锋、牛方曲.栅格地图信息量计算方法的验证分析.[J].地球信息科学,2006,8(1):128-130.
[43]王郑耀、程正兴、汤少杰,基于视觉特征的尺度空间信息量度量[J].中国图象图形学报, 2005,10(7):922-927.
[44]李雯静,毋河海.地图综合中的地图目标自相似性分形衰减研究[J].测绘科学,2005,30(3):21-23.
[45]李雯静,毋河海.地图信息衰减中关键比例尺的研究[J].武汉大学学报?信息科学版,2006,31(12):1116-1119.
[46]傅祖芸编著.信息论-基础理论与应用(第二版)[M].电子工业出版社,2007.
[47]宛天巍、王浣尘,张旭,信息测度方法的综述[J].系统工程理论方法应用,2005年12月, 14(6), 481-486.
[48] Thomas M.Cover,Joy A.Thmas.Elements of Information Theory,信息论基础(原书第二版)[M].机械工业出版社,2008.1.
[49]http://en.wikipedia.org/wiki/Entropy_(information_theory)#Limitations_of_entropy_as_information_content.
[50]邬伦,刘瑜等,地理信息系统原理、方法和应用[M].科学出版社,2001年.
[51]国家测绘局,国家测绘局测绘标准化研究所,测绘标准汇编-地图制图及印刷卷[M].中国标准出版社,2004.
[52]测绘学名词(第二版),科学出版社, 2002年.
[53]葛颐龄、马晓萍、薛明.中华人民共和国国家标准GB/T 16820-1997地图学术语,国家技术监督局,1997年5月.
[54]屠德雍,"信息量悖论"及其有关问题[J].科学技术与辩证法, 2003,20(2):23-25.
[55]Shannon C E. A mathematical theory of communication[J]. The Bell System Technical Journal, 27 (1948,July, October.):379-423&623-656 .
[56]郭仁忠.空间分析(二版)[M].高等教育出版社,2001.
[57]陈军. Voronoi动态空间数据模型.[M].测绘出版社,2000年.
[58]陈军、赵仁亮、乔朝飞.基于Voronoi图的GIS空间分析研究[J].武汉大学学报信息科学版,2003,28卷特刊:32-35.
[59]舒红,概念、形式化和逻辑时空数据建模型原理初探[D].武汉测绘科技大学论文,1998年。
[60]乔朝飞、赵仁亮、陈军.基于树的等高线空间关系表达与计算[J].中国矿业大学学报,2005,34(5):571-573.
[61]刘建军、陈军、王东华等,等高线邻接关系的表达及应用研究[J].测绘学报, 33(2),2004年5月, 174-178.
[62]祝国瑞、张根寿.地图分析[M].测绘出版社,1994:58-67.
[63]张坤、肖学年、周一等,基础地理信息要素分类与代码(GB/T 13923-2006)[S].中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会,2006年5月.
[64]赵仁亮,基于Voronoi图的空间关系计算研究[D].中南大学学位论文,2002:13-17.
[65] Silverman, B.W. Density Estimation for Statistics and Data Analysis. New York: Chapman and Hall, 1986.
[66] http://downloads.esri.com/support/whitepapers/ao_/mapgen.pdf , Technical paper, ESRI, "Automation of Map Generalization: The Cutting-Edge Technology," 1996.
[67]毋河海.地图信息的分形描述[J].测绘通报,2001( 2):24.
[68]安巧绒.基于信息维数的地表分形特征研究——以黄土高原为例[D].西北大学学位论文,2008:32-35.
[69]柏春广,蔡先华.南京市交通网络的分形特征[J].地理研究,2008,27(6):1419-1425.
[70]曹颖.基于DEM的地貌分形特征研究——以陕北黄土高原部分样区为例[D].西北大学学位论文,2007:32-51.
[71]陈楠、林宗坚、李成名等.基于信息论的不同比例尺DEM地形信息比较分析[J].遥感信息,2004(3):5-8.
[72]陈彦光、刘继生.城市土地利用结构和形态的定量描述:从信息熵到分数维.[J].地理研究,2001,20(2):146-151.
[73]梁虹,卢娟.喀斯特流域水系分形、熵及其地貌意义[J].地理科学,1997,17(4):310-314.
[74]朱永清、李占斌、崔灵周等,基于GIS地貌形态特征分形信息维数与等高距关系研究[J].水土保持学报,2005, 19(1):105-113.
[75] Paul S.Addison ,Fractals and chaos: an illustrated course[M].Institute of Physics Publishing,1997:36-38.
[76]王丽琴,线状河流的扩展分维及其分析方法[D].南京师范大学学位论文,2008: 9-26.
[77]中华人民共和国国家测绘局,中国数字地图(1:100万,国际版)数据字典[M].中国地图出版社,1998.
[78] http://www.sbsm.gov.cn/article//jcch/jcdlxxxt.
[79] Chen Jun, Qiao Chaofei, Zhao Renliang. A Voronoi Interior Adjacency-Based Approach for Generating a Contour Tree [ J]. Computers and Geosciences,30( 2004) : 355-367.
[80] Gold C M. The Meaning of"Neighbour". [J].Lecture Notes in Computing Science ,39(1992) :220～235.
[81] Douglas, David H. and Thomas K. Peucker. Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or Its Caricature, Canadian Cartographer, 10, No. 2 ,December 1973.
[82]李成名.空间关系描述的Voronoi原理与方法[M].西安地图出版社,2000年.
[83]孙博玲,分形维数(Fractal dimension)及其测量方法[J].东北林业大学学报, 2004,32(3):116-119.
[84]李江,郭庆胜.基于信息熵的城市用地结构动态演变分析[J].长江流域资源与环境,2002,11(5):393-396.
[85]刘继生、陈彦光,城镇体系等级结构的分形维数及其测算方法[J].地理研究, 17(1),1998年3月, 82-88.
[86]王昭、费立凡,基于语法层的地图综合信息量原则[J].测绘科学,2007, 32(6): 21-23.
[87]王桥、吴纪桃,制图综合方根规律模型的分形扩展[J].测绘学报, 1996,25(2): 104-115.
[88] Sandro Bimonte,Anne Tchounikine,Maryvonne Miquel.Spatial OLAP:Open Issues and a Web Based Prototype[C].10th AGILE International Conference on Geographic Information Science, 2007:1-11.
[89]常宏宇.信息量和熵的关系[J].数学的实践与认识,2005,35(5):137-140.
[90]钟义信.信息科学原理[M].北京邮电大学出版社,2002.
[91]于江佩,基于ARCGIS的等高线与河流的自动综合[D].武汉测绘科技大学论文,2005.
[92]袁志发、静芋周,多元统计分析[M].科学出版社,2002: 257-287.
[93]张济忠,分形[M].北京:清华大学出版社,2001:65.
[94]王家耀,地图学与地理信息工程研究[M].科学出版社,2005:161-175.
[95]张宏才、汤国安,基于GIS的河网分形研究[J].西北大学学报(自然科学版),2006, 36(4):659-661.
[96]胡志勇、何建邦、柯正谊.地理空间意像模式的Voronoi模型[J].地理科学,2001,21(2):177-182.
[97]刘海容.形状的曲率表示与分解[D].华中科技大学学位论文,2009:11-26.参考书目
[98] Bin Jiang, Editorial: Some Thoughts on Geospatial Analysis and Modeling[J].Computers, Environment and Urban Systems,31 (2007):477–480.
[99] Carol J. Bartels , Arthur U.C.J. van Beurden,Using Geographic and Cartographic Principles for Environmental Assessment and Risk Mapping[J].Journal of Hazardous Materials, 61(1998):115–124.
[100] D.A. Holland, D.S. Boyd, P. Marshall,Updating Topographic Mapping in Great Britain Using imagery from High-resolution Satellite sensors. ISPRS Journal of Photogrammetry & Remote Sensing, 60 (2006): 212–223.
[101] Guo Ming-Ming,Entropy-based Complexity Measure for Aspect-Oriented Program,2007,Vol.43(5):509-518.
[102] Guo, D.Z.,Fan, A.M. ,Quality evaluation of spatial data in GIS based on information theory,Journal of China University of Mining & Technology, Vol. 30( 3), 2001:221-224 .
[103] Harry T. Uitermark a, Peter J.M. van Oosterom b, Nicolaas J.I. Mars c,Ontology-based integration of topographic data sets[J].International Journal of Applied Earth Observation and Geoinformation,7 (2005): 97–106.
[104] Jason A. Dykes,,Exploring Spatial Data Representation With Dynamic Graphics [J].Computers & Geosciences , Vol. 23, No. 4,1997: 345-370.
[105] Kronenfeld, Barry Joel,The Tradeoff Between Information Content And Cognitive Simplicity In Graded Area-Class Maps: A Case Study In Vegetation Mapping, Ph.D., State University Of New York At Buffalo, 2004: 162 .
[106] Liu, HY; Wang, X; Xiao, JH,Analog/digital Map Conversion and Cartographic Information Content Changes [C].15th International Conference on Geoinformatics, Nanjing, CHINA, 2007:25-27.
[107] M. Duckham,K. Mason,J. Stell,M. Worboys, A formal approach to imperfection in geographic information.Computers[J].Environment and Urban Systems, 25 (2001): 89-103.
[108] M. Weis,S. Muller, C.-E. Liedtke, M. Pahl, A Framework for GIS and Imagery Data Fusion in Support of Cartographic Updating ,[J].Information Fusion, 6 (2005) :311–317.
[109] Markus Gerke, Matthias Butenuth, Christian Heipke, Felicitas Willrich.Graph-supported Verification of Road Databases. [J].ISPRS Journal of Photogrammetry & Remote Sensing, 58 (2004): 152– 165.
[110] Papalazarou, C; Snoeren, RM; Willems, FMJ.Towards a Full-reference, Information-theoretic Quality Assessment Method for X-ray images[C].Medical Imaging 2008 Conference, FEB 17-19, 2008, San Diego, CA.
[111] Peggy Agouris,Anthony Stefanidis, and James D. Carswell,Sketch-Based Image Queries in Topographic Databases,[J].Journal of Visual Communication and Image Representation, 10 (1999): 113–129.
[112] Petkevich, Nl; Kurashov, Ag,The Information Capacity Of Synthesized Aperture Radars In Mapping Problems,[J].Telecommunications and Radio Engineering ,44 (11),1989:108-113 .
[113] Ron Store, Jukk Jokimki .A GIS-based Multi-scale Approach to Habitat Suitability Modeling, [J].Ecological Modeling,169 (2003) :1-15.
[114] S. Jodouin. Spatial Database Updating Using Active Contours for Multispectral Images: Application with Landsat 7,[J].ISPRS Journal of Photogrammetry & Remote Sensing, 57 (2003) :346– 355.
[115] Seth E. Spielman a, Jean-Claude Thill.Social Area Analysis, Data Mining, and GIS[J].Computers, Environment and Urban Systems 32 (2008) :110–122.
[116] Tomislav Heng.Finding the right pixel size [J].Computers & Geosciences,2006, 32: 1283–1298
[117]郭庆胜,毋河海,李沛川.等高线的空间关系规则和渐进式图形简化方法[J].武汉大学学报,2000,25(1):31-34.
[118]何丽丽.基于不同比例尺和分辨率DEM的数字地形分析[D].西南大学学位论文,2007:25-46.
[119]何宗宜.地图数据处理模型的原理与算法[M].武汉大学出版社,2004.
[120]何宗宜.用信息论方法确定地图分级[J].四川测绘,1995,18(l),:18-22.
[121]李艺.信息与信息量.[J].自然辩证法研究,1998,14(12):20-22.
[122]李公宜.汉字最高阶条件熵及其实验测定[J].上海交通大学学报,1994,28(2):113-120.
[123]刘继生、陈彦,交通网络空间结构的分形维数及其测算方法探讨[J].地理学报,1999年9月, 54(5):471-477.
[124]刘仁维、秦海燕、蒋庆华等,媒体(报纸)信息量分析[J].兰州教育学院学报,2002年4), 53-55.
[125]刘善存、邱菀华,熵用于信息评价的进一步探讨[J].系统工程理论与实践, 11),1999年11月, 8-12.
[126]刘怡,从哲学的角度看信息的本质[J].图书与情报,2008:80-84.,
[127]秦耀辰、刘凯,分形理论在地理学中的应用研究进展[J].地理科学进展, ,2003,22(4):426-434.
[128]阮沈勇、黄润秋,基于GIS的信息量法模型在地质灾害危险性区划中的应用[J].成都理工学院学报, 28卷,2001年1月, 89-92.
[129]史文中,空间数据与空间分析不确定性原理[M].科学出版社, 2005年6月
[130]帅方敏,王新生,朱超平等,中国省级行政区边界形状的GIS分析[J].地球信息科学, 10(1),2008年2月, 34-37.
[131]宋国杰,唐世渭,杨冬青,王腾蛟,基于最大熵原理的空间特征选择方法[J].软件学报, 2003,14(9): 1544-1546.
[132]宋华岭、冯述虎、李金克,基于信息量度量的企业管理复杂性评价方法-神东煤炭公司管理复杂性评价[J].数学的实践和认识, 2004,34(12):46-51.
[133]孙庆先、李茂堂、路京选等,地理空间数据的尺度问题及其研究进展[J].地理与地理信息科学,2007, 23(4):53-56.
[134]陶旸、汤国安、王春等.DEM子集划分对地形信息量计算的影响研究[C].中国测绘学会九届四次理事会暨2008年学术年会论文集,2008: 48-54.
[135]王华、晏磊、钱旭、朱明,基于地形熵和地形差异熵的综合地形匹配算法[J].计算机技术与发展, 2007,17(9):61-62.
[136]王平、卢珊、杨桄、刘湘南,地理图形信息分析方法及其在土地利用研究中的应用[J].东北师大学报自然科学版, 2002,34(1): 93-99.
[137]王桥,胡毓拒,基于分形分析的自动化制图综合研究[J].测绘学报,1995, 24(3):211-216.
[138]王涛,地貌信息提取中的结构化问题研究[D].武汉大学学位论文,2005:79-83.
[139]王占全,基于地理信息系统空间数据挖掘若干关键技术的研究[D].浙江大学学位论文,2005: 6-17.
[140]魏文展、钟业勋、黄仁涛、彭月英,地图符号视觉变量数学定义的研究[J].武汉大学学报?信息科学版, 2002,27(5):11-513.
[141]巫兆聪,分形分析中的无标度区确定问题[J].测绘学报, 2002,31(3): 240-244.
[142]吴宝玉,姜兴起,信息量统计学的形成[J].大连海事大学学报,1995, 21(2):105-109.
[143]吴立新,史文中,地理信息系统原理与算法[M].科学出版社,2003.
[144]吴秀芹,张洪岩等,ARCGIS 9地理信息系统应用与实践[M].清华大学出版社,2007.
[145]徐峥,基于ARCG15的居民地与道路的自动综合[D].武汉测绘科技大学论文,2005.
[146]许丽敏、薛安,基于Delaunay三角网与Voronoi图联合提取等高线骨架的地形重建算法研究[J].北京大学学报(自然科学版)网络版,2009(1): 43-48.
[147]许志海、张昭云,分形理论在交通网络分布形态研究中的应用[J].测绘工程, 2006,15(1):27-30.
[148]张宏敏,数学在地图分析中的运用[J].测绘科学,2006, 31(6):58-59.
[148]张克权,郭仁忠,专题制图数学模型[M].测绘出版社,1991: 42-51.
[150]张良,蔡生,信息量的度量及应用[J].沈阳大学学报, 2004,16(2):89-91.
[151]钟业勋,地图易读性的度量研究[J].武汉测绘科技大学学报,1994, 19(4):346-351.
[152]钟业勋,胡毓钜,吴剑辉,地图要素的分类定义及其度量化研究[J].测绘工程,1999, 8(2):11-15.
[153]钟业勋、魏文展,地图符号若干特征的数字化表达研究[J].测绘科学,2004, 29(4):23-25.
[154]钟业勋、魏文展,李占元,基本地貌形态数学定义的研究[J].测绘科学, 2002,27(3):16-18.
[155]周成虎、张健挺,基于信息熵的地学空间数据挖掘模型[J].中国图象图形学报, 1999,4(A版) ( 11):946-951.
[156]朱长青,史文中,空间分析建模与原理[M].科学出版社, 2006.
[157]祝国瑞、王建华.现代地图分析有关问题的探讨[J].测绘学报,1995,24(1):77-79.