地球信息科学理论与方法

面要素空间信息量的度量方法研究

展开
  • 中南大学地球科学与信息物理学院, 长沙 410083
刘慧敏(1977-),女,湖南长沙人,博士,讲师,研究方向为地理空间信息度量与应用。E-mail:lhmgis@163.com

收稿日期: 2012-11-01

  修回日期: 2012-12-01

  网络出版日期: 2012-12-25

基金资助

国家自然科学基金项目(41171351);中央高校基本科研业务费青年助推项目;江西省数字国土重点实验室2012年度开放基金资助项目(DLLJ201204)。

An Approach to Measuring the Spatial Information Content of an Area Feature

Expand
  • School of Geosciences and Info-Physics, Central South University, Changsha 410083, China

Received date: 2012-11-01

  Revised date: 2012-12-01

  Online published: 2012-12-25

摘要

地图是空间信息的载体,地图空间信息的度量是地图信息传输理论的一个基础问题。地图空间信息主要包括地图要素的空间信息和要素分布的空间信息。地图空间信息是由要素的几何形态结构来体现,即要素的空间信息通过其几何形态特征描述。为此,本文以面要素为研究对象,提出一种以几何形态结构特征的面要素空间信息量度量方法。首先,从空间认知角度对面要素结构进行凸包分解,构建凸包树的面要素表达方法。然后,采用层次化策略,分别从结点的元素、邻域和整体三个层次来描述面要素几何形态结构,将面要素空间信息分解为几何形态信息和分布结构信息,结合面要素空间信息量的认知分析,给出了几何形态和分布结构特征的定量描述指标,并发展了基于几何形态结构特征的面要素空间信息量计算模型。最后,通过一组实验计算,进行了案例验证分析。

本文引用格式

刘慧敏, 邓敏, 何占军, 徐震 . 面要素空间信息量的度量方法研究[J]. 地球信息科学学报, 2012 , 14(6) : 744 -750,774 . DOI: 10.3724/SP.J.1047.2012.00744

Abstract

Map is a visualization representation of geospatial entities and their distribution. Users often can obtain large amount of information through reading a map. The measurement of map information content is one of the most important basic research issues in the theory of map information transmission. It has been preliminarily applied to map generalization and many other aspects of map applications. Spatial information of a map contains that of features and their distributions. Existing methods of measuring spatial information content only consider the information content of spatial distribution among the features. In other words, the information content of spatial features is not involved. Therefore, the results of the information content obtained by existing methods are inaccurate. For this purpose, in this paper we focused on the development of a methodology for the information content measurement of individual spatial features, where area features are chosen as an example. As a matter of fact, it has been extensively accepted that geometric shape is deemed to be the carrier of geospatial information content of an area feature. As a result, the convex hull is firstly used for shape decomposition of individual area features and a hierarchical structure called convex hull tree is proposed to represent an area feature from the view of spatial cognition. Secondly, geometric shape of area features is analyzed according to the nodes of convex hull tree at three levels, namely, node level, neighborhood level and global level. Moreover, quantitative indicators at each level are defined and utilized for the description of geometric shape, including edge number as the indicator of shape complexity, and convexity as that of shape pattern at node level, out-degree at neighborhood level and layer at global level as indicators of geometry distributions. Sequentially, the corresponding computational models are respectively developed based on geometry characteristics at three levels, which are further used to measure spatial information content of individual area features. At last, an example is provided to illustrate the rationality and the accuracy of the proposed methods.

参考文献

[1] Kolácny A. Cartographic information: A fundamental concept and term in modern cartography [J]. The Cartographic Journal, 1969, 6(1): 47-49.

[2] Stigmar H. Amount of information in mobile maps: A study of user preference [J]. Mapping and Image Science, 2006, 21(4): 68-74.

[3] 王家耀. 我国地图制图学与地理信息工程学科发展研究[J].测绘通报,2007(5):1-6.

[4] Sukhov V I. Information capacity of a map entropy [J]. Geodesy and Aerophotography, 1967, X: 212-215.

[5] 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.

[6] 田晶,艾廷华.街道渐进性选取的信息传输模型[J].武汉大学学报(信息科学版),2010,35(4):415-418.

[7] 邓敏,徐震,赵彬彬,等. 地图综合中空间目标空间信息传递模型研究[J].地球信息科学学报, 2010, 12(5): 655-661.

[8] 刘慧敏, 樊子德, 邓敏,等. 地图上等高线信息度量的层次方法研究[J].测绘学报, 2012, 41(5): 777-783.

[9] Stoter J, Burghardt D, Duchéne C, et al. Methodology for evaluating automated map generalization in commercial software[J]. Computers, Environment and Urban Systems, 2009(33): 311-324.

[10] Harrie L, Weibel R. Modeling the overall process of generalization [C].//Ruas A, Mackaness W, Sarjakoski T (Eds.). Generalization of Geographic Information: Cartographic Modeling and Applications. Elsevier, 2007, 67-88.

[11] Sukhov V I. Application of information theory in generalization of map contents [J]. International Yearbook of Cartography, 1970, X: 41-47.

[12] Neumann J. The topological information content of a map: An attempt at a rehabilitation of information theory in cartography [J]. Cartographical, 1994, 31: 26-34.

[13] Bjorke J T. Framework for entropy-based map evaluation [J]. Cartography and Geographical Information Systems, 1996, 23(2): 78-95.

[14] Wang S Y, Du Q Y, Wang Z. A quantitative measurement approach for metric information of maps based on spatial cognition [C]. Fourth International Conference on Natural Computation, IEEE Computer Society, 2008, 235-239. doi: 10.1109/ICNC.2008.379

[15] Li Z L, Huang P Z. Quantitative measures for spatial information of maps [J]. International Journal of Geographical Information Science, 2002, 16(7): 699-709.

[16] Harrie L, Stijmar H. An evaluation of measures for quantifying map information[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2010, 65(3): 266-274.

[17] 陈杰,邓敏,徐枫,等. 面状地图空间信息度量方法研究[J].测绘科学, 2010, 35(1): 74-76.

[18] Batchelor B. Hierarchical shape description based upon convex hulls of concavities [J]. Journal of Cybernetics, 1980(10): 205-210.

[19] Xu J. Hierarchical representation of 2-D shapes using convex polygons: A morphological approach [J]. Pattern Recognition Letters, 1997, 18: 1009-1017.

[20] Whelan B M, McBratney A B. Prediction uncertainty and implications for digital map resolution [C].//Robert P C, Rust R H, Larson W E (Eds.). Proceedings of the Fourth International Conference on Precision Agriculture, Madison, WI, USA, 1998, 4: 1185-1196.

[21] Palmer S. Hierarchical structure in perceptual representation [J]. Cognitive Psychology, 1977, 9: 441-474.

[22] Siddiqi K, Kimia B B. Parts of visual form: computational aspects [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995, 17(3): 239-251.

[23] 艾廷华,李志林,刘耀林,等.面向流媒体传输的空间数据变化累积模型[J].测绘学报, 2009, 38(6): 514-519.

[24] 丁险峰,吴洪,张宏江,等. 形状匹配综述[J].自动化学报, 2001, 27(5): 678-693.

[25] 刘颖. 空间图形的表达、识别与综合.郑州:中国人民解放军信息工程大学, 2005.

[26] Liu H R, Liu W Y, Latecki L J. Convex shape decomposition [J]. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, 97-104.

[27] Latecki L, Lakamper R. Convexity rule for shape decomposition based on discrete contour evolution [J]. Computer Vision and Image Understanding, 1999, 73(3): 441-454.

[28] 鲁学军. 空间认知模式研究[J].地理信息世界, 2004(6):9-13.

文章导航

/