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

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  • 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

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.

Cite this article

LIU Hui-Min, DENG Min, HE Tie-Jun, XU Shen . An Approach to Measuring the Spatial Information Content of an Area Feature[J]. Journal of Geo-information Science, 2012 , 14(6) : 744 -750,774 . DOI: 10.3724/SP.J.1047.2012.00744

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