The Methods Of Quantitative Measurement Of Geospatial Information In Vector Map

To measure map information is one of key issues in the field of cartography, and is aslo the basis of analyzing, evaluating the quality of cartography. It is not only important for further understanding characteristics of map information, but also for the effective use of map information. This paper develops some quantitative methods for the measurement of map information. These methods can be used to evaluate cartographic quality, generalization algorithms, and the transferring of map information. After reviewing relevant research progress and pointing out the existing problems and deficiencies, this paper systematically studies the measurement of map information in theories and methods. Main works are summarized as follows:(1) From the view of spatial complexity, this paper utilizes the fractal dimension to measure map information, which is respectively considered from three levels, i.e., object level, class level and map level. Then, a new method is proposed, which is based on a series of buffering operation, so it is named a buffering-based method. Unlike box-counting method and walking dividers method, the buffering-based method does not involve the location of starting box and the choice of starting point on curve. To large degree, the buffering-based method is built upon object itself.(2) From the view of the distribution of spatial objects, this paper firstly makes a critical examination of the existing approaches for map information measurement. And then, a reclassification of contents of map information is made from the consideration of geometric, thematic, topological and thematic topology. The corresponding measurements are further developed, including geometric information entropy, thematic information entropy, topological information entropy and thematic topological information entropy. On this basis, the morphology operators, i.e. dilation and sequential dilation, are used to analyze the changes of map information with the influence space of map symbols. Then it has been shown by two examples, a group of simple lines and areas, which the result obtained by Voronoi diagram is an extreme value of those by the proposed method in this paper. Indeed, our method is able to provide a series of entropy measures with different times of dilations for map symbols.Finally, this paper summarizes main findings, and highlights further research directions in the near future.