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Proceedings Paper

A quantitative approach to measure road network information based on edge diversity
Author(s): Xun Wu; Hong Zhang; Tian Lan; Weiwei Cao; Jing He
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Paper Abstract

The measure of map information has been one of the key issues in assessing cartographic quality and map generalization algorithms. It is also important for developing efficient approaches to transfer geospatial information. Road network is the most common linear object in real world. Approximately describe road network information will benefit road map generalization, navigation map production and urban planning. Most of current approaches focused on node diversities and supposed that all the edges are the same, which is inconsistent to real-life condition, and thus show limitations in measuring network information. As real-life traffic flow are directed and of different quantities, the original undirected vector road map was first converted to a directed topographic connectivity map. Then in consideration of preferential attachment in complex network study and rich-club phenomenon in social network, the from and to weights of each edge are assigned. The from weight of a given edge is defined as the connectivity of its end node to the sum of the connectivities of all the neighbors of the from nodes of the edge. After getting the from and to weights of each edge, edge information, node information and the whole network structure information entropies could be obtained based on information theory. The approach has been applied to several 1 square mile road network samples. Results show that information entropies based on edge diversities could successfully describe the structural differences of road networks. This approach is a complementarity to current map information measurements, and can be extended to measure other kinds of geographical objects.

Paper Details

Date Published: 9 December 2015
PDF: 9 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 980819 (9 December 2015); doi: 10.1117/12.2207585
Show Author Affiliations
Xun Wu, Southwest Jiaotong Univ. (China)
Hong Zhang, Southwest Jiaotong Univ. (China)
Tian Lan, Southwest Jiaotong Univ. (China)
Weiwei Cao, Southwest Jiaotong Univ. (China)
Jing He, Southwest Jiaotong Univ. (China)


Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

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