Centrality-based hierarchy for street network generalization in multi-resolution maps

Abstract

This paper introduces a new hierarchy for cartographic generalisation processes, applied in street networks. The aims of implementing this hierarchy are to emphasise on significant street features, and to provide more free spaces between street features. The hierarchy is obtained from the functional classes of the features and four centrality measures in a street network, i.e. betweenness, reach, straightness and closeness extracted from a primary graph. The values of centrality measures change in every zoom level by calculating a radius parameter, which depends on the users' field of view. The coefficients for the measures are constructed using a decision-making technique called fuzzy analytical hierarchy process (FAHP). The weights for each of the centrality measures are computed and normalised to form the proposed hierarchy. The hierarchy is applied and used later in the thinning process to omit insignificant features from the street network in medium scales.