CENTRALITY BASED HIERARCHY FOR GENERALIZING AND LABELLING STREET FEATURES IN MULTI RESOLUTION MAPS

Abstract

This paper presents a methodology to extract a new hierarchy to effectively generalize and label street features in intermediate multi scale street networks. The hierarchy uses two main parameters as criteria for ordering the street features; their centrality measures, i.e., betweeness, reach, straightness and closeness, and their functional classes attribute. The measures are integrated using fuzzy-AHP to yield proper coefficients in the hierarchy creation process. The hierarchy is applied for the thinning process to reduce the complexity of the network. Later, the proposed hierarchy is implemented as a priority value to label street features in intermediate scales.