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Measuring polycentricity: a whole graph embedding perspective
Polycentricity is a critical characteristic of the spatial organization of cities. Many indices have been proposed to measure the degree of morphological polycentricity or functional polycentricity. However, selecting a proper set of polycentricity indices for cities in a particular region or country still needs prior expert knowledge. This study demonstrates that whole graph embedding, as a novel and efficient computational tool, can model the city polycentricity in an integrated manner without much prior knowledge. The new method can further support visual analytics and classification very well.
Measuring polycentricity: a whole graph embedding perspective
Polycentricity is a critical characteristic of the spatial organization of cities. Many indices have been proposed to measure the degree of morphological polycentricity or functional polycentricity. However, selecting a proper set of polycentricity indices for cities in a particular region or country still needs prior expert knowledge. This study demonstrates that whole graph embedding, as a novel and efficient computational tool, can model the city polycentricity in an integrated manner without much prior knowledge. The new method can further support visual analytics and classification very well.
Measuring polycentricity: a whole graph embedding perspective
Fu, Cheng (Autor:in) / Nanni, Mirco (Autor:in) / Yeghikyan, Gevorg (Autor:in) / Weibel, Robert (Autor:in)
01.01.2021
doi:10.25436/E2TG6C
Fu, Cheng; Nanni, Mirco; Yeghikyan, Gevorg; Weibel, Robert (2021). Measuring polycentricity: a whole graph embedding perspective. Santa Barbara: UC Santa Barbara: Center for Spatial Studies.
Paper
Elektronische Ressource
Englisch
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