 Identifying the city center using human travel flows generated from location-based social networking dataYeran Sun, Hongchao Fan, Ming Li and Alexander Zipf Environment and Planning B, 2016, vol. 43, issue 3, 480-498 Abstract: Since cities have become more complex and some large cities are likely to be polycentric, a better understanding of cities requires a clear topology that reveals how city centers are spatially distributed and interacted with. The identification of a city center that aims to find the accurate location of the city center or delineate the city center with a precise boundary becomes vital. This work attempts to achieve this by using a new type of movement data generated from location-based social networks, whereby three different methods are deployed for clustering and compared regarding identification of city centers and delineation of their boundaries. Experiments show that city centers with precise boundaries can be identified by using the proposed approach with location-based social network data. Furthermore, the results show that the three methods for clustering have different advantages and disadvantages during the process of city center identification, and thus seem to be suitable for cities with different urban structures. Keywords: Center identification; human mobility; local Getis–Ord Gi*; DBSCAN; Grivan–Newman (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:43:y:2016:i:3:p:480-498 Access Statistics for this article More articles in Environment and Planning B |
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