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This paper examined the use of navigation and point-of-interests big data in three urban planning tools: community detection, road importance assessment, and urban function pattern recognition. We revealed the community structure for the urban spatial organization, followed by identifying major transit corridors and the urban function pattern. We found that the detected communities were significantly associated with the administrative divisions in the city. Major commercial and residential centers were primarily located across several communities. Besides, the spatial mismatch between commercial-residential areas and industrial development areas was also identified and examined for spatial structure optimization in urban development.

Community detection, road importance assessment, and urban function pattern recognition: a big data approach