Discovering Urban Functional Polycentricity: A Traffic Flow-Embedded and Topic Modeling-Based Methodology Framework

With the rapid development of communication and transportation technologies, the urban area is increasingly becoming an ever more dynamic, comprehensive, and complex system. Meanwhile, functional polycentricity as a distinctive feature has been characterizing urban areas around the world. However, the spatial structure of the urban area has yet to be fully comprehended from a dynamic perspective, and understanding the spatial organization of polycentric urban regions (PUR) is crucial for issues related to urban planning, traffic control, and urban risk management. The analysis of polycentricity strongly depends on the spatial scale. In order to identify functional polycentricity at the intra-unban scale, this paper presents a traffic flow-embedded and topic modeling-based methodology framework. This framework was evaluated on real-world datasets from the Wujiang district, Suzhou, China, which contains 151,419 records of taxi trajectory data and 86,036 records of points of interest (POI) data. This paper provides a novel approach to examining urban functional polycentricity via combining urban function distribution and spatial interactions. This proposed methodology can help urban authorities better understand urban dynamics in terms of function distribution and internal connectedness and facilitate urban development in terms of urban planning and traffic control.

[1]  Carlo Ratti,et al.  Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis , 2006 .

[2]  Tomoharu Iwata,et al.  Geo topic model: joint modeling of user's activity area and interests for location recommendation , 2013, WSDM.

[3]  Thomas Hofmann,et al.  Unsupervised Learning by Probabilistic Latent Semantic Analysis , 2004, Machine Learning.

[4]  Zhenhong Du,et al.  Identifying Urban Functional Zones Using Public Bicycle Rental Records and Point-of-Interest Data , 2018, ISPRS Int. J. Geo Inf..

[5]  Minho Seo,et al.  Does the Polycentric Urban Region Contribute to Economic Performance? The Case of Korea , 2018, Sustainability.

[6]  Michael I. Jordan,et al.  Modeling annotated data , 2003, SIGIR.

[7]  J. B. Parr,et al.  Perspectives on the city‐region , 2005 .

[8]  Xing Xie,et al.  Discovering regions of different functions in a city using human mobility and POIs , 2012, KDD.

[9]  Otto Raspe,et al.  On the Economic Foundation of the Urban Network Paradigm: Spatial Integration, Functional Integration and Economic Complementarities within the Dutch Randstad , 2009 .

[10]  N. Green.  Functional Polycentricity: A Formal Definition in Terms of Social Network Analysis , 2007 .

[11]  Soong Moon Kang,et al.  Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows , 2010, PloS one.

[12]  Michael Batty,et al.  Detecting the dynamics of urban structure through spatial network analysis , 2014, Int. J. Geogr. Inf. Sci..

[13]  Daniel Müller,et al.  Land use dynamics in the central highlands of Vietnam: a spatial model combining village survey data with satellite imagery interpretation , 2002 .

[14]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[15]  Martijn J. Burger,et al.  Functional Polycentrism and Urban Network Development in the Greater South East, United Kingdom: Evidence from Commuting Patterns, 1981–2001 , 2010 .

[16]  J. Storbeck.  The Spatial Structuring of Central Places , 2010 .

[17]  Michael Hoyler,et al.  External Urban Relational Process: Introducing Central Flow Theory to Complement Central Place Theory , 2010 .

[18]  R. Tateishi,et al.  Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing , 2006 .

[19]  M. Burger,et al.  Spatial Structure and Productivity in US Metropolitan Areas , 2010 .

[20]  John F. McDonald,et al.  Employment Subcenters and Land Values in a Polycentric Urban Area: The Case of Chicago , 1990 .

[21]  M. Burger,et al.  Heterogeneous development of metropolitan spatial structure: Evidence from commuting patterns in English and Welsh city-regions, 1981–2001 , 2011 .

[22]  Andrew McCallum,et al.  Topics over time: a non-Markov continuous-time model of topical trends , 2006, KDD '06.

[23]  K. W. Ogden,et al.  THE DISTRIBUTION OF TRUCK TRIPS AND COMMODITY FLOW IN URBAN AREAS: A GRAVITY MODEL ANALYSIS , 1978 .

[24]  P. Hall,et al.  Modelling the Post-Industrial City , 1997 .

[25]  Francisco C. Pereira,et al.  Mining point-of-interest data from social networks for urban land use classification and disaggregation , 2015, Comput. Environ. Urban Syst..

[26]  Alexei Pozdnoukhov,et al.  Temporal decomposition and semantic enrichment of mobility flows , 2013, LBSN '13.

[27]  E. Meijers.  Polycentric Urban Regions and the Quest for Synergy: Is a Network of Cities More than the Sum of the Parts? , 2005 .

[28]  Chenghu Zhou,et al.  A new insight into land use classification based on aggregated mobile phone data , 2013, Int. J. Geogr. Inf. Sci..

[29]  M. Burger,et al.  Form Follows Function? Linking Morphological and Functional Polycentricity , 2012 .

[30]  Felix Kling,et al.  When a city tells a story: urban topic analysis , 2012, SIGSPATIAL/GIS.

[31]  Albert-László Barabási,et al.  Understanding individual human mobility patterns , 2008, Nature.

[32]  Favyen Bastani,et al.  Towards Reducing Taxicab Cruising Time Using Spatio-Temporal Profitability Maps , 2011, SSTD.

[33]  Daqing Zhang,et al.  Measuring social functions of city regions from large-scale taxi behaviors , 2011, 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[34]  Licia Capra,et al.  Urban Computing: Concepts, Methodologies, and Applications , 2014, TIST.

[35]  Antti Vasanen.  Functional Polycentricity: Examining Metropolitan Spatial Structure through the Connectivity of Urban Sub-centres , 2012 .

[36]  R. E. Preston.  A COMPARISON OF FIVE MEASURES OF CENTRAL PLACE IMPORTANCE AND OF SETTLEMENT SIZE , 1975 .

[37]  A. Markusen.  Fuzzy Concepts, Scanty Evidence, Policy Distance: The Case for Rigour and Policy Relevance in Critical Regional Studies , 1999 .

[38]  Peng Gao,et al.  Discovering Spatial Patterns in Origin‐Destination Mobility Data , 2012, Trans. GIS.

[39]  Hui Xiong,et al.  Discovering Urban Functional Zones Using Latent Activity Trajectories , 2015, IEEE Transactions on Knowledge and Data Engineering.

[40]  R. Kloosterman,et al.  The Polycentric Urban Region: Towards a Research Agenda , 2001 .

[41]  B. Derudder,et al.  Measuring Polycentric Urban Development in China: An Intercity Transportation Network Perspective , 2016 .

[42]  J. B. Parr,et al.  The Polycentric Urban Region: A Closer Inspection , 2004 .

[43]  J. B. Parr,et al.  Spatial Definitions of the City: Four Perspectives , 2007 .

[44]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[45]  R. Kloosterman,et al.  Clustering of Economic Activities in Polycentric Urban Regions: The Case of the Randstad , 2001 .