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To study inter-city trip distribution pattern by exploration massive cellular data

Analyses of inter-city transport dynamics and accessibility by mining massive cellular datasets: Case Study in Chongqing City. Research Motivation. To study inter-city trip distribution pattern by exploration massive cellular data The traditional trip distribution data gathering methods:

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To study inter-city trip distribution pattern by exploration massive cellular data

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  1. Analyses of inter-city transport dynamics and accessibility by mining massive cellular datasets: Case Study in Chongqing City Research Motivation To study inter-city trip distribution pattern by exploration massive cellular data The traditional trip distribution data gathering methods: Incapability of analyzing inter-city trip distribution; Expensive, time-consuming; Limited sample size/low update frequency; Cellphones data: Sharply increase in Cellpone penetration rates; Capability of positioning; Large simple size/High update frequency; To incorporate some social economic factors into inter-city distribution analysis Unlike the traditional trip distribution graph, this study employed a social network visualization tool to reflect interaction between inter-city trip distribution and social economic factors;

  2. Analyses of inter-city transport dynamics and accessibility by mining massive cellular datasets: Case Study in Chongqing City Cellphones Data and Working Philosophy

  3. Analyses of inter-city transport dynamics and accessibility by mining massive cellular datasets: Case Study in Chongqing City Outcome • Around 1.5TB cellular data has been processed and around 1.0TB has been tracked. • A 30*30 OD matrix has been successfully extracted in Chongqing main city and its satellite cities. • Population, GDP and Urbanization rate have been incorporated with trip distribution to reflect interaction with social/economic factors. • A social network visualization concept is employed to graph the interaction between social/economic factors and inter-city trip distribution, and it is found the connectivity strength among cities has a positive relationship with GDP and urbanization rate while the size of population does not show heavy impact on inter-city trip distribution.

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