Individual Differentiated Multidimensional Hawkes Model: Uncovering Urban Spatial Interaction Using Mobile-Phone Data

Abstract

With the advent of big data and major technological achievements in information and communications technology, abundant human trajectory data are collected by location-aware devices such as mobile phones. This information has spurred the development of several methods for measuring spatial interaction, such as the gravity model and radiation model. However, prior studies have mainly measured the scale of spatial interaction at an aggregated level and have derived static or unidirectional interaction. As an improvement, an individual differentiated multidimensional (IDMD) Hawkes model, which can capture individual mobility differences as well as the dynamic mutual interaction between geographical units, is proposed herein. Internet protocol detail records (IPDRs) of Jinhua, Zhejiang, China, covering 23 days, are used as a case study to infer the spatial structure of urban interaction. Compared to the traditional spatial interaction model, the IDMD Hawkes model demonstrates unique advantages in capturing spatial interactions. The results reveal the level of interaction between regions and identify the closely related districts; this can be verified by the economic exchange and transportation convenience between these regions. Our approach provides a novel perspective for measuring spatial interaction considering individual mobility, which can assist policymakers to better understand the spatial structure of a city and plan an efficient city configuration.