A Review of Human Mobility Research Based on Big Data and Its Implication for Smart City Development

Anshu Zhang · Edwin H.W. Chan · Wenzhong Shi · Xiaolin Zhou · Zhewei Liu

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Human Mobility and Location-Based Analysis Geographic Information Systems Studies Smart Cities and Technologies

Abstract

Along with the increase of big data and the advancement of technologies, comprehensive data-driven knowledge of urban systems is becoming more attainable, yet the connection between big-data research and its application e.g., in smart city development, is not clearly articulated. Focusing on Human Mobility, one of the most frequently investigated applications of big data analytics, a framework for linking international academic research and city-level management policy was established and applied to the case of Hong Kong. Literature regarding human mobility research using big data are reviewed. These studies contribute to (1) discovering the spatial-temporal phenomenon, (2) identifying the difference in human behaviour or spatial attributes, (3) explaining the dynamic of mobility, and (4) applying to city management. Then, the application of the research to smart city development are scrutinised based on email queries to various governmental departments in Hong Kong. The identified challenges include data isolation, data unavailability, gaming between costs and quality of data, limited knowledge derived from rich data, as well as estrangement between public and private sectors. With further improvement in the practical value of data analytics and the utilization of data sourced from multiple sectors, paths to achieve smarter cities from policymaking perspectives are highlighted.

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References

2020Economic and social consequences of human mobility restrictions under COVID-19 2015Big Data for Development: A Review of Promises and Challenges 2014Detecting the dynamics of urban structure through spatial network analysis 2020COVID-19: Challenges to GIS with Big Data 2015Geospatial Big Data: Challenges and Opportunities 2012Spatiotemporal Patterns of Urban Human Mobility 2015Inferring trip purposes and uncovering travel patterns from taxi trajectory data 2017On data processing required to derive mobility patterns from passively-generated mobile phone data

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