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Open AccessJournal ArticleDOI

A framework for spatial interaction analysis based on large-scale mobile phone data

TLDR
This study aimed to analyze the spatial interaction based on the large-scale mobile phone data and proposed a three-stage framework, including data preprocessing, critical activity identification, and spatial interaction measurement.
Abstract
The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning. This study aimed to analyze the spatial interaction based on the large-scale mobile phone data. The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics. A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement. The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association. A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application. The spatial interaction patterns and the representative features proved the rationality of the proposed framework.

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Journal ArticleDOI

The rise of big data on urban studies and planning practices in China: Review and open research issues

TL;DR: The research progress of big data since 2000 in China is reviewed, focusing on behavior big data mining and big data application in urban studies and planning practices, and some open research issues such as potential challenges and possible directions of development are discussed.
Journal ArticleDOI

Using mobile phone data to determine spatial correlations between tourism facilities

TL;DR: A framework is proposed to determine spatial correlations between tourism destinations, rest places, and transportation hubs based on mobile phone data and it is concluded that tourists tend to rest near next-day destinations and choose transportation hubs in the city center.
Journal ArticleDOI

Understanding evacuation and impact of a metro collision on ridership using large-scale mobile phone data

TL;DR: It is found that most of Line 10 commuters still preferred to use metro to complete their travels during the disruption period of Line10, and returned to their typical commuting patterns immediately after Line 10 resumed service.
Journal ArticleDOI

Mobile Phone Data in Urban Commuting: A Network Community Detection-Based Framework to Unveil the Spatial Structure of Commuting Demand

TL;DR: A methodology framework is proposed to describe the spatial structure of commuting demand in a city using mobile phone data and finds that the administrative boundaries show a significant effect on the residential commuting behavior and the metro lines on the cross-regional commuting behavior.
References
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Book

Data Mining: Concepts and Techniques

TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Journal ArticleDOI

Modelling the scaling properties of human mobility

TL;DR: Empirical data is used to show that the predictions of the CTRW models are in systematic conflict with the empirical results, and two principles that govern human trajectories are introduced, allowing for a statistically self-consistent microscopic model for individual human mobility.
Journal ArticleDOI

Uncovering individual and collective human dynamics from mobile phone records

TL;DR: The mean collective behavior at large scales is studied and it is shown that the interevent time of consecutive calls is heavy-tailed, which has implications for dynamics of spreading phenomena in social networks.
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