Project

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Characterizing human mobility from mobile phone usage

Applicant Raubal Martin
Number 141284
Funding scheme Project funding (Div. I-III)
Research institution Institut für Kartografie und Geoinformation ETH Zürich Departement Bau, Umwelt und Geomatik
Institution of higher education ETH Zurich - ETHZ
Main discipline Other disciplines of Engineering Sciences
Start/End 01.09.2012 - 31.12.2013
Approved amount 78'416.00
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All Disciplines (2)

Discipline
Other disciplines of Engineering Sciences
Information Technology

Keywords (8)

Spatio-temporal knowledge discovery; Geographic knowledge discovery; Mobile phone data; Information and Communication Technologies; Mobility patterns; Time series analysis; Human mobility; Uncertainty

Lay Summary (English)

Lead
Lay summary

Our mobile information society depends increasingly on the use of Information and Communication Technologies (ICTs) such as mobile phones. People’s usage of these technologies impacts many aspects of their lives but the relationship between ICT and human activities is not fully known. An understanding of this relationship will help in predicting people’s mobility patterns and provide important guidelines for maintaining sustainable transportation, updating environmental policies, and designing early warning and emergency response systems.

The goal of this project is to develop a framework for extracting and characterizing human mobility patterns from georeferenced mobile phone datasets. We analyze the different types of information that can be stored in mobile phone datasets, and develop human mobility models and data mining methodologies for spatio-temporal knowledge discovery. These models provide the basis for investigating and quantifying the relationship between human physical travel, communication travel, and environmental structure. Our research also addresses issues of uncertainty, which arise from the natural variability of human mobility, the inaccuracy and imprecision of recorded trajectories, and the imperfection of the underlying models. In order to evaluate the developed models and the relationship between human mobility patterns, spatial structure, and mobile phone usage, we will utilize a large dataset of northeast China.

This research will enhance our understanding of the relationship between human mobility and ICT in general, and between human mobility patterns and mobile phone usage in particular. We will advance conventional geographic knowledge discovery by focusing on knowledge extraction from sparse datasets with low resolution and individual attributes. The case study from northeast China allows us to examine the influence of mobile phone usage in a highly populated and rapidly developing country.

The project contributes to both scientific advances and professional development. The application of advanced geographic knowledge discovery methods to mobile data is highly important in the age of instant access and extremely relevant in diverse fields, ranging from geography to transportation, planning, and economics. The results of our project can be directly utilized by makers of environmental and transportation policies in order to direct people to more sustainable behaviors, as well as private business people in the Location-Based Services market. Our dataset from China covers over 5 million people and is therefore an excellent case study for the examination of public policies by a strong central government.

Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
Analyzing the distribution of human activity space from mobile phone usage - An individual and urban-oriented study
Yuan Y., Raubal M. (2016), Analyzing the distribution of human activity space from mobile phone usage - An individual and urban-oriented study, in International Journal of Geographical Information Science, 30(8), 1594-1621.
Exploring Georeferenced Mobile Phone Datasets - A Survey and Reference Framework
Yuan Y., Raubal M. (2016), Exploring Georeferenced Mobile Phone Datasets - A Survey and Reference Framework, in Geography Compass, 10(6), 239-252.
Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn
Ahas R., Aasa A., Yuan Y., Raubal M., Smoreda Z., Liu Y., Ziemlicki C., Tiru M., Zook M. (2015), Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn, in International Journal of Geographical Information Science , 29(11), 2017-2039.
Measuring similarity of mobile phone user trajectories - a Spatio-temporal Edit Distance method
Yihong Yuan (2014), Measuring similarity of mobile phone user trajectories - a Spatio-temporal Edit Distance method, in International Journal of Geographic Information Science, 28(3), 496-520.
Investigating the distribution of human activity space from mobile phone usage
Yuan Yihong, Raubal Martin (2013), Investigating the distribution of human activity space from mobile phone usage, in Mobile Ghent, Ghent, BelgiumUniversity of Ghent, Ghent.
Correlating mobile phone usage and travel behavior - a case study of Harbin, China
Yuan Yihong, Raubal Martin, Liu Yu (2012), Correlating mobile phone usage and travel behavior - a case study of Harbin, China, in Computers, Environment and Urban Systems, 36(2), 118-130.
Extracting dynamic urban mobility patterns from mobile phone data
Yuan Yihong, Raubal Martin (2012), Extracting dynamic urban mobility patterns from mobile phone data, in Geographic Information Science - 7th International Conference (GIScience 2012), Lect, Columbus, OhioSpringer, Heidelberg.
Similarity measurement of mobile phone user trajectories - a modified edit distance method
Yuan Yihong, Raubal Martin (2012), Similarity measurement of mobile phone user trajectories - a modified edit distance method, in Workshop on “Progress in Movement Analysis - Experiences with Real Data, Zurich, SwitzerlandUniversity of Zurich, Zurich.

Collaboration

Group / person Country
Types of collaboration
Orange Lab France (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Institute of RS and GIS, Peking University China (Asia)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
GeoTrans Laboratory, University of California, Santa Barbara United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
Department of Geography, University of Tartu Estonia (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Department of Geography, University of the Aegean Greece (Europe)
- in-depth/constructive exchanges on approaches, methods or results
Institute for Transport Planning and Systems, ETH Zurich Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Mobile Ghent Talk given at a conference Investigating the distribution of human activity space from mobile phone usage 24.10.2013 Ghent, Belgium Yuan Yihong; Raubal Martin;
SAGEO’13 Talk given at a conference GIScience & Mobility 24.09.2013 Brest, France Raubal Martin;
Geodätisches Kolloquium, Technische Universität Dresden Individual talk Geoinformations-Engineering und Mobilität 12.06.2013 Dresden, Germany Raubal Martin;
Workshop on Common Challenges in Computationally-Based Engineering Research Talk given at a conference Computationally-Based Geoinformation Engineering Research 05.06.2013 Zurich, Switzerland Raubal Martin;
Annual Meeting of the Association of American Geographers Talk given at a conference A framework for characterizing human mobility from georeferenced mobile phone data 09.04.2013 Los Angeles, United States of America Yuan Yihong;
Seminar on “Mobility, segregation and neighborhoods' change” Talk given at a conference Identifying Dynamic Urban Mobility Patterns from Mobile Phone Data 14.03.2013 Tartu, Estonia Yuan Yihong;
Transportation Research Board Annual Meeting (TRB) Talk given at a conference Characterizing human mobility and travel behavior from mobile phone usage 13.01.2013 Washington DC, United States of America Yuan Yihong;
Z_GIS, TechnologieZentrum, Salzburg Individual talk GIScience & Mobility 18.12.2012 Salzburg, Austria Raubal Martin;
Workshop on “Progress in Movement Analysis - Experiences with Real Data” Talk given at a conference Similarity Measure of Mobile Phone Trajecotories – a Modified Edit Distance Method 15.11.2012 Zurich, Switzerland Yuan Yihong;
GIScience 2012 Talk given at a conference Extracting Dynamic Urban Mobility Patterns from Mobile Phone Data 18.09.2012 Columbus, United States of America Raubal Martin; Yuan Yihong;


Knowledge transfer events

Active participation

Title Type of contribution Date Place Persons involved
Public Lecture for ETH Cource "Mobile GIS" Talk 31.10.2013 Zurich, Switzerland Yuan Yihong;


Communication with the public

Communication Title Media Place Year
Talks/events/exhibitions Public Lecture for ETH Cource "Mobile GIS" German-speaking Switzerland 2013

Awards

Title Year
Dangermond Travel Award, Department of Geography, UC Santa Barbara 2013
Government Award for Outstanding Self-Financed Students Abroad, Chinese Ministry of Education 2013
Excellence in Research, Department of Geography, UC Santa Barbara 2012
Graduate Division Dissertation Fellowship, UC Santa Barbara 2012
Student Scholarship, GIScience 2012 2012

Abstract

Today's mobile information society depends increasingly on the use of Information and Communication Technologies (ICTs) such as mobile phones. People's usage of these technologies impacts many aspects of their lives, but the relationship between ICT and human activities is a complex one. A thorough understanding of the correlation between mobile phone usage and human mobility will help in predicting people's mobility patterns and therefore provide important guidelines for maintaining sustainable transportation, updating environmental policies, and designing early warning and emergency response systems.In this project, we develop a generalizable framework for extracting and characterizing human mobility patterns from georeferenced mobile phone datasets. We begin by analyzing the different types of information that can be stored in mobile phone datasets. We then develop extended human mobility models and data mining methodologies for spatio-temporal knowledge discovery. These models provide the basis for investigating and quantifying the correlation between human physical travel, communication travel, and environmental structure. Our research will also address issues of uncertainty, which arise from the natural variability of human mobility, the inaccuracy and imprecision of recorded trajectories, and the imperfection of the underlying models. Finally, a large dataset of northeast China will be utilized for a comprehensive evaluation of the developed models and the correlation between spatial structure, human mobility patterns, and mobile phone usage.This research will enhance our understanding of the relationship between human mobility and ICT in general, and between human mobility patterns and mobile phone usage in particular. In addition, we will advance conventional geographic knowledge discovery by focusing on knowledge extraction from sparse datasets with low resolution and individual attributes. The case study from northeast China allows us to examine the influence of mobile phone usage in a highly populated and rapidly developing country.The proposed project contributes to both scientific advances and professional development. The application of advanced geographic knowledge discovery methods to mobile data is highly important in the age of instant access and extremely relevant in diverse fields, ranging from geography to transportation, planning, and economics. The results of our project can be directly utilized by makers of environmental and transportation policies in order to direct people to more sustainable behaviors, as well as private business people in the Location-Based Services market. Our dataset from China covers over 5 million people and is therefore an excellent case study for the examination of public policies by a strong central government.With respect to professional development, the proposal presents collaboration among researchers on three continents, which brings a unique richness in terms of intellectual and cultural resources. Our graduate and undergraduate researchers will gain valuable experience due to the highly multi- and interdisciplinary research. Human mobility is a wide ranging topic and will therefore offer unique opportunities for the integration of research and education; we will provide both teaching material and a large real-world dataset to be integrated in various courses at ETH Zurich.We plan to disseminate our research results broadly in peer-reviewed journals, at conferences and professional meetings, and through the project’s website.
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