Measures of Human Mobility Using Mobile Phone Records Enhanced with GIS Data

In the past decade, large scale mobile phone data have become available for the study of human movement patterns. These data hold an immense promise for understanding human behavior on a vast scale, and with a precision and accuracy never before possible with censuses, surveys or other existing data collection techniques. There is already a significant body of literature that has made key inroads into understanding human mobility using this exciting new data source, and there have been several different measures of mobility used. However, existing mobile phone based mobility measures are inconsistent, inaccurate, and confounded with social characteristics of local context. New measures would best be developed immediately as they will influence future studies of mobility using mobile phone data. In this article, we do exactly this. We discuss problems with existing mobile phone based measures of mobility and describe new methods for measuring mobility that address these concerns. Our measures of mobility, which incorporate both mobile phone records and detailed GIS data, are designed to address the spatial nature of human mobility, to remain independent of social characteristics of context, and to be comparable across geographic regions and time. We also contribute a discussion of the variety of uses for these new measures in developing a better understanding of how human mobility influences micro-level human behaviors and well-being, and macro-level social organization and change.

[1]  Margaret Martonosi,et al.  ON CELLULAR , 2022 .

[2]  M. Todaro,et al.  Migration, Unemployment and Developmnent: A Two-Sector Analysis , 2007 .

[3]  Nithya Sambasivan,et al.  Information technology and international development , 2012, XRDS.

[4]  John R. Harris,et al.  Migration, Unemployment & Development: A Two-Sector Analysis , 1970 .

[5]  Caroline O. Buckee,et al.  The impact of biases in mobile phone ownership on estimates of human mobility , 2013, Journal of The Royal Society Interface.

[6]  David L. Smith,et al.  Quantifying the Impact of Human Mobility on Malaria , 2012, Science.

[7]  David W. S. Wong,et al.  Comparing Traditional and Spatial Segregation Measures: A Spatial Scale Perspective1 , 2004 .

[8]  N. Stanietsky,et al.  The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity , 2009, Proceedings of the National Academy of Sciences.

[9]  Nathan Eagle,et al.  Spatiotemporal Detection of Unusual Human Population Behavior Using Mobile Phone Data , 2014, PloS one.

[10]  Petter Holme,et al.  Predictability of population displacement after the 2010 Haiti earthquake , 2012, Proceedings of the National Academy of Sciences.

[11]  Andrew J. Tatem,et al.  Mapping population and pathogen movements. , 2014, International health.

[12]  Edzer J. Pebesma,et al.  Applied Spatial Data Analysis with R - Second Edition , 2008, Use R!.

[13]  P. Diggle Applied Spatial Statistics for Public Health Data , 2005 .

[14]  Albert-László Barabási,et al.  Collective Response of Human Populations to Large-Scale Emergencies , 2011, PloS one.

[15]  Guangqing Chi,et al.  Applied Spatial Data Analysis with R , 2015 .

[16]  Volker C. Radeloff,et al.  Road Density and Landscape Pattern in Relation to Housing Density, and Ownership, Land Cover, and Soils , 2005, Landscape Ecology.

[17]  Peter D. Hoff Extending the rank likelihood for semiparametric copula estimation , 2006, math/0610413.

[18]  Carlo Ratti,et al.  Understanding individual mobility patterns from urban sensing data: A mobile phone trace example , 2013 .

[19]  Caroline O. Buckee,et al.  The Use of Census Migration Data to Approximate Human Movement Patterns across Temporal Scales , 2013, PloS one.

[20]  Michael P. Todaro,et al.  Illegal migration and US immigration reform: a conceptual framework. , 1987 .

[21]  S H Putman,et al.  Effects of Spatial System Design on Spatial Interaction Models. 1: The Spatial System Definition Problem , 1988 .

[22]  Joshua E. Blumenstock,et al.  Information Technology for Development Inferring Patterns of Internal Migration from Mobile Phone Call Records: Evidence from Rwanda Inferring Patterns of Internal Migration from Mobile Phone Call Records: Evidence from Rwanda , 2022 .

[23]  J. Edward Taylor,et al.  Undocumented Mexico—U.S. Migration and the Returns to Households in Rural Mexico , 1987 .

[24]  Lars Brabyn,et al.  Modeling population access to New Zealand public hospitals , 2002, International journal of health geographics.

[25]  K. Donato,et al.  Current Trends and Patterns of Female Migration: Evidence from Mexico 1 , 1993, The International migration review.

[26]  A S Fotheringham,et al.  The Modifiable Areal Unit Problem in Multivariate Statistical Analysis , 1991 .

[27]  Albert-László Barabási,et al.  Understanding individual human mobility patterns , 2008, Nature.

[28]  Nathalie Williams,et al.  Education, gender, and migration in the context of social change. , 2009, Social science research.

[29]  P. Olivier,et al.  Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data , 2012, PloS one.

[30]  Nathalie E. Williams,et al.  COMMUNITY SERVICES AND OUT-MIGRATION. , 2009, International migration.

[31]  Harry Eugene Stanley,et al.  Calling patterns in human communication dynamics , 2013, Proceedings of the National Academy of Sciences.

[32]  M. Todaro,et al.  A Model for Labor Migration and Urban Unemployment in Less Developed Countries , 1969 .

[33]  J. Blumenstock,et al.  Divided We Call: Disparities in Access and Use of Mobile Phones in Rwanda , 2012 .

[34]  Robert Haining,et al.  Spatial Data Analysis: Theory and Practice , 2003 .

[35]  E. Fama,et al.  Migration , 2007 .

[36]  D. Massey,et al.  Social structure, household strategies, and the cumulative causation of migration. , 1990, Population index.

[37]  Douglas S. Massey,et al.  What's Driving Mexico-U.S. Migration? A Theoretical, Empirical, and Policy Analysis , 1997, American Journal of Sociology.

[38]  Liang Liu,et al.  Estimating Origin-Destination Flows Using Mobile Phone Location Data , 2011, IEEE Pervasive Computing.

[39]  Stephen Graham Ritchie,et al.  TRANSPORTATION RESEARCH. PART C, EMERGING TECHNOLOGIES , 1993 .

[40]  Marta C. González,et al.  Origin-destination trips by purpose and time of day inferred from mobile phone data , 2015 .

[41]  Ronald R. Keiper Social structure. , 2003, The Veterinary clinics of North America. Equine practice.

[42]  Ling Bian,et al.  From traces to trajectories: How well can we guess activity locations from mobile phone traces? , 2014 .

[43]  Stephen Greaves,et al.  Household travel surveys: Where are we going? , 2007 .

[44]  A. Tatem,et al.  Dynamic population mapping using mobile phone data , 2014, Proceedings of the National Academy of Sciences.

[45]  J. Wolf,et al.  Impact of Underreporting on Mileage and Travel Time Estimates: Results from Global Positioning System-Enhanced Household Travel Survey , 2003 .

[46]  Graeme Hugo,et al.  Theories of international migration: a review and appraisal. , 1993 .

[47]  Douglas S. Massey,et al.  International migration and development in mexican communities , 1996, Demography.

[48]  Daniel A Rodriguez,et al.  International Journal of Health Geographics the Importance of Accurate Road Data for Spatial Applications in Public Health: Customizing a Road Network , 2022 .

[49]  Leah K. Vanwey Land Ownership as a Determinant of International and Internal Migration in Mexico and Internal Migration in Thailand 1 , 2005 .

[50]  D D Darshan,et al.  Clinical study to know the efficacy of Amlexanox 5% with other topical Antiseptic, Analgesic and Anesthetic agents in treating minor RAS. , 2014, Journal of international oral health : JIOH.

[51]  David E. Bloom,et al.  The new economics of labor migration , 1985 .

[52]  Hunter N. B. Moseley,et al.  Limits of Predictability in Human Mobility , 2010 .

[53]  Oded Stark,et al.  Migration incentives migration types: the role of relative deprivation. , 1991 .