Mobile Phones in a Traffic Flow: A Geographical Perspective to Evening Rush Hour Traffic Analysis Using Call Detail Records

Järv, Olle; Ahas, Rein; Saluveer, Erki; Derudder, Ben; Witlox, Frank

doi:10.1371/journal.pone.0049171

Cited by 74 publications

(38 citation statements)

References 78 publications

(67 reference statements)

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“…Data provided by communication tools are opening up new opportunities for studying sociospatial behaviors (33)(34)(35)(36). MP call detail records were used in the past for studying human mobility patterns at the individual level (37)(38)(39) or for mapping human movements and activities using aggregated data (40)(41)(42)(43)(44). Most of these studies focused on specific cities or city neighborhoods or groups, and were aimed at understanding traffic flows (40), mapping the intensity of human activities at different times (42)(43)(44), or exploring seasonality in foreign tourist numbers and destinations (45,46).…”

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confidence: 99%

“…MP call detail records were used in the past for studying human mobility patterns at the individual level (37)(38)(39) or for mapping human movements and activities using aggregated data (40)(41)(42)(43)(44). Most of these studies focused on specific cities or city neighborhoods or groups, and were aimed at understanding traffic flows (40), mapping the intensity of human activities at different times (42)(43)(44), or exploring seasonality in foreign tourist numbers and destinations (45,46). Population movement analyses based on MP data are particularly promising for improving responses to disasters (47,48) and for planning malaria elimination strategies (49)(50)(51).…”

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confidence: 99%

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Dynamic population mapping using mobile phone data

DeVillé

Linard

Martín

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

729

528

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During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.O ur knowledge of human population numbers and distribution for many areas of the world remains poor (1) despite their importance for policy (2, 3), operational decisions (4), and research (5-7) across many fields. In the 1990s, a growing interest in the global mapping of human populations emerged (8, 9), leading to the advanced development of methodologies that undertake the spatial downscaling of human population count data from censuses summarized over large and irregular administrative units to grid squares of 100 m to 5 km resolution (10-16). Initial efforts to downscale these data used simple areal weighting methods (10, 17) or dasymetric modeling approaches (13-15), which use ancillary layers to redistribute population counts within administrative units (18). Modeling techniques that spatially downscale population numbers into gridded datasets continue to be refined, with basic dasymetric models increasing in sophistication, incorporating multiscale remotely sensed and geospatial data and making improvements in the type of statistical algorithms used in the modeling process (19)(20)(21). These detailed population databases have proven crucial for studies reliant on information about human population distributions, typically for calculating populations at risk for human or natural disasters (22-24), to assess vulnerabilities (7, 25), or to derive hea...

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confidence: 99%

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confidence: 99%

Dynamic population mapping using mobile phone data

DeVillé

Linard

Martín

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

729

528

View full text Add to dashboard Cite

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“…One of such examples is the use of cellular network's signalisation and call details record data [2,[80][81][82]. Although such data exhibit high potential for future integration into transport system planning process, at this phase, their applicability for replacing traditional data collection is still not at mature phase.…”

Section: Discussionmentioning

confidence: 99%

Integrating Big Data into a Sustainable Mobility Policy 2.0 Planning Support System

et al. 2016

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Abstract:It is estimated that each of us, on a daily basis, produces a bit more than 1 GB of digital content through our mobile phone and social networks activities, bank card payments, location-based positioning information, online activities, etc. However, the implementation of these large data amounts in city assets planning systems still remains a rather abstract idea for several reasons, including the fact that practical examples are still very strongly services-oriented, and are a largely unexplored and interdisciplinary field; hence, missing the cross-cutting dimension. In this paper, we describe the Policy 2.0 concept and integrate user generated content into Policy 2.0 platform for sustainable mobility planning. By means of a real-life example, we demonstrate the applicability of such a big data integration approach to smart cities planning process. Observed benefits range from improved timeliness of the data and reduced duration of the planning cycle to more informed and agile decision making, on both the citizens and the city planners end. The integration of big data into the planning process, at this stage, does not have uniform impact across all levels of decision making and planning process, therefore it should be performed gradually and with full awareness of existing limitations.

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“…For example, Montgomery's (2011) conceptual work "focuses on cross-place concentrations" of telecommunication between different social groups vis-à-vis "framing the residential area as the locus of racial/ethnic concentration" (p.659). Arie and Mesch (2015) empirically assess the social segregation between Arab versus Jewish Israelis in terms of their mobile phone usage, while the same type of data source was also deployed by Järv et al (2012). An intriguing recent publication is by Halberstam and Knight (2016), who track Twitter users' online connections to identify social separation in terms of political opinions.…”

Section: Segregation With Chinese Characteristicsmentioning

confidence: 99%

Measuring segregation between rural migrants and local residents in urban China: An integrated spatio-social network analysis of Kecun in Guangzhou

Zhao

Wang²

2017

Environment and Planning B: Urban Analytics and City Science

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In this paper, we demonstrate an integrated spatio-social network analysis to measure the degree of segregation within a Chinese urban neighborhood in terms of the everyday activities by rural migrants and local urban residents at such routine venues as restaurants, grocery stores, barber shops, etc. Our data were collected in May 2014, through an integrated geographical and social survey conducted within an inner-city neighborhood around Kecun in south China’s Guangzhou Municipality. Although Kecun features a highly condensed and mixed dwelling pattern between the rural migrants and indigenous urban population, we find that within our sample of 110 local and 132 migrant residents, the former tend to socialize more inwardly with their peer locals and visit neighborhood amenities more often such as pubs, stadia, and public kindergartens. In contrast, the migrants tend to attend local roadside food stalls, outdoor recreation facilities, small clinic shops, grocery malls, and private ( minban) kindergartens more often. Overall, only a modest degree of social interaction between the locals and migrants appears to exist in Kecun. On top of the methodological implications of our study, we argue that urban segregation in China is both socially and spatially different from its Anglo-American counterpart. More empirical research is needed to understand and assess social segregation underlying the everyday urban life in Chinese cities.

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Mobile Phones in a Traffic Flow: A Geographical Perspective to Evening Rush Hour Traffic Analysis Using Call Detail Records

Cited by 74 publications

References 78 publications

Dynamic population mapping using mobile phone data

Dynamic population mapping using mobile phone data

Integrating Big Data into a Sustainable Mobility Policy 2.0 Planning Support System

Measuring segregation between rural migrants and local residents in urban China: An integrated spatio-social network analysis of Kecun in Guangzhou

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