Опыт использования данных операторов сотовой связи в зарубежных экономико-географических исследованиях

  • Роман Александрович Бабкин ФГБОУ Российский экономический университет имени Г.В. Плеханова, 117997, Российская Федерация, г. Москва, Стремянный пер., 36

Аннотация

Вступление в эпоху «Больших данных» и появление новых источников геоинформации, включая данные сотовых операторов, предоставили принципиально новые возможности для исследований многих социально-экономических процессов. По сравнению с традиционными источниками, сведения операторов сотовой связи имеют ряд уникальных особенностей и преимуществ, которые привлекают ученых из различных областей знаний. Обширный опыт применения технологий сбора и обработки пространственной информации с мобильных телефонов, накопленный за последние 15 лет, обуславливает интерес к ним в целях совершенствования демографической статистики, транспортного планирования, анализа систем расселения, статистики туризма, изучения поведения людей и мониторинга чрезвычайных ситуаций. В статье на примерах зарубежных работ продемонстрированы различные кейсы использования данных сотовых операторов в научных и научно-прикладных исследованиях по этим направлениям. Зарубежная практика применения данных операторов сотовой связи демонстрирует, насколько анализ данных способен дополнять результаты переписей и регистров населения, позволяя переходить от статического к динамическому рассмотрению системы расселения. Сочетание сведений мобильной телефонии с информацией традиционной статистики, а также другими видами «Больших данных», например дистанционного зондирования, способствует улучшению пространственного и временного разрешения геоинформации при изучении демографических и социально-экономических процессов. При этом можно наблюдать, что потенциальное использование этого источника данных не ограничивается дополнением системы существующих статистических показателей, а включает в себя создание принципиально новых социально-экономических индикаторов (например, дневного или сезонного населения и др.). Кроме того, существующая долгое время проблема отставания отечественной статистики от передовых стран Европы и США может быть в значительной степени нивелирована в результате инкорпорирования в исследовательскую практику «Больших данных».

Ключевые слова:

данные сотовых операторов, изучение систем расселения, делимитация агломераций, мониторинг социально-экономических процессов

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Литература

A Study on Urban Mobility and Dynamic Population Estimation by Using Aggregate Mobile Phone Sources. (2014). CSIS Discussion Paper. No. 115. [online] Available at: http://www.csis.u-tokyo.ac.jp/dp/115.pdf [Accessed 10 July 2021].

Ahas, R., Aasa, A., Silm, S. and Tiru, M. (2007). Mobile Positioning Data in Tourism Studies and Monitoring: Case Study in Tartu, Estonia. In: M. Sigala, L. Mich, J. Murphy, ed., Information and Communication Technologies in Tourism. Vienna: Springer, 119-128. https://doi.org/10.1007/978-3-211-69566-1_12

Ahas, R., Aasa, A., Yuan, Y., Raubal, M., Smoreda, Z., Liu, Y., Ziemlicki, C., Tiru, M. and Zook, M. (2015). Everyday space-time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn. International Journal of Geographical Information Science, 29 (11), 2017-2039. https://doi.org/10.1080/13658816.2015.1063151

Ahas, R., Silm, S., Järv, O., Saluveer, E. and Tiru, M. (2010). Using mobile positioning data to model locations meaningful to users of mobile phones. Journal of Urban Technology, 1 (17), 3-27. https://doi.org/10.1080/10630731003597306

Ahas, R., Silm, S., Saluveer, E. and Järv, O.(2009). Modelling home and work locations of populations using passive mobile positioning data. In: G. Gartner, K. Rehrl, ed., Location based services and telecartography II, Lecture Notes in Geoinformation and Cartography. Berlin, Heidelberg: Springer, 301-315. https://doi.org/10.1007/978-3-540-87393-8_18

Aker, J. C. and Mbiti, I. M. (2010). Mobile Phones and Economic Development in Africa. Journal of Economic Perspectives, 3 (24), 207-232. http://dx.doi.org/10.2139/ssrn.1693963

Andrienko, G. and Andrienko, N. (2008). Spatio-temporal aggregation for visual analysis of movements. In: Visual Analytics Science and Technology conference, 51-58. http://dx.doi.org/10.1109/ VAST. 2008.4677356

Bajardi, P., Delfino, M., Panisson, A., Petri, G. and Tizzoni, M.(2015). Unveiling patterns of international communities in a global city using mobile phone data. Data Science, 4, 1-17. https://doi.org/10.1140/epjds/s13688-015-0041-5

Bekhor, S., Cohen, Y. and Solomon, C. (2013). Evaluating Long Distance Travel Patterns in Israel by Tracking Cellular Phone Positions. Journal of Advanced Transportation, 47, 435-446. https://doi.org/10.1002/atr.170

Berlingerio, M., Calabrese, F., Lorenzo, G., Nair, R., Pinelli, F. and Sbodio, M.(2013). AllAboard: A system for exploring urban mobility and optimizing public transport using cellphone data. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 663-666. https://doi.org/10.1007/978-3-642-40994-3_50

Birkin, M., Clarke, C. and Clarke, M. (2017). Retail Location Planning in an Era of Multi-Channel Growth. London: Routledge.

Blondel, V., Krings, G. and Thomas, I. (2010). Regions and borders of mobile telephony in Belgium and in the Brussels metropolitan zone. Brusells Studies, 42, 1-12. https://doi.org/10.4000/BRUSSELS.806

Blumenstock, J. and Fratamico, L. (2013). Social and Spatial Ethnic Segregation: A Framework for Analyzing Segregation with Large-Scale Spatial Network Data. In: Proceedings of the 4th Annual Symposium on Computing for Development, 1-10. https://doi.org/10.1145/2537052.2537061

Calabrese, F., Diao, M., Lorenzo, D., Ferreira, J. and Ratti, C. (2013). Understanding individual mobility patterns from urban sensing data: A mobile phone trace example. Transportation Research Part C: Emerging Technologies, 26, 301-313. https://doi.org/10.1016/j.trc.2012.09.009

Csaji, B., Browet, A., Traag, V. A., Delvenne, J.-C., Huens, E., Van Dooren, P., Smoreda, Z. and Blondel, V. (2013). Exploring the Mobility of Mobile Phone Users. Physics and Society, 6 (392), 1459-1473. https://doi.org/10.1016/j.physa.2012.11.040

Deville, P., Linard, C., Martine, S., Gilbert, M., Steven, F., Gaughan, A., Blondel, V. and Tatem, A. (2014). Dynamic population mapping using mobile phone data. PNAS, 111 (45), 88-93. https://doi.org/10.1073/pnas.1408439111

Eagle, N., Macy, M. and Claxton, R.(2010). Network diversity and economic development. Science, 328 (5981), 1029-1031. https://doi.org/10.1126/science.1186605

ESSnet Big Data. (2021). European Commission. [online] Available at: https://ec.europa.eu/eurostat/cros/content/essnet-big-data_en [Accessed 10 July 2021].

Eurostat. (2014). Feasibility study of the use of mobile positioning data for tourism statistics. In: Consolidated Report Eurostat Contract No. 30501.2012.001-2012.452. https://doi.org/10.2785/55051

Giugale, M. (2012). Fix Africa’s Statistics. [online] Available at: https://www.huffpost.com/entry/fix-africas-statistics_b_2324936 [Accessed 10 July 2021].

Handbook on the use of Mobile Phone data for Official Statistics. (2019). UN Global Working Group on Big Data for Official Statistics. [online] Available at: https://unstats.un.org/bigdata/task-teams/mobile-phone/MPD%20Handbook%2020191004.pdf [Accessed 10 July 2021].

Hellerstein, J. (2008). The Commoditization of Massive Data Analysis. O’reilly Radar. [online] Available at: http://radar.oreilly.com/2008/11/the-commoditization-of-massive.html [Accessed 10 July 2021].

Inferring migrations, traditional methods and new approaches based on mobile phone, social media, and other big data. Feasibility study on inferring (labour) mobility and migration in the European Union from big data and social media data. (2016). In: Feasibility study on inferring (labour) mobility and migration in the European Union from big data and social media data. https://doi.org/10.2767/61617 [online] Available at: https://op.europa.eu/en/publication-detail/-/publication/1f66f928-f307-4c1f-9bec-fd-e0d2008c69 [Accessed 10 July 2021].

Järv, O. (2013). Mobile phone based data in human travel behaviour studies: New insights from a longitudinal perspective. Tartu: University of Tartu Press.

Järv, O., Ahas, R., Saluveer, E., Derudder, B. and Witlox, F. (2012). Mobile phones in a traffic flow: A geographical perspective to evening rush hour traffic analysis using call detail records. PLoS ONE, 7 (11), 1-11. https://doi.org/10.1371/journal.pone.0049171

Jiang, S., Ferreira, J., Gonzalez, J. and Gonzalez, M. (2017). Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore. IEEE Transactions on Big Data, 2 (3), 208-219. https://doi.org/10.1109/TBDATA.2016.2631141

Lenormand, M., Picomell, M., Cantú-Ros, O. G., Tugores, A., Louail, T., Herranz, R., Barthelemy, M., Frías-Martínez, E. and Ramasco, J. J. (2014). Cross-Checking Different Sources of Mobility Information. PLoS ONE, 8 (9), 1-10. https://doi.org/10.1371/journal.pone.0105184

Louail, T., Lenormand, M., Ros, O.-K., Picornell, M., Herranz, R., Frias-Martinez, E., Ramasco, J. and Barthelemy, M. (2014). From mobile phone data to the spatial structure of cities. Scientific Reports, 4, 1-12. https://doi.org/10.1038/srep05276

Lu, X., Bengtsson, L. and Holme, P. (2012). Predictability of population displacement after the 2010 Haiti earthquake. In: Proceedings of the National Academy of Sciences, 29 (109), 11576-11581. https://doi.org/10.1073/pnas.1203882109

Masso, A., Silm, S. and Ahas, R. (2018). Generational differences in spatial mobility: A study with mobile phone data. Population, Space and Place, 25 (2), 1-15. https://doi.org/10.1002/psp.2210

Measuring the Information Society Report. (2014). International Telecommunication Union Place des Nation. Geneva.

Nanni, M., Trasarti, R., Furletti, B., Gabrielli, L., Mede, P., Bruijn, J., Romph, E. and Bruil, G. (2013). MP4-A project: Mobility planning for Africa. In: 3rd Conference on the Analysis of Mobile Phone datasets (Net- Mob 2013).

Nemeškal, J., Ouředníček, M. and Pospíšilová, L. (2020). Temporality of urban space: daily rhythms of a typical week day in the Prague metropolitan area. Journal of Maps, 1 (16), 30-39. https://doi.org/10.1080/17445647.2019.1709577

Nilbe, K., Ahas, R. and Siiri, S. (2014). Evaluating the Travel Distances of Events Visitors and Regular Visitors Using Mobile Positioning Data: The Case of Estonia. Journal of Urban Technology, 21 (2), 91-107. https://doi.org/10.1080/10630732.2014.888218

Novak, J. and Temelova, J. (2012). Everyday Life and Spatial Mobility of Young People in Prague: A Pilot Study Using Mobile Phone Location Data. Sociologický časopis, 5 (48), 911-938. https://doi.org/10.13060/00380288.2012.48.5.05

Novak, J., Ahas, R., Aasa, A. and Silm, S. (2013). Application of mobile phone location data in mapping of commuting patterns and functional regionalisation: A pilot study of Estonia. Journal of Maps, 1 (9), 10-15. https://doi.org/10.1080/17445647.2012.762331

Olsson, G. (1970). Explanation, Prediction and Meaning Variance: An Assessment of Distance Interaction Models. Economic Geography, 46, 223-233. https://doi.org/10.2307/143140

Ouředníček, M., Nemeškal, J., Pospíšilova, L. and Hampl, M. (2019). Vymezení území pro Integrované teritoriální investice (ITI) v ČR: Technická metodika. Prague: Ministry of Regional Development Press. (In Czech)

Pentland, A. (2012). Reinventing Society in the Wake of Big Data. Edge. [online] Available at: https://www.edge.org/conversation/reinventing-society-in-the-wake-of-big-data [Accessed 10 July 2021].

Phithakkitnukoon, S., Smoreda, Z. and Olivier, P. (2012). Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data. PLoS ONE, 7 (6), 1-9. https://doi.org/10.1371/journal.pone.0039253

Press Conference on Challenges Faced by Countries Emerging from Conflicts in Conducting Census of Housing, Population. (2010). World population and Housing Census Programme. United Nations Statistics Division. [online] Available at: https://reliefweb.int/report/liberia/press-conference-challenges-faced-countries-emerging-conflicts-conducting-census [Accessed 12 Aug. 2021].

Ratti, C. (2005). Mobile Landscape - Graz in real time. In: Proceedings of 3rd Symposium on LBS & TeleCartography in Vienna University of Technology, 28-30.

Ratti, C., Sobolevsky, S., Calabrese, F., Andris, C., Reades, J., Martino, M., Claxton, R. and Strogatz, S. (2010). Redrawing the Map of Great Britain from a Network of Human Interactions. PLoS ONE, 5 (12), 1-6. https://doi.org/10.1371/journal.pone.0014248

Real Time Rome. (2006). MIT Senseable City Lab. [online] Available at: http://senseable.mit.edu/realtimerome/ [Accessed 10 July 2021].

Šcepanovic, S., Mishkovski, I., Hui, P. and Nurminen, J. (2015). Mobile Phone Call Data as a Regional Socio-Economic Proxy Indicator. PLoS ONE, 4 (10), 1-15. https://doi.org/10.1371/journal.pone.0124160

Schlich, R., Schönfelder, S., Hanson, S. and Axhausen, K. (2004). Structures of Leisure Travel: Temporal and Spatial Variability. Transport Review, 24, 219-237. https://doi.org/10.1080/0144164032000138742

Silm, S. and Ahas, R. (2014). The temporal variation of ethnic segregation in a city: Evidence from a mobile phone use dataset. Social Science Research, 47, 30-43. https://doi.org/10.1016/j.ssresearch.2014.03.011

Silm, S., Ahas, R. and Nuga, M. (2013). Gender differences in space-time mobility patterns in a post-communist city: a case study based on mobile positioning in the suburbs of Tallinn. Environment and Planning B: Planning and Design, 40 (5), 814-828. https://doi.org/10.1068/b38068

Smith-Clarke, C., Mashhadi, A. and Capra, L. (2014). Poverty on the Cheap: Estimating Poverty Maps Using Aggregated Mobile Communication Networks. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 511-520. https://doi.org/10.1145/2556288.2557358

Stelman, T. (2012). Trendit mapping population movements through mobile signals. NoCamels. [online] Available at: https://nocamels.com/2012/03/trendit-mapping-population-movements-through-mobile-signals/[Accessed 10 July 2021].

The Cancellation of Mobile Phone Tracking System for the London Olympics: An Overview. (2012). Tracking Mobile (TM). [online] Available at: https://trackingmobile.co.uk/the-cancellation-of-mobile-phone-tracking-system-for-the-london-olympics-an-overview/[Accessed 10 July 2021].

Tiru, M. (2014). Overview of the sources and challenges of mobile positioning data for statistics. In: International Conference on Big Data for Official Statistics in Beijing, 1-26.

Tizzoni, M., Bajardi, P., Decuyper, A., King, G., Schneider, C., Blondel, V., Smoreda, Z., González, M. and Colizza, V. (2014). On the use of human mobility proxies for modeling epidemics. PLoS Comput. Biol., 7 (10), 1-35. https://doi.org/10.1371/journal.pcbi.1003716

Tobler, W. R. (1970). A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography, 46, 234-240. https://doi.org/10.2307/143141

Versichele, M., Neutens, T., Goudeseune, S., van Bossche, F. and van de Weghe, W. (2012). Mobile Mapping of Sporting Event Spectators Using Bluetooth Sensors: Tour of Flanders Sensors. Sensors (Basel), 12 (10), 14196-14213. https://doi.org/10.3390/s121014196

Vogelová, M., Chaloupka, R. and Abrhám, J. (2018). Potential of new data sources in tourism. Slovak Journal of Public Policy and Public Administration, 5 (2). [online] Available at: https://sjpppa.fsvucm.sk/index.php/journal/article/view/83 [Accessed 12 Aug. 2021].

Wesolowski, A., Eagle, N., Tatem, A. and Smith, D. L. (2012). Quantifying the impact of human mobility on malaria. Science, 338 (6104), 267-270. https://doi.org/10.1126/science.1223467

Yadav, K., Kumar, A., Bharati, A. and Naik, V. (2014). Characterizing mobility patterns of people in developing countries using their mobile phone data. In: 2014 Sixth International Conference on Communication Systems and Networks (COMSNETS), 1-8. https://doi.org/10.1109/COMSNETS.2014.6734892

Опубликован
2021-06-30
Как цитировать
Бабкин, Р. А. (2021) «Опыт использования данных операторов сотовой связи в зарубежных экономико-географических исследованиях», Вестник Санкт-Петербургского университета. Науки о Земле, 66(3). doi: 10.21638/spbu07.2021.301.
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