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Urban Dynamic Estimation Using Mobile Phone Logs and Locally Varying Anisotropy

  • Oscar F. PeredoEmail author
  • José A. García
  • Ricardo Stuven
  • Julián M. Ortiz
Chapter
Part of the Quantitative Geology and Geostatistics book series

Abstract

In telecommunications, the billing data of each telephone, denoted call detail records (CDRs), are a large and rich database with information that can be geo-located. By analyzing the events logged in each antenna, a set of time series can be constructed measuring the number of voice and data events in each time of the day. One question that can be addressed using these data involves estimating the movement or flow of people in the city, which can be used for prediction and monitoring in transportation or urban planning. In this work, geostatistical estimation techniques such as kriging and inverse distance weighting (IDW) are used to numerically estimate the flow of people. In order to improve the accuracy of the model, secondary information is included in the estimation. This information represents the locally varying anisotropy (LVA) field associated with the major streets and roads in the city. By using this technique, the flow estimation can be obtained with a better quantitative and qualitative interpretation. In terms of storage and computing power, the volume of raw information is extremely large; for that reason big data technologies are mandatory to query the database. Additionally, if high-resolution grids are used in the estimation, high-performance computing techniques are necessary to speed up the numerical computations using LVA codes. Case studies are shown, using voice/data records from anonymized clients of Telefónica Movistar in Santiago, capital of Chile.

Keywords

Street Segment Ordinary Kriging Inverse Distance Weighting Hadoop Distribute File System Secondary Street 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors would like to acknowledge the project CORFO 13CEE2-21592 (2013-21592-1-INNOVA_PRODUCCION2013-21592-1), Telefónica Investigación y Desarrollo SPA and Telefónica Chile SA for the support and data provided in this study.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Oscar F. Peredo
    • 1
    Email author
  • José A. García
    • 1
  • Ricardo Stuven
    • 1
  • Julián M. Ortiz
    • 2
  1. 1.Telefónica R & DSantiagoChile
  2. 2.Department of Mining EngineeringUniversity of ChileSantiagoChile

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