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Robust Land Use Characterization of Urban Landscapes using Cell Phone Data

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First Workshop on Pervasive Urban Applications in conjuntion with 9th Int. Conf. on Pervasive Computing, San Francisco, CA, 2011

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Robust Land Use Characterization of Urban Landscapes using Cell Phone Data

  1. 1. <ul><li>Robust Land Use Characterization
  2. 2. of Urban Landscapes using Cell Phone Data </li></ul><ul>June 12, 2011 </ul><ul>Víctor Soto & Enrique Frías-Martínez </ul><ul>TELEFÓNICA I+D </ul>
  3. 3. <ul></ul><ul>Introduction </ul><ul>01 </ul><ul>Telefónica I+D </ul>
  4. 4. <ul><li>Goal: Land use of urban areas using Call Details Records. </li></ul><ul></ul>
  5. 5. <ul></ul><ul>Preliminaries </ul><ul>02 </ul><ul>Telefónica I+D </ul>
  6. 6. <ul>Cell Phone Network </ul><ul><li>Cell Phone networks are built using Base Transceiver Stations (BTS).
  7. 7. Each BTS will be characterized by a feature vector that describes the calling behavior area. </li></ul><ul></ul>
  8. 8. <ul>CDR dataset </ul><ul><li>Our Dataset </li></ul><ul><ul><li>1 month of phone call interactions.
  9. 9. 1100 Base Transceiver Stations.
  10. 10. Each CDR contains: </li><ul><li>phone Source | phone Destiny | bts Source | bts Destiny | DD/MM/YYYY | hh:mm:ss | d </li></ul><li>Phone number are encrypted to anonymize user identities. </li></ul></ul><ul></ul>
  11. 11. <ul></ul><ul>Activity Signature </ul><ul>03 </ul><ul>Telefónica I+D </ul>
  12. 12. <ul>Representations </ul><ul><li>Activity signature vectors are built: each component contains the number of managed calls by the BTS in 5-minute intervals. </li></ul><ul></ul>
  13. 13. <ul></ul><ul>Land Use Identification </ul><ul>04 </ul><ul>Telefónica I+D </ul>
  14. 14. <ul></ul>
  15. 15. <ul>Methodology (I) </ul><ul><li>Detect the number of fuzzy clusters c in the signatures dataset using subtractive clustering. </li></ul><ul></ul>
  16. 16. <ul></ul>
  17. 17. <ul></ul><ul>Robust Land Use Analysis </ul><ul>05 </ul><ul>Telefónica I+D </ul>
  18. 18. <ul>Why Robust Land Usage? </ul><ul><li>Land uses in urban landscapes are not well defined </li></ul><ul><ul><li>One lot can show several land uses at different degrees.
  19. 19. Often real and planned land uses won't match. </li></ul></ul><ul><li>The key: </li></ul><ul><ul><li>Fuzzy c-means returns the membership degree of each object to the class representatives. These membership indices can be used to filter robust land uses. </li></ul></ul><ul></ul>
  20. 20. <ul>Filtering process </ul><ul></ul>
  21. 21. <ul>Filtering process </ul><ul></ul>
  22. 22. <ul></ul><ul>Validation </ul><ul>06 </ul><ul>Telefónica I+D </ul>
  23. 23. <ul></ul>
  24. 24. <ul>Cluster 1: Industrial & Office </ul><ul></ul>
  25. 25. <ul>Cluster 2: Business & Commercial </ul><ul></ul>
  26. 26. <ul>Cluster 3: Nightlife </ul><ul></ul>
  27. 27. <ul>Cluster 4: Leisure & Transport </ul><ul></ul>
  28. 28. <ul>Cluster 5: Residential </ul><ul></ul>
  29. 29. <ul></ul><ul>Conclusions & Future Work </ul><ul>07 </ul><ul>Telefónica I+D </ul>
  30. 30. <ul><li>Specific uses for City Halls. </li></ul><ul></ul>
  31. 31. Questions?

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