Supersampling and Network Reconstruction of Urban Mobility
Name
Sagarra-2015-Supersampling and Ne.pdf
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1.26 MB
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Checksum (MD5)
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Author(s)
Sagarra, Oleguer
Szell, Michael
Santi, Paolo
Ratti, Carlo
Diaz-Guilera, Albert
Sagarra. Oleguer
Date Issued
August 2015
Journal
PLOS ONE
Publisher
Public Library of Science
Citation
Sagarra, Oleguer, Michael Szell, Paolo Santi, Albert Díaz-Guilera, and Carlo Ratti. “Supersampling and Network Reconstruction of Urban Mobility.” Edited by Matjaz Perc. PLOS ONE 10, no. 8 (August 14, 2015): e0134508.
Version
Final published version
Abstract
Understanding human mobility is of vital importance for urban planning, epidemiology, and many other fields that draw policies from the activities of humans in space. Despite the recent availability of large-scale data sets of GPS traces or mobile phone records capturing human mobility, typically only a subsample of the population of interest is represented, giving a possibly incomplete picture of the entire system under study. Methods to reliably extract mobility information from such reduced data and to assess their sampling biases are lacking. To that end, we analyzed a data set of millions of taxi movements in New York City. We first show that, once they are appropriately transformed, mobility patterns are highly stable over long time scales. Based on this observation, we develop a supersampling methodology to reliably extrapolate mobility records from a reduced sample based on an entropy maximization procedure, and we propose a number of network-based metrics to assess the accuracy of the predicted vehicle flows. Our approach provides a well founded way to exploit temporal patterns to save effort in recording mobility data, and opens the possibility to scale up data from limited records when information on the full system is required.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Massachusetts Institute of Technology. SENSEable City Laboratory
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0134508
