Mining Urban Performance: Scale-Independent Classification of Cities Based on Individual Economic Transactions
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Ratti_Mining urban.pdf
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Author(s)
Sobolevsky, Stanislav
Sitko, Izabela
Tachet des Combes, Remi
Hawelka, B.
Murillo Arias, Juan
Ratti, Carlo
Date Issued
May 2014
Journal
Proceedings of the 2014 ASE Big Data/Social Com/Cyber Security Conference
Publisher
Academy of Science and Engineering
Citation
Sobolevsky, S., I. Sitko, R. Tachet des Combes, B. Hawelka, J. Murillo Arias, and C. Ratti. "Mining Urban Performance: Scale-Independent Classification of Cities Based on Individual Economic Transactions." 2014 ASE Big Data/Social Com/Cyber Security Conference (May 2014).
Version
Author's final manuscript
Abstract
Intensive development of urban systems creates a number of challenges for urban planners and policy makers in order to maintain sustainable growth. Running efficient urban policies requires meaningful urban metrics, which could quantify important urban characteristics including various aspects of an actual human behavior. Since a city size is known to have a major, yet often nonlinear, impact on the human activity, it also becomes important to develop scale-free metrics that capture qualitative city properties, beyond the effects of scale. Recent availability of extensive datasets created by human activity involving digital technologies creates new opportunities in this area. In this paper we propose a novel approach of city scoring and classification based on quantitative scale-free metrics related to economic activity of city residents, as well as domestic and foreign visitors. It is demonstrated on the example of Spain, but the proposed methodology is of a general character. We employ a new source of large-scale ubiquitous data, which consists of anonymized countrywide records of bank card transactions collected by one of the largest Spanish banks. Different aspects of the classification reveal important properties of Spanish cities, which significantly complement the pattern that might be discovered with the official socioeconomic statistics.
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-Noncommercial-Share Alike
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DOI of Published Version
http://www.ase360.org/handle/123456789/48
