att_abstract={{Characterizing human mobility patterns is critical to a deeper understanding of the effects of people’s travel on society and the environment. Location data from cellular telephone networks can shed light on human movements cheaply, frequently, and on a large scale. We have developed techniques for analyzing anonymized cellphone locations to explore various aspects of human mobility, in particular for hundreds of thousands of people in each of the Los Angeles, San Francisco, and New York metropolitan areas. Our results include measures of how far people travel every day, estimates of carbon footprints due to home-to-work commutes, maps of the residential areas that contribute workers to a city, and relative traffic volumes on commuting routes. We have validated the accuracy of our techniques through comparisons against ground truth provided by volunteers and against independent sources such as the US Census Bureau. Throughout our work, we have taken measures to preserve the privacy of cellphone users. This article presents an overview of our methodologies and findings.}},
	att_authors={rb2812, rc177e, kh1285, jl213k, jr6321, su2464, av8693, cv2452},
	att_categories={C_NSS.7, C_NSS.13, C_IIS.2},
	att_copyright_notice={{(c) ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Communications of the ACM {{, Volume 56}}{{, Issue 1}}{{, 2013-01-01}}.
	att_projects={ SagaCITY},
	author={Richard Becker and Ramon Caceres and Karrie Hanson and Sibren Isaacman and Ji Loh and Margaret Martonosi and James Rowland and Simon Urbanek and Alexander Varshavsky and Christopher Volinsky},
	institution={{Communications of the ACM}},
	title={{Human Mobility Characterization from Cellular Network Data}},