Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network

By Jonathan Reades, F. Calabrese, Carlo Ratti. 2009

306 citations recorded by the source corpus.

Subfields: Building and Construction, Global and Planetary Change, Transportation

View Paper: https://www.semanticscholar.org/paper/368e588031b3354f26611a57055b58df72e75ab7

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In Building and Construction

In Global and Planetary Change

In Transportation

Citations in the corpus

Principal Component Analysis on Spatial Data: An Overview (2013, unknown): “As a different Reades, Calabrese, and Ratti (2009), where the spatio-PCA is computed for every point x, the results vary temporal structure of a rasterized representation of a continuously through the data space.”
Revealing daily travel patterns and city structure with taxi trip data (2013, background): “Keywords: GPS-enabled taxi data, intra-urban human mobility, urban structure, land use condition, Shanghai”
Measurements of POI-based mixed use and their relationships with neighbourhood vibrancy (2017, unknown): “Recent studies on urban analysis (Ratti et al. 2006, Reades et al. 2009, Louail et al. 2014) and land use (Toole et al. 2012; JacobsCrisioni et al. 2014; Pei et al. 2014) have shown that mobile phone data are a good proxy not only for the space-time dynamics of human activity but also for land…”
A new insight into land use classification based on aggregated mobile phone data (2013, methodology): “To identify and extract recurring patterns of mobile phone usage and relate them to some land-use types, Reades et al. (2009) proposed the eigen-decomposition method, a process similar to factoring but suitable for complex datasets.”
Smart cities of the future (2012, unknown): “Spatial interaction also manifests itself in strong spatial consistency in the function of the city, both defined by infrastructure and underlying urban planning, so as in terms of the ways people tend to use cities [38] and the temporal evolution of these patterns.”