In this work we aim at studying spatio-temporal patterns of the population movement across a large city. We exploit the information on people position collected by the smartphone application of the Earthquake Network project and we adopt a dynamic model-based clustering approach to identify the patterns. The approach is applied to smartphone data collected in Santiago (Chile) over the period February-April 2016. Some preliminary results are presented and discussed.
Finazzi, F., Paci, L., Space-time clustering for identifying population patterns from smart-phone data, in SIS 2017. Statistics and Data Science: New Challenges, New Generations, (Firenze, 28-30 June 2017), Università degli Studi di Firenze, Firenze 2017: 1-6 [http://hdl.handle.net/10807/105368]
Space-time clustering for identifying population patterns from smart-phone data
Paci, LuciaSecondo
2017
Abstract
In this work we aim at studying spatio-temporal patterns of the population movement across a large city. We exploit the information on people position collected by the smartphone application of the Earthquake Network project and we adopt a dynamic model-based clustering approach to identify the patterns. The approach is applied to smartphone data collected in Santiago (Chile) over the period February-April 2016. Some preliminary results are presented and discussed.
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